Publications

2020

J. R. Abella, D. A. Antunes, K. Jackson, G. Lizée, C. Clementi, and L. E. Kavraki, “Markov state modeling reveals alternative unbinding pathways for peptide–MHC complexes,” Proceedings of the National Academy of Sciences, vol. 117, no. 48, pp. 30610–30618, Dec. 2020.

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BibTeX

@article{abella2020-pnas,
  author = "Abella, Jayvee R. and Antunes, Dinler A. and Jackson, Kyle and Liz{\'e}e, Gregory and Clementi, Cecilia and Kavraki, Lydia E.",
  title = "Markov state modeling reveals alternative unbinding pathways for peptide{\textendash}MHC complexes",
  year = "2020",
  doi = "10.1073/pnas.2007246117",
  pmid = "33184174",
  month = dec,
  volume = "117",
  number = "48",
  pages = "30610--30618",
  publisher = "National Academy of Sciences",
  abstract = "Peptide binding to MHC receptors is part of a central biological process that enables our immune system to attack diseased cells. We use molecular simulations to illuminate the mechanisms driving stable peptide{\textendash}MHC binding. Our simulation framework produces an atomistic model of the unbinding dynamics for a given peptide{\textendash}MHC, which quantifies transitions between the major states of the system (bound, intermediate, and unbound). We applied this framework to study the binding of a SARS-CoV peptide to the HLA-A*24:02 receptor. This work revealed the unexpected importance of peptide{\textquoteright}s position 4 in driving the stability of the complex, a finding with broader biomedical implications. Our methods can be applied to other peptide{\textendash}MHC complexes, requiring only a 3D model as input.Peptide binding to major histocompatibility complexes (MHCs) is a central component of the immune system, and understanding the mechanism behind stable peptide{\textendash}MHC binding will aid the development of immunotherapies. While MHC binding is mostly influenced by the identity of the so-called anchor positions of the peptide, secondary interactions from nonanchor positions are known to play a role in complex stability. However, current MHC-binding prediction methods lack an analysis of the major conformational states and might underestimate the impact of secondary interactions. In this work, we present an atomically detailed analysis of peptide{\textendash}MHC binding that can reveal the contributions of any interaction toward stability. We propose a simulation framework that uses both umbrella sampling and adaptive sampling to generate a Markov state model (MSM) for a coronavirus-derived peptide (QFKDNVILL), bound to one of the most prevalent MHC receptors in humans (HLA-A24:02). While our model reaffirms the importance of the anchor positions of the peptide in establishing stable interactions, our model also reveals the underestimated importance of position 4 (p4), a nonanchor position. We confirmed our results by simulating the impact of specific peptide mutations and validated these predictions through competitive binding assays. By comparing the MSM of the wild-type system with those of the D4A and D4P mutations, our modeling reveals stark differences in unbinding pathways. The analysis presented here can be applied to any peptide{\textendash}MHC complex of interest with a structural model as input, representing an important step toward comprehensive modeling of the MHC class I pathway.Code for umbrella sampling, adaptive sampling, and MSM analysis, as well as representative structures, can be found in Github at https://github.com/KavrakiLab/adaptive-sampling-pmhc. Simulation data are available upon request.",
  issn = "0027-8424",
  url = "https://www.pnas.org/content/early/2020/11/10/2007246117",
  eprint = "https://www.pnas.org/content/early/2020/11/10/2007246117.full.pdf",
  journal = "Proceedings of the National Academy of Sciences"
}

Abstract

Peptide binding to MHC receptors is part of a central biological process that enables our immune system to attack diseased cells. We use molecular simulations to illuminate the mechanisms driving stable peptide–MHC binding. Our simulation framework produces an atomistic model of the unbinding dynamics for a given peptide–MHC, which quantifies transitions between the major states of the system (bound, intermediate, and unbound). We applied this framework to study the binding of a SARS-CoV peptide to the HLA-A*24:02 receptor. This work revealed the unexpected importance of peptide’s position 4 in driving the stability of the complex, a finding with broader biomedical implications. Our methods can be applied to other peptide–MHC complexes, requiring only a 3D model as input.Peptide binding to major histocompatibility complexes (MHCs) is a central component of the immune system, and understanding the mechanism behind stable peptide–MHC binding will aid the development of immunotherapies. While MHC binding is mostly influenced by the identity of the so-called anchor positions of the peptide, secondary interactions from nonanchor positions are known to play a role in complex stability. However, current MHC-binding prediction methods lack an analysis of the major conformational states and might underestimate the impact of secondary interactions. In this work, we present an atomically detailed analysis of peptide–MHC binding that can reveal the contributions of any interaction toward stability. We propose a simulation framework that uses both umbrella sampling and adaptive sampling to generate a Markov state model (MSM) for a coronavirus-derived peptide (QFKDNVILL), bound to one of the most prevalent MHC receptors in humans (HLA-A24:02). While our model reaffirms the importance of the anchor positions of the peptide in establishing stable interactions, our model also reveals the underestimated importance of position 4 (p4), a nonanchor position. We confirmed our results by simulating the impact of specific peptide mutations and validated these predictions through competitive binding assays. By comparing the MSM of the wild-type system with those of the D4A and D4P mutations, our modeling reveals stark differences in unbinding pathways. The analysis presented here can be applied to any peptide–MHC complex of interest with a structural model as input, representing an important step toward comprehensive modeling of the MHC class I pathway.Code for umbrella sampling, adaptive sampling, and MSM analysis, as well as representative structures, can be found in Github at https://github.com/KavrakiLab/adaptive-sampling-pmhc. Simulation data are available upon request.

D. Devaurs, D. A. Antunes, and L. E. Kavraki, “Computational analysis of complement inhibitor compstatin using molecular dynamics,” J Mol Model, vol. 26, no. 9, p. 231, Aug. 2020.

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BibTeX

@article{devaurs2020-compstatin,
  pmid = "32789582",
  doi = "10.1007/s00894-020-04472-8",
  author = "Devaurs, D. and Antunes, D. A. and Kavraki, L. E.",
  title = "{{C}omputational analysis of complement inhibitor compstatin using molecular dynamics}",
  journal = "J Mol Model",
  year = "2020",
  volume = "26",
  number = "9",
  pages = "231",
  month = aug,
  abstract = "The complement system plays a major role in human immunity, but its abnormal activation can have severe pathological impacts. By mimicking a natural mechanism of complement regulation, the small
  peptide compstatin has proven to be a very promising complement inhibitor. Over the years, several compstatin analogs have been created, with an improved inhibitory potency. A recent analog is being developed as a candidate drug against several pathological conditions, including COVID-19. However, the reasons behind its higher potency and increased binding affinity to complement proteins are not fully clear. This computational study highlights mechanistic properties of several compstatin analogs, thus complementing previous experimental studies. We perform molecular dynamics simulations involving six analogs alone in solution and two complexes with compstatin bound to complement component 3. These simulations reveal that all the analogs we consider, except the original compstatin, naturally adopt a pre-bound conformation in solution. Interestingly, this set of analogs adopting a pre-bound conformation includes analogs that were not known to benefit from this behavior. We also show that the most recent compstatin analog (among those we consider) forms a stronger hydrogen bond network with its complement receptor than an earlier analog."
}

Abstract

The complement system plays a major role in human immunity, but its abnormal activation can have severe pathological impacts. By mimicking a natural mechanism of complement regulation, the small peptide compstatin has proven to be a very promising complement inhibitor. Over the years, several compstatin analogs have been created, with an improved inhibitory potency. A recent analog is being developed as a candidate drug against several pathological conditions, including COVID-19. However, the reasons behind its higher potency and increased binding affinity to complement proteins are not fully clear. This computational study highlights mechanistic properties of several compstatin analogs, thus complementing previous experimental studies. We perform molecular dynamics simulations involving six analogs alone in solution and two complexes with compstatin bound to complement component 3. These simulations reveal that all the analogs we consider, except the original compstatin, naturally adopt a pre-bound conformation in solution. Interestingly, this set of analogs adopting a pre-bound conformation includes analogs that were not known to benefit from this behavior. We also show that the most recent compstatin analog (among those we consider) forms a stronger hydrogen bond network with its complement receptor than an earlier analog.

D. A. Antunes, J. R. Abella, S. Hall-Swan, D. Devaurs, A. Conev, M. Moll, G. Lizée, and L. E. Kavraki, “HLA-Arena: a customizable environment for the structural modeling and analysis of peptide-HLA complexes for cancer immunotherapy,” JCO Clinical Cancer Informatics, vol. 4, pp. 623–636, Jul. 2020.

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BibTeX

@article{antunes2020-hla-arena,
  pmid = "32667823",
  doi = "10.1200/CCI.19.00123",
  author = "Antunes, D. A. and Abella, J. R. and Hall-Swan, S. and Devaurs, D. and Conev, A. and Moll, M. and Liz\'{e}e, G. and Kavraki, L. E.",
  title = "{HLA}-{A}rena: a customizable environment for the structural modeling and analysis of peptide-{HLA} complexes for cancer immunotherapy",
  journal = "JCO Clinical Cancer Informatics",
  year = "2020",
  volume = "4",
  pages = "623--636",
  keywords = "fundamentals of protein modeling, proteins and drugs, other biomedical computing",
  month = jul,
  abstract = "PURPOSE: HLA protein receptors play a key role in cellular immunity. They bind intracellular peptides and display them for recognition by T-cell lymphocytes. Because T-cell activation is partially driven by structural features of these peptide-HLA complexes, their structural modeling and analysis are becoming central components of cancer immunotherapy projects. Unfortunately, this kind of analysis is limited by the small number of experimentally determined structures of peptide-HLA complexes. Overcoming this limitation requires developing novel computational methods to model and analyze peptide-HLA structures.
  
  METHODS: Here we describe a new platform for the structural modeling and analysis of peptide-HLA complexes, called HLA-Arena, which we have implemented using Jupyter Notebook and Docker. It is a customizable environment that facilitates the use of computational tools, such as APE-Gen and DINC, which we have previously applied to peptide-HLA complexes. By integrating other commonly used tools, such as MODELLER and MHCflurry, this environment includes support for diverse tasks in structural modeling, analysis, and visualization.
  
  RESULTS To illustrate the capabilities of HLA-Arena, we describe 3 example workflows applied to peptide-HLA complexes. Leveraging the strengths of our tools, DINC and APE-Gen, the first 2 workflows show how to perform geometry prediction for peptide-HLA complexes and structure-based binding prediction, respectively. The third workflow presents an example of large-scale virtual screening of peptides for multiple HLA alleles.
  
  CONCLUSION: These workflows illustrate the potential benefits of HLA-Arena for the structural modeling and analysis of peptide-HLA complexes. Because HLA-Arena can easily be integrated within larger computational pipelines, we expect its potential impact to vastly increase. For instance, it could be used to conduct structural analyses for personalized cancer immunotherapy, neoantigen discovery, or vaccine development."
}

Abstract

PURPOSE: HLA protein receptors play a key role in cellular immunity. They bind intracellular peptides and display them for recognition by T-cell lymphocytes. Because T-cell activation is partially driven by structural features of these peptide-HLA complexes, their structural modeling and analysis are becoming central components of cancer immunotherapy projects. Unfortunately, this kind of analysis is limited by the small number of experimentally determined structures of peptide-HLA complexes. Overcoming this limitation requires developing novel computational methods to model and analyze peptide-HLA structures. METHODS: Here we describe a new platform for the structural modeling and analysis of peptide-HLA complexes, called HLA-Arena, which we have implemented using Jupyter Notebook and Docker. It is a customizable environment that facilitates the use of computational tools, such as APE-Gen and DINC, which we have previously applied to peptide-HLA complexes. By integrating other commonly used tools, such as MODELLER and MHCflurry, this environment includes support for diverse tasks in structural modeling, analysis, and visualization. RESULTS To illustrate the capabilities of HLA-Arena, we describe 3 example workflows applied to peptide-HLA complexes. Leveraging the strengths of our tools, DINC and APE-Gen, the first 2 workflows show how to perform geometry prediction for peptide-HLA complexes and structure-based binding prediction, respectively. The third workflow presents an example of large-scale virtual screening of peptides for multiple HLA alleles. CONCLUSION: These workflows illustrate the potential benefits of HLA-Arena for the structural modeling and analysis of peptide-HLA complexes. Because HLA-Arena can easily be integrated within larger computational pipelines, we expect its potential impact to vastly increase. For instance, it could be used to conduct structural analyses for personalized cancer immunotherapy, neoantigen discovery, or vaccine development.

J. R. Abella, D. A. Antunes, C. Clementi, and L. E. Kavraki, “Large-scale structure-based prediction of stable peptide binding to Class I HLAs using random forests,” Frontiers in Immunology, vol. 11, no. 1583, Jul. 2020.

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BibTeX

@article{abella2020-frontiers-random-forest,
  doi = "10.3389/fimmu.2020.01583",
  author = "Abella, J. R. and Antunes, D. A. and Clementi, C. and Kavraki, L. E.",
  title = "Large-scale structure-based prediction of stable peptide binding to {Class I HLAs} using random forests",
  keywords = "fundamentals of protein modeling, proteins and drugs, other biomedical computing",
  journal = "Frontiers in Immunology",
  year = "2020",
  volume = "11",
  number = "1583",
  month = jul,
  abstract = "Prediction of stable peptide binding to Class I HLAs is an important component for designing immunotherapies. While the best performing predictors are based on machine learning algorithms trained on peptide-HLA (pHLA) sequences, the use of structure for training predictors deserves further exploration. Given enough pHLA structures, a predictor based on the residue-residue interactions found in these structures has the potential to generalize for alleles with little or no experimental data. We have previously developed APE-Gen, a modeling approach able to produce pHLA structures in a scalable manner. In this work we use APE-Gen to model over 150,000 pHLA structures, the largest dataset of its kind, which were used to train a structure-based pan-allele model. We extract simple, homogenous features based on residue-residue distances between peptide and HLA, and build a random forest model for predicting stable pHLA binding. Our model achieves competitive AUROC values on leave-one-allele-out validation tests using significantly less data when compared to popular sequence-based methods. Additionally, our model offers an interpretation analysis that can reveal how the model composes the features to arrive at any given prediction. This interpretation analysis can be used to check if the model is in line with chemical intuition, and we showcase particular examples. Our work is a significant step toward using structure to achieve generalizable and more interpretable prediction for stable pHLA binding."
}

Abstract

Prediction of stable peptide binding to Class I HLAs is an important component for designing immunotherapies. While the best performing predictors are based on machine learning algorithms trained on peptide-HLA (pHLA) sequences, the use of structure for training predictors deserves further exploration. Given enough pHLA structures, a predictor based on the residue-residue interactions found in these structures has the potential to generalize for alleles with little or no experimental data. We have previously developed APE-Gen, a modeling approach able to produce pHLA structures in a scalable manner. In this work we use APE-Gen to model over 150,000 pHLA structures, the largest dataset of its kind, which were used to train a structure-based pan-allele model. We extract simple, homogenous features based on residue-residue distances between peptide and HLA, and build a random forest model for predicting stable pHLA binding. Our model achieves competitive AUROC values on leave-one-allele-out validation tests using significantly less data when compared to popular sequence-based methods. Additionally, our model offers an interpretation analysis that can reveal how the model composes the features to arrive at any given prediction. This interpretation analysis can be used to check if the model is in line with chemical intuition, and we showcase particular examples. Our work is a significant step toward using structure to achieve generalizable and more interpretable prediction for stable pHLA binding.

T. Arns, D. A. Antunes, J. R. Abella, M. M. Rigo, L. E. Kavraki, S. Giuliatti, and E. A. Donadi, “Structural Modeling and Molecular Dynamics of the Immune Checkpoint Molecule HLA-G,” Frontiers in Immunology, vol. 11, p. 2882, 2020.

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BibTeX

@article{arns2020,
  author = "Arns, Thais and Antunes, Dinler A. and Abella, Jayvee R. and Rigo, Maurício M. and Kavraki, Lydia E. and Giuliatti, Silvana and Donadi, Eduardo A.",
  title = "Structural Modeling and Molecular Dynamics of the Immune Checkpoint Molecule HLA-G",
  journal = "Frontiers in Immunology",
  volume = "11",
  pages = "2882",
  year = "2020",
  url = "https://www.frontiersin.org/article/10.3389/fimmu.2020.575076",
  doi = "10.3389/fimmu.2020.575076",
  issn = "1664-3224",
  abstract = "HLA-G is considered to be an immune checkpoint molecule, a function that is closely linked to the structure and dynamics of the different HLA-G isoforms. Unfortunately, little is known about the structure and dynamics of these isoforms. For instance, there are only seven crystal structures of HLA-G molecules, being all related to a single isoform, and in some cases lacking important residues associated to the interaction with leukocyte receptors. In addition, they lack information on the dynamics of both membrane-bound HLA-G forms, and soluble forms. We took advantage of in silico strategies to disclose the dynamic behavior of selected HLA-G forms, including the membrane-bound HLA-G1 molecule, soluble HLA-G1 dimer, and HLA-G5 isoform. Both the membrane-bound HLA-G1 molecule and the soluble HLA-G1 dimer were quite stable. Residues involved in the interaction with ILT2 and ILT4 receptors (α3 domain) were very close to the lipid bilayer in the complete HLA-G1 molecule, which might limit accessibility. On the other hand, these residues can be completely exposed in the soluble HLA-G1 dimer, due to the free rotation of the disulfide bridge (Cys42/Cys42). In fact, we speculate that this free rotation of each protomer (i.e., the chains composing the dimer) could enable alternative binding modes for ILT2/ILT4 receptors, which in turn could be associated with greater affinity of the soluble HLA-G1 dimer. Structural analysis of the HLA-G5 isoform demonstrated higher stability for the complex containing the peptide and coupled β2-microglobulin, while structures lacking such domains were significantly unstable. This study reports for the first time structural conformations for the HLA-G5 isoform and the dynamic behavior of HLA-G1 molecules under simulated biological conditions. All modeled structures were made available through GitHub (https://github.com/KavrakiLab/), enabling their use as templates for modeling other alleles and isoforms, as well as for other computational analyses to investigate key molecular interactions."
}

Abstract

HLA-G is considered to be an immune checkpoint molecule, a function that is closely linked to the structure and dynamics of the different HLA-G isoforms. Unfortunately, little is known about the structure and dynamics of these isoforms. For instance, there are only seven crystal structures of HLA-G molecules, being all related to a single isoform, and in some cases lacking important residues associated to the interaction with leukocyte receptors. In addition, they lack information on the dynamics of both membrane-bound HLA-G forms, and soluble forms. We took advantage of in silico strategies to disclose the dynamic behavior of selected HLA-G forms, including the membrane-bound HLA-G1 molecule, soluble HLA-G1 dimer, and HLA-G5 isoform. Both the membrane-bound HLA-G1 molecule and the soluble HLA-G1 dimer were quite stable. Residues involved in the interaction with ILT2 and ILT4 receptors (α3 domain) were very close to the lipid bilayer in the complete HLA-G1 molecule, which might limit accessibility. On the other hand, these residues can be completely exposed in the soluble HLA-G1 dimer, due to the free rotation of the disulfide bridge (Cys42/Cys42). In fact, we speculate that this free rotation of each protomer (i.e., the chains composing the dimer) could enable alternative binding modes for ILT2/ILT4 receptors, which in turn could be associated with greater affinity of the soluble HLA-G1 dimer. Structural analysis of the HLA-G5 isoform demonstrated higher stability for the complex containing the peptide and coupled β2-microglobulin, while structures lacking such domains were significantly unstable. This study reports for the first time structural conformations for the HLA-G5 isoform and the dynamic behavior of HLA-G1 molecules under simulated biological conditions. All modeled structures were made available through GitHub (https://github.com/KavrakiLab/), enabling their use as templates for modeling other alleles and isoforms, as well as for other computational analyses to investigate key molecular interactions.

2019

D. Devaurs, D. A. Antunes, S. Hall-Swan, N. Mitchell, M. Moll, G. Lizée, and L. E. Kavraki, “Using parallelized incremental meta-docking can solve the conformational sampling issue when docking large ligands to proteins,” BMC Molecular and Cell Biology, vol. 20, no. 1, p. 42, Sep. 2019.

pdf publisher

BibTeX

@article{devaurs2019using-parallelized-incremental-meta-docking,
  grants = "NIH 1R21CA209941",
  author = "Devaurs, Didier and Antunes, Dinler A and Hall-Swan, Sarah and Mitchell, Nicole and Moll, Mark and Liz{\'e}e, Gregory and Kavraki, Lydia E",
  journal = "BMC Molecular and Cell Biology",
  title = "Using parallelized incremental meta-docking can solve the conformational sampling issue when docking large ligands to proteins",
  volume = "20",
  number = "1",
  pages = "42",
  month = sep,
  year = "2019",
  keywords = "proteins and drugs",
  doi = "10.1186/s12860-019-0218-z",
  abstract = "Background: Docking large ligands, and especially peptides, to protein receptors is still considered a challenge in computational structural biology. Besides the issue of accurately scoring the binding modes of a protein-ligand complex produced by a molecular docking tool, the conformational sampling of a large ligand is also often considered a challenge because of its underlying combinatorial complexity. In this study, we evaluate the impact of using parallelized and incremental paradigms on the accuracy and performance of conformational sampling when docking large ligands. We use ﬁve datasets of protein-ligand complexes involving ligands that could not be accurately docked by classical protein-ligand docking tools in previous similar studies.
  
  Results: Our computational evaluation shows that simply increasing the amount of conformational sampling performed by a protein-ligand docking tool, such as Vina, by running it for longer is rarely beneﬁcial. Instead, it is more eﬃcient and advantageous to run several short instances of this docking tool in parallel and group their results together, in a straightforward parallelized docking protocol. Even greater accuracy and eﬃciency are achieved by our parallelized incremental meta-docking tool, DINC, showing the additional beneﬁts of its incremental paradigm. Using DINC, we could accurately reproduce the vast majority of the protein-ligand complexes we considered.
  
  Conclusions: Our study suggests that, even when trying to dock large ligands to proteins, the conformational sampling of the ligand should no longer be considered an issue, as simple docking protocols using existing tools can solve it. Therefore, scoring should currently be regarded as the biggest unmet challenge in molecular docking.
  
  Keywords: molecular docking; protein-ligand docking; protein-peptide docking; conformational sampling; scoring; parallelism; incremental protocol"
}

Abstract

Background: Docking large ligands, and especially peptides, to protein receptors is still considered a challenge in computational structural biology. Besides the issue of accurately scoring the binding modes of a protein-ligand complex produced by a molecular docking tool, the conformational sampling of a large ligand is also often considered a challenge because of its underlying combinatorial complexity. In this study, we evaluate the impact of using parallelized and incremental paradigms on the accuracy and performance of conformational sampling when docking large ligands. We use ﬁve datasets of protein-ligand complexes involving ligands that could not be accurately docked by classical protein-ligand docking tools in previous similar studies. Results: Our computational evaluation shows that simply increasing the amount of conformational sampling performed by a protein-ligand docking tool, such as Vina, by running it for longer is rarely beneﬁcial. Instead, it is more eﬃcient and advantageous to run several short instances of this docking tool in parallel and group their results together, in a straightforward parallelized docking protocol. Even greater accuracy and eﬃciency are achieved by our parallelized incremental meta-docking tool, DINC, showing the additional beneﬁts of its incremental paradigm. Using DINC, we could accurately reproduce the vast majority of the protein-ligand complexes we considered. Conclusions: Our study suggests that, even when trying to dock large ligands to proteins, the conformational sampling of the ligand should no longer be considered an issue, as simple docking protocols using existing tools can solve it. Therefore, scoring should currently be regarded as the biggest unmet challenge in molecular docking. Keywords: molecular docking; protein-ligand docking; protein-peptide docking; conformational sampling; scoring; parallelism; incremental protocol

C. F. Soon, S. Zhang, P. V. Suneetha, D. A. Antunes, M. P. Manns, S. Raha, C. Schultze-Florey, I. Prinz, H. Wedemeyer, M. S. Chen, and M. Cornberg, “Hepatitis E Virus (HEV)-Specific T Cell Receptor Cross-Recognition: Implications for Immunotherapy,” Frontiers in Immunology, vol. 10, p. 2076, 2019.

pdf publisher

BibTeX

@article{soon2019-hev-immunotherapy,
  pmid = "31552033",
  doi = "10.3389/fimmu.2019.02076",
  author = "Soon, Chai Fen and Zhang, Shihong and Suneetha, Pothakamuri Venkata and Antunes, Dinler Amaral and Manns, Michael Peter and Raha, Solaiman and Schultze-Florey, Christian and Prinz, Immo and Wedemeyer, Heiner and Chen, Margaret Sällberg and Cornberg, Markus",
  title = "{Hepatitis E Virus (HEV)-Specific T Cell Receptor Cross-Recognition: Implications for Immunotherapy}",
  journal = "Frontiers in Immunology",
  year = "2019",
  volume = "10",
  pages = "2076",
  keywords = "cross-reactivity, immunotherapy, viral immunity",
  abstract = "T cell immunotherapy is a concept developed for the treatment of cancer and infectious diseases, based on cytotoxic T lymphocytes to target tumor- or pathogen-specific antigens. Antigen-specificity of the T cell receptors (TCRs) is an important selection criterion in the developmental design of immunotherapy. However, off-target specificity is a possible autoimmunity concern if the engineered antigen-specific T cells are cross-reacting to self-peptides in-vivo. In our recent work, we identified several hepatitis E virus (HEV)-specific TCRs as potential candidates to be developed into T cell therapy to treat chronic hepatitis E. One of the identified TCRs, targeting a HLA-A2-restricted epitope at the RNA-dependent RNA polymerase (HEV-1527: LLWNTVWNM), possessed a unique multiple glycine motif in the TCR-β CDR3, which might be a factor inducing cross-reactivity. The aim of our study was to explore if this TCR could cross-recognize self-peptides to underlay autoimmunity. Indeed, we found that this HEV-1527-specific TCR could also cross-recognize an apoptosis-related epitope, Nonmuscle Myosin Heavy Chain 9 (MYH9-478: QLFNHTMFI). While this TCR had dual specificities to both viral epitope and a self-antigen by double Dextramer binding, it was selectively functional against HEV-1527 but not activated against MYH9-478. The consecutive glycine motif in β chain may be the reason promoting TCR binding promiscuity to recognize a secondary target, thereby facilitating cross-recognition. In conclusion, candidate TCRs for immunotherapy development should be screened for autoimmune potential, especially when the TCRs exhibit unique sequence pattern."
}

Abstract

T cell immunotherapy is a concept developed for the treatment of cancer and infectious diseases, based on cytotoxic T lymphocytes to target tumor- or pathogen-specific antigens. Antigen-specificity of the T cell receptors (TCRs) is an important selection criterion in the developmental design of immunotherapy. However, off-target specificity is a possible autoimmunity concern if the engineered antigen-specific T cells are cross-reacting to self-peptides in-vivo. In our recent work, we identified several hepatitis E virus (HEV)-specific TCRs as potential candidates to be developed into T cell therapy to treat chronic hepatitis E. One of the identified TCRs, targeting a HLA-A2-restricted epitope at the RNA-dependent RNA polymerase (HEV-1527: LLWNTVWNM), possessed a unique multiple glycine motif in the TCR-β CDR3, which might be a factor inducing cross-reactivity. The aim of our study was to explore if this TCR could cross-recognize self-peptides to underlay autoimmunity. Indeed, we found that this HEV-1527-specific TCR could also cross-recognize an apoptosis-related epitope, Nonmuscle Myosin Heavy Chain 9 (MYH9-478: QLFNHTMFI). While this TCR had dual specificities to both viral epitope and a self-antigen by double Dextramer binding, it was selectively functional against HEV-1527 but not activated against MYH9-478. The consecutive glycine motif in β chain may be the reason promoting TCR binding promiscuity to recognize a secondary target, thereby facilitating cross-recognition. In conclusion, candidate TCRs for immunotherapy development should be screened for autoimmune potential, especially when the TCRs exhibit unique sequence pattern.

J. R. Abella, D. A. Antunes, C. Clementi, and L. E. Kavraki, “APE-Gen: A Fast Method for Generating Ensembles of Bound Peptide-MHC Conformations,” Molecules, vol. 24, no. 5, 2019.

pdf publisher

BibTeX

@article{abella2019-apegen,
  author = "Abella, Jayvee R. and Antunes, Dinler A. and Clementi, Cecilia and Kavraki, Lydia E.",
  title = "APE-Gen: A Fast Method for Generating Ensembles of Bound Peptide-MHC Conformations",
  journal = "Molecules",
  volume = "24",
  year = "2019",
  number = "5",
  article-number = "881",
  url = "http://www.mdpi.com/1420-3049/24/5/881",
  issn = "1420-3049",
  abstract = "The Class I Major Histocompatibility Complex (MHC) is a central protein in immunology as it binds to intracellular peptides and displays them at the cell surface for recognition by T-cells. The structural analysis of bound peptide-MHC complexes (pMHCs) holds the promise of interpretable and general binding prediction (i.e., testing whether a given peptide binds to a given MHC). However, structural analysis is limited in part by the difficulty in modelling pMHCs given the size and flexibility of the peptides that can be presented by MHCs. This article describes APE-Gen (Anchored Peptide-MHC Ensemble Generator), a fast method for generating ensembles of bound pMHC conformations. APE-Gen generates an ensemble of bound conformations by iterated rounds of (i) anchoring the ends of a given peptide near known pockets in the binding site of the MHC, (ii) sampling peptide backbone conformations with loop modelling, and then (iii) performing energy minimization to fix steric clashes, accumulating conformations at each round. APE-Gen takes only minutes on a standard desktop to generate tens of bound conformations, and we show the ability of APE-Gen to sample conformations found in X-ray crystallography even when only sequence information is used as input. APE-Gen has the potential to be useful for its scalability (i.e., modelling thousands of pMHCs or even non-canonical longer peptides) and for its use as a flexible search tool. We demonstrate an example for studying cross-reactivity.",
  doi = "10.3390/molecules24050881",
  keywords = "fundamentals of protein modeling"
}

Abstract

The Class I Major Histocompatibility Complex (MHC) is a central protein in immunology as it binds to intracellular peptides and displays them at the cell surface for recognition by T-cells. The structural analysis of bound peptide-MHC complexes (pMHCs) holds the promise of interpretable and general binding prediction (i.e., testing whether a given peptide binds to a given MHC). However, structural analysis is limited in part by the difficulty in modelling pMHCs given the size and flexibility of the peptides that can be presented by MHCs. This article describes APE-Gen (Anchored Peptide-MHC Ensemble Generator), a fast method for generating ensembles of bound pMHC conformations. APE-Gen generates an ensemble of bound conformations by iterated rounds of (i) anchoring the ends of a given peptide near known pockets in the binding site of the MHC, (ii) sampling peptide backbone conformations with loop modelling, and then (iii) performing energy minimization to fix steric clashes, accumulating conformations at each round. APE-Gen takes only minutes on a standard desktop to generate tens of bound conformations, and we show the ability of APE-Gen to sample conformations found in X-ray crystallography even when only sequence information is used as input. APE-Gen has the potential to be useful for its scalability (i.e., modelling thousands of pMHCs or even non-canonical longer peptides) and for its use as a flexible search tool. We demonstrate an example for studying cross-reactivity.

2018

D. A. Antunes, J. R. Abella, D. Devaurs, M. M. Rigo, and L. E. Kavraki, “Structure-based methods for binding mode and binding affinity prediction for peptide-MHC complexes,” Current Topics in Medicinal Chemistry, vol. 19, no. 1, 2018.

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BibTeX

@article{antunes2018structure-based-methods-for-binding,
  grants = "NIH 1R21CA209941",
  abstract = "Understanding the mechanisms involved in the activation of an immune response is essential to many fields in human health, including vaccine development and personalized cancer immunotherapy. A central step in the activation of the adaptive immune response is the recognition, by T-cell lymphocytes, of peptides displayed by a special type of receptor known as Major Histocompatibility Complex (MHC). Considering the key role of MHC receptors in T-cell activation, the computational prediction of peptide binding to MHC has been an important goal for many immunological applications. Sequence-based methods have become the gold standard for peptide-MHC binding affinity prediction, but structure-based methods are expected to provide more general predictions (i.e., predictions applicable to all types of MHC receptors). In addition, structural modeling of peptide-MHC complexes has the potential to uncover yet unknown drivers of T-cell activation, thus allowing for the development of better and safer therapies. In this review, we discuss the use of computational methods for the structural modeling of peptide-MHC complexes (i.e., binding mode prediction) and for the structure-based prediction of binding affinity.",
  author = "Antunes, Dinler A. and Abella, Jayvee R. and Devaurs, Didier and Rigo, Maur\'{i}cio M. and Kavraki, Lydia E.",
  title = "Structure-based methods for binding mode and binding affinity prediction for peptide-{MHC} complexes",
  journal = "Current Topics in Medicinal Chemistry",
  year = "2018",
  volume = "19",
  number = "1",
  doi = "10.2174/1568026619666181224101744",
  keywords = "proteins and drugs, molecular docking, binding mode prediction, binding affinity prediction, peptide-MHC complexes, immunogenicity, T-cell activation",
  pmid = "30582480"
}

Abstract

Understanding the mechanisms involved in the activation of an immune response is essential to many fields in human health, including vaccine development and personalized cancer immunotherapy. A central step in the activation of the adaptive immune response is the recognition, by T-cell lymphocytes, of peptides displayed by a special type of receptor known as Major Histocompatibility Complex (MHC). Considering the key role of MHC receptors in T-cell activation, the computational prediction of peptide binding to MHC has been an important goal for many immunological applications. Sequence-based methods have become the gold standard for peptide-MHC binding affinity prediction, but structure-based methods are expected to provide more general predictions (i.e., predictions applicable to all types of MHC receptors). In addition, structural modeling of peptide-MHC complexes has the potential to uncover yet unknown drivers of T-cell activation, thus allowing for the development of better and safer therapies. In this review, we discuss the use of computational methods for the structural modeling of peptide-MHC complexes (i.e., binding mode prediction) and for the structure-based prediction of binding affinity.

D. Devaurs, D. A. Antunes, and L. E. Kavraki, “Revealing Unknown Protein Structures Using Computational Conformational Sampling Guided by Experimental Hydrogen-Exchange Data,” International Journal of Molecular Sciences, vol. 19, no. 11, p. 3406, 2018.

pdf publisher

BibTeX

@article{devaurs2018revealing-unknown-protein0structures,
  grants = "NSF AF 1423304",
  abstract = "Both experimental and computational methods are available to gather information about a protein’s conformational space and interpret changes in protein structure. However, experimentally observing and computationally modeling large proteins remain critical challenges for structural biology. Our work aims at addressing these challenges by combining computational and experimental techniques relying on each other to overcome their respective limitations. Indeed, despite its advantages, an experimental technique such as hydrogen-exchange monitoring cannot produce structural models because of its low resolution. Additionally, the computational methods that can generate such models suffer from the curse of dimensionality when applied to large proteins. Adopting a common solution to this issue, we have recently proposed a framework in which our computational method for protein conformational sampling is biased by experimental hydrogen-exchange data. In this paper, we present our latest application of this computational framework: generating an atomic-resolution structural model for an unknown protein state. For that, starting from an available protein structure, we explore the conformational space of this protein, using hydrogen-exchange data on this unknown state as a guide. We have successfully used our computational framework to generate models for three proteins of increasing size, the biggest one undergoing large-scale conformational changes.",
  author = "Devaurs, Didier and Antunes, Dinler A. and Kavraki, Lydia E.",
  title = "Revealing Unknown Protein Structures Using Computational Conformational Sampling Guided by Experimental Hydrogen-Exchange Data",
  journal = "International Journal of Molecular Sciences",
  year = "2018",
  volume = "19",
  number = "11",
  pages = "3406",
  doi = "10.3390/ijms19113406",
  keywords = "fundamentals of protein modeling"
}

Abstract

Both experimental and computational methods are available to gather information about a protein’s conformational space and interpret changes in protein structure. However, experimentally observing and computationally modeling large proteins remain critical challenges for structural biology. Our work aims at addressing these challenges by combining computational and experimental techniques relying on each other to overcome their respective limitations. Indeed, despite its advantages, an experimental technique such as hydrogen-exchange monitoring cannot produce structural models because of its low resolution. Additionally, the computational methods that can generate such models suffer from the curse of dimensionality when applied to large proteins. Adopting a common solution to this issue, we have recently proposed a framework in which our computational method for protein conformational sampling is biased by experimental hydrogen-exchange data. In this paper, we present our latest application of this computational framework: generating an atomic-resolution structural model for an unknown protein state. For that, starting from an available protein structure, we explore the conformational space of this protein, using hydrogen-exchange data on this unknown state as a guide. We have successfully used our computational framework to generate models for three proteins of increasing size, the biggest one undergoing large-scale conformational changes.

D. A. Antunes, D. Devaurs, M. Moll, G. Lizée, and L. E. Kavraki, “General prediction of peptide-MHC binding modes using incremental docking: A proof of concept,” Scientific Reports - Nature, vol. 8, p. 4327, 2018.

pdf publisher

BibTeX

@article{antunes2018-dinc-hla-proof,
  grants = "NIH 1R21CA209941",
  abstract = "The class I major histocompatibility complex (MHC) is capable of binding peptides derived from intracellular proteins and displaying them at the cell surface. The recognition of these peptide-MHC (pMHC) complexes by T-cells is the cornerstone of cellular immunity, enabling the elimination of infected or tumoral cells. T-cell-based immunotherapies against cancer, which leverage this mechanism, can greatly benefit from structural analyses of pMHC complexes. Several attempts have been made to use molecular docking for such analyses, but pMHC structure remains too challenging for even state-of-the-art docking tools. To overcome these limitations, we describe the use of an incremental meta-docking approach for structural prediction of pMHC complexes. Previous methods applied in this context used specific constraints to reduce the complexity of this prediction problem, at the expense of generality. Our strategy makes no assumption and can potentially be used to predict binding modes for any pMHC complex. Our method has been tested in a re-docking experiment, reproducing the binding modes of 25 pMHC complexes whose crystal structures are available. This study is a proof of concept that incremental docking strategies can lead to general geometry prediction of pMHC complexes, with potential applications for immunotherapy against cancer or infectious diseases.",
  doi = "10.1038/s41598-018-22173-4",
  pmcid = "PMC5847594",
  pmid = "29531253",
  author = "Antunes, Dinler A and Devaurs, Didier and Moll, Mark and Liz\'{e}e, Gregory and Kavraki, Lydia E",
  title = "General prediction of peptide-MHC binding modes using incremental docking: A proof of concept",
  journal = "Scientific Reports - Nature",
  volume = "8",
  page = "4327",
  year = "2018",
  keywords = "proteins and drugs, peptide-docking, pHLA structure, geometry prediction, DINC, cancer immunotherapy"
}

Abstract

The class I major histocompatibility complex (MHC) is capable of binding peptides derived from intracellular proteins and displaying them at the cell surface. The recognition of these peptide-MHC (pMHC) complexes by T-cells is the cornerstone of cellular immunity, enabling the elimination of infected or tumoral cells. T-cell-based immunotherapies against cancer, which leverage this mechanism, can greatly benefit from structural analyses of pMHC complexes. Several attempts have been made to use molecular docking for such analyses, but pMHC structure remains too challenging for even state-of-the-art docking tools. To overcome these limitations, we describe the use of an incremental meta-docking approach for structural prediction of pMHC complexes. Previous methods applied in this context used specific constraints to reduce the complexity of this prediction problem, at the expense of generality. Our strategy makes no assumption and can potentially be used to predict binding modes for any pMHC complex. Our method has been tested in a re-docking experiment, reproducing the binding modes of 25 pMHC complexes whose crystal structures are available. This study is a proof of concept that incremental docking strategies can lead to general geometry prediction of pMHC complexes, with potential applications for immunotherapy against cancer or infectious diseases.

2017

D. A. Antunes, M. Moll, D. Devaurs, K. R. Jackson, G. Lizée, and L. E. Kavraki, “DINC 2.0: a new protein-peptide docking webserver using an incremental approach,” Cancer Research, vol. 77, no. 21, pp. e55–57, Nov. 2017.

pdf publisher

BibTeX

@article{antunes2017-dinc2,
  grants = "NIH 1R21CA209941",
  abstract = "Molecular docking is a standard computational approach to predict binding modes of protein-ligand complexes, by exploring alternative orientations and conformations of the ligand (i.e., by exploring ligand flexibility). Docking tools are largely used for virtual screening of small drug-like molecules, but their accuracy and efficiency greatly decays for ligands with more than 10 flexible bonds. This prevents a broader use of these tools to dock larger ligands such as peptides, which are molecules of growing interest in cancer research. To overcome this limitation, our group has previously proposed a meta-docking strategy, called DINC, to predict binding modes of large ligands. By incrementally docking overlapping fragments of a ligand, DINC allowed predicting binding modes of peptide-based inhibitors of transcription factors involved in cancer. Here we describe DINC 2.0, a revamped version of the DINC webserver with enhanced capabilities and a more user-friendly interface. DINC 2.0 allows docking ligands that were previously too challenging for DINC, such as peptides with more than 25 flexible bonds. The webserver is freely accessible at \url{http://dinc.kavrakilab.org}, together with additional documentation and video tutorials. Our team will provide continuous support for this tool and is working on extending its applicability to other challenging fields, such as personalized immunotherapy against cancer.",
  keywords = "proteins and drugs, other biomedical computing",
  author = "Antunes, Dinler A and Moll, Mark and Devaurs, Didier and Jackson, KR and Liz\'{e}e, Gregory and Kavraki, Lydia E",
  title = "{DINC} 2.0: a new protein-peptide docking webserver using an incremental approach",
  journal = "Cancer Research",
  volume = "77",
  number = "21",
  pages = "e55-57",
  year = "2017",
  doi = "10.1158/0008-5472.CAN-17-0511",
  pmcid = "PMC5679007",
  pmid = "29092940",
  msid = "NIHMS898073",
  month = nov
}

Abstract

Molecular docking is a standard computational approach to predict binding modes of protein-ligand complexes, by exploring alternative orientations and conformations of the ligand (i.e., by exploring ligand flexibility). Docking tools are largely used for virtual screening of small drug-like molecules, but their accuracy and efficiency greatly decays for ligands with more than 10 flexible bonds. This prevents a broader use of these tools to dock larger ligands such as peptides, which are molecules of growing interest in cancer research. To overcome this limitation, our group has previously proposed a meta-docking strategy, called DINC, to predict binding modes of large ligands. By incrementally docking overlapping fragments of a ligand, DINC allowed predicting binding modes of peptide-based inhibitors of transcription factors involved in cancer. Here we describe DINC 2.0, a revamped version of the DINC webserver with enhanced capabilities and a more user-friendly interface. DINC 2.0 allows docking ligands that were previously too challenging for DINC, such as peptides with more than 25 flexible bonds. The webserver is freely accessible at http://dinc.kavrakilab.org, together with additional documentation and video tutorials. Our team will provide continuous support for this tool and is working on extending its applicability to other challenging fields, such as personalized immunotherapy against cancer.

D. A. Antunes, M. M. Rigo, M. V. Freitas, M. M. FA, M. Sinigaglia, G. Lizée, L. E. Kavraki, L. K. Selin, M. Cornberg, and G. F. Vieira, “Interpreting T-cell cross-reactivity through structure: implications for TCR-based cancer immunotherapy,” Front. Immunol., vol. 8, no. 1210, 2017.

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BibTeX

@article{antunes2017-frontiers-immunol,
  abstract = "Immunotherapy has become one of the most promising avenues for cancer treatment, making use of the patient's own immune system to eliminate cancer cells. Clinical trials with T-cell-based immunotherapies have shown dramatic tumor regressions, being effective in multiple cancer types and for many different patients. Unfortunately, this progress was tempered by reports of serious (even fatal) side effects. Such therapies rely on the use of cytotoxic T-cell lymphocytes, an essential part of the adaptive immune system. Cytotoxic T-cells are regularly involved in surveillance and are capable of both eliminating diseased cells and generating protective immunological memory. The specificity of a given T-cell is determined through the structural interaction between the T-cell receptor (TCR) and a peptide-loaded major histocompatibility complex (MHC); i.e., an intracellular peptide–ligand displayed at the cell surface by an MHC molecule. However, a given TCR can recognize different peptide–MHC (pMHC) complexes, which can sometimes trigger an unwanted response that is referred to as T-cell cross-reactivity. This has become a major safety issue in TCR-based immunotherapies, following reports of melanoma-specific T-cells causing cytotoxic damage to healthy tissues (e.g., heart and nervous system). T-cell cross-reactivity has been extensively studied in the context of viral immunology and tissue transplantation. Growing evidence suggests that it is largely driven by structural similarities of seemingly unrelated pMHC complexes. Here, we review recent reports about the existence of pMHC ``hot-spots" for cross-reactivity and propose the existence of a TCR interaction profile (i.e., a refinement of a more general TCR footprint in which some amino acid residues are more important than others in triggering T-cell cross-reactivity). We also make use of available structural data and pMHC models to interpret previously reported cross-reactivity patterns among virus-derived peptides. Our study provides further evidence that structural analyses of pMHC complexes can be used to assess the intrinsic likelihood of cross-reactivity among peptide-targets. Furthermore, we hypothesize that some apparent inconsistencies in reported cross-reactivities, such as a preferential directionality, might also be driven by particular structural features of the targeted pMHC complex. Finally, we explain why TCR-based immunotherapy provides a special context in which meaningful T-cell cross-reactivity predictions can be made.",
  doi = "10.3389/fimmu.2017.01210",
  pmcid = "PMC5632759",
  pmid = "29046675",
  author = "Antunes, Dinler A and Rigo, Maur\'{i}cio M and Freitas, Martiela V and FA, Mendes Marcus and Sinigaglia, Marialva and Liz\'{e}e, Gregory and Kavraki, Lydia E and Selin, Liisa K and Cornberg, Markus and Vieira, Gustavo F",
  title = "Interpreting {T}-cell cross-reactivity through structure: implications for {TCR}-based cancer immunotherapy",
  journal = "Front. Immunol.",
  volume = "8",
  number = "1210",
  year = "2017",
  keywords = "T-cell cross-reactivity, peptide–MHC complex, cross-reactivity hot-spots, TCR-interacting surface, hierarchical clustering, TCR/pMHC, cancer immunotherapy"
}

Abstract

Immunotherapy has become one of the most promising avenues for cancer treatment, making use of the patient’s own immune system to eliminate cancer cells. Clinical trials with T-cell-based immunotherapies have shown dramatic tumor regressions, being effective in multiple cancer types and for many different patients. Unfortunately, this progress was tempered by reports of serious (even fatal) side effects. Such therapies rely on the use of cytotoxic T-cell lymphocytes, an essential part of the adaptive immune system. Cytotoxic T-cells are regularly involved in surveillance and are capable of both eliminating diseased cells and generating protective immunological memory. The specificity of a given T-cell is determined through the structural interaction between the T-cell receptor (TCR) and a peptide-loaded major histocompatibility complex (MHC); i.e., an intracellular peptide–ligand displayed at the cell surface by an MHC molecule. However, a given TCR can recognize different peptide–MHC (pMHC) complexes, which can sometimes trigger an unwanted response that is referred to as T-cell cross-reactivity. This has become a major safety issue in TCR-based immunotherapies, following reports of melanoma-specific T-cells causing cytotoxic damage to healthy tissues (e.g., heart and nervous system). T-cell cross-reactivity has been extensively studied in the context of viral immunology and tissue transplantation. Growing evidence suggests that it is largely driven by structural similarities of seemingly unrelated pMHC complexes. Here, we review recent reports about the existence of pMHC “hot-spots" for cross-reactivity and propose the existence of a TCR interaction profile (i.e., a refinement of a more general TCR footprint in which some amino acid residues are more important than others in triggering T-cell cross-reactivity). We also make use of available structural data and pMHC models to interpret previously reported cross-reactivity patterns among virus-derived peptides. Our study provides further evidence that structural analyses of pMHC complexes can be used to assess the intrinsic likelihood of cross-reactivity among peptide-targets. Furthermore, we hypothesize that some apparent inconsistencies in reported cross-reactivities, such as a preferential directionality, might also be driven by particular structural features of the targeted pMHC complex. Finally, we explain why TCR-based immunotherapy provides a special context in which meaningful T-cell cross-reactivity predictions can be made.

D. Devaurs, D. A. Antunes, M. Papanastasiou, M. Moll, D. Ricklin, J. D. Lambris, and L. E. Kavraki, “Coarse-grained conformational sampling of protein structure improves the fit to experimental hydrogen-exchange data,” Frontiers in Molecular Biosciences, vol. 4, no. 13, 2017.

pdf publisher

BibTeX

@article{devaurs-17-fmb,
  grants = "NSF AF 1423304,NIH 1R21CA209941",
  abstract = "Monitoring hydrogen/deuterium exchange (HDX) undergone by a protein in solution produces experimental data that translates into valuable information about the protein’s structure. Data produced by HDX experiments is often interpreted using a crystal structure of the protein, when available. However, it has been shown that the correspondence between experimental HDX data and crystal structures is often not satisfactory. This creates difficulties when trying to perform a structural analysis of the HDX data. In this paper, we evaluate several strategies to obtain a conformation providing a good fit to the experimental HDX data, which is a premise of structural analysis. We show that performing molecular dynamics simulations can be inadequate to obtain such conformations, and we propose a novel methodology involving a coarse-grained conformational sampling approach instead. By extensively exploring the intrinsic flexibility of a protein with this approach, we produce a conformational ensemble from which we extract a single conformation providing a good fit to the experimental HDX data. We successfully demonstrate the applicability of our method to four small and medium-sized proteins.",
  keywords = "fundamentals of protein modeling",
  author = "Devaurs, Didier and Antunes, Dinler A. and Papanastasiou, Malvina and Moll, Mark and Ricklin, Daniel and Lambris, John D. and Kavraki, Lydia E.",
  title = "Coarse-grained conformational sampling of protein structure improves the fit to experimental hydrogen-exchange data",
  journal = "Frontiers in Molecular Biosciences",
  volume = "4",
  number = "13",
  doi = "10.3389/fmolb.2017.00013",
  pmcid = "PMC5344923",
  pmid = "28344973",
  year = "2017"
}

Abstract

Monitoring hydrogen/deuterium exchange (HDX) undergone by a protein in solution produces experimental data that translates into valuable information about the protein’s structure. Data produced by HDX experiments is often interpreted using a crystal structure of the protein, when available. However, it has been shown that the correspondence between experimental HDX data and crystal structures is often not satisfactory. This creates difficulties when trying to perform a structural analysis of the HDX data. In this paper, we evaluate several strategies to obtain a conformation providing a good fit to the experimental HDX data, which is a premise of structural analysis. We show that performing molecular dynamics simulations can be inadequate to obtain such conformations, and we propose a novel methodology involving a coarse-grained conformational sampling approach instead. By extensively exploring the intrinsic flexibility of a protein with this approach, we produce a conformational ensemble from which we extract a single conformation providing a good fit to the experimental HDX data. We successfully demonstrate the applicability of our method to four small and medium-sized proteins.

2016

D. Devaurs, M. Papanastasiou, D. A. Antunes, J. R. Abella, M. Moll, D. Ricklin, J. D. Lambris, and L. E. Kavraki, “Native state of complement protein C3d analysed via hydrogen exchange and conformational sampling,” International Journal of Computational Biology and Drug Design, vol. 11, no. 1/2, pp. 90–113, 2016.

pdf publisher

BibTeX

@article{devaurs-16-icibm,
  grants = "NSF AF 1423304,NIH 1R21CA209941",
  author = "Devaurs, Didier and Papanastasiou, Malvina and Antunes, Dinler A. and Abella, Jayvee R. and Moll, Mark and Ricklin, Daniel and Lambris, John D. and Kavraki, Lydia E.",
  title = "Native state of complement protein {C3d} analysed via hydrogen exchange and conformational sampling",
  journal = "International Journal of Computational Biology and Drug Design",
  keywords = "fundamentals of protein modeling",
  volume = "11",
  number = "1/2",
  pages = "90-113",
  doi = "10.1504/IJCBDD.2018.10011903",
  year = "2016",
  abstract = "Hydrogen/deuterium exchange detected by mass spectrometry (HDX-MS) provides valuable information on protein structure and dynamics. Although HDX-MS data is often interpreted using crystal structures, it was suggested that conformational ensembles produced by molecular dynamics simulations yield more accurate interpretations. In this paper, we analyse the complement protein C3d through HDX-MS data and evaluate several interpretation methodologies, using an existing prediction model to derive HDX-MS data from protein structure. We perform an HDX-MS experiment on C3d and, then, to interpret and refine the obtained data, we look for a conformation (or conformational ensemble) of C3d that allows computationally replicating this data. First, we confirm that crystal structures are not a good choice. Second, we suggest that conformational ensembles produced by molecular dynamics simulations might not always be satisfactory either. Finally, we show that coarse-grained conformational sampling of C3d produces a conformation from which the HDX-MS data can be replicated and refined."
}

Abstract

Hydrogen/deuterium exchange detected by mass spectrometry (HDX-MS) provides valuable information on protein structure and dynamics. Although HDX-MS data is often interpreted using crystal structures, it was suggested that conformational ensembles produced by molecular dynamics simulations yield more accurate interpretations. In this paper, we analyse the complement protein C3d through HDX-MS data and evaluate several interpretation methodologies, using an existing prediction model to derive HDX-MS data from protein structure. We perform an HDX-MS experiment on C3d and, then, to interpret and refine the obtained data, we look for a conformation (or conformational ensemble) of C3d that allows computationally replicating this data. First, we confirm that crystal structures are not a good choice. Second, we suggest that conformational ensembles produced by molecular dynamics simulations might not always be satisfactory either. Finally, we show that coarse-grained conformational sampling of C3d produces a conformation from which the HDX-MS data can be replicated and refined.

2015

M. M. Rigo, D. A. Antunes, M. Vaz de Freitas, M. Fabiano de Almeida Mendes, L. Meira, M. Sinigaglia, and G. F. Vieira, “DockTope: a Web-based tool for automated pMHC-I modelling,” Scientific Reports - Nature, vol. 5, p. 18413, Dec. 2015.

publisher

BibTeX

@article{Rigo2015,
  doi = "10.1038/srep18413",
  abstract = "The immune system is constantly challenged, being required to protect the organism against a wide variety of infectious pathogens and, at the same time, to avoid autoimmune disorders. One of the most important molecules involved in these events is the Major Histocompatibility Complex class I (MHC-I), responsible for binding and presenting small peptides from the intracellular environment to CD8+ T cells. The study of peptide:MHC-I (pMHC-I) molecules at a structural level is crucial to understand the molecular mechanisms underlying immunologic responses. Unfortunately, there are few pMHC-I structures in the Protein Data Bank (PDB) (especially considering the total number of complexes that could be formed combining different peptides), and pMHC-I modelling tools are scarce. Here, we present DockTope, a free and reliable web-based tool for pMHC-I modelling, based on crystal structures from the PDB. DockTope is fully automated and allows any researcher to construct a pMHC-I complex in an efficient way. We have reproduced a dataset of 135 non-redundant pMHC-I structures from the PDB (Cα RMSD below 1 Å). Modelling of pMHC-I complexes is remarkably important, contributing to the knowledge of important events such as cross-reactivity, autoimmunity, cancer therapy, transplantation and rational vaccine design.",
  author = "Rigo, M. M. and Antunes, D. A. and Vaz de Freitas, M. and Fabiano de Almeida Mendes, M. and Meira, L. and Sinigaglia, M. and Vieira, G. F.",
  title = "{D}ock{T}ope: a {W}eb-based tool for automated p{M}{H}{C}-{I} modelling",
  journal = "Scientific Reports - Nature",
  year = "2015",
  volume = "5",
  pages = "18413",
  month = dec
}

Abstract

The immune system is constantly challenged, being required to protect the organism against a wide variety of infectious pathogens and, at the same time, to avoid autoimmune disorders. One of the most important molecules involved in these events is the Major Histocompatibility Complex class I (MHC-I), responsible for binding and presenting small peptides from the intracellular environment to CD8+ T cells. The study of peptide:MHC-I (pMHC-I) molecules at a structural level is crucial to understand the molecular mechanisms underlying immunologic responses. Unfortunately, there are few pMHC-I structures in the Protein Data Bank (PDB) (especially considering the total number of complexes that could be formed combining different peptides), and pMHC-I modelling tools are scarce. Here, we present DockTope, a free and reliable web-based tool for pMHC-I modelling, based on crystal structures from the PDB. DockTope is fully automated and allows any researcher to construct a pMHC-I complex in an efficient way. We have reproduced a dataset of 135 non-redundant pMHC-I structures from the PDB (Cα RMSD below 1 Å). Modelling of pMHC-I complexes is remarkably important, contributing to the knowledge of important events such as cross-reactivity, autoimmunity, cancer therapy, transplantation and rational vaccine design.

M. F. Mendes, D. A. Antunes, M. M. Rigo, M. Sinigaglia, and G. F. Vieira, “Improved structural method for T-cell cross-reactivity prediction,” Molecular Immunology, vol. 67, no. 2 Pt B, pp. 303–310, Oct. 2015.

publisher

BibTeX

@article{Mendes2015,
  doi = "10.1016/j.molimm.2015.06.017",
  abstract = "Cytotoxic T-lymphocytes (CTLs) are the key players of adaptive cellular immunity, being able to identify and eliminate infected cells through the interaction with peptide-loaded major histocompatibility complexes class I (pMHC-I). Despite the high specificity of this interaction, a given lymphocyte is actually able to recognize more than just one pMHC-I complex, a phenomenon referred as cross-reactivity. In the present work we describe the use of pMHC-I structural features as input for multivariate statistical methods, to perform standardized structure-based predictions of cross-reactivity among viral epitopes. Our improved approach was able to successfully identify cross-reactive targets among 28 naturally occurring hepatitis C virus (HCV) variants and among eight epitopes from the four dengue virus serotypes. In both cases, our results were supported by multiscale bootstrap resampling and by data from previously published in vitro experiments. The combined use of data from charges and accessible surface area (ASA) of selected residues over the pMHC-I surface provided a powerful way of assessing the structural features involved in triggering cross-reactive responses. Moreover, the use of an R package (pvclust) for assessing the uncertainty in the hierarchical cluster analysis provided a statistical support for the interpretation of results. Taken together, these methods can be applied to vaccine design, both for the selection of candidates capable of inducing immunity against different targets, or to identify epitopes that could trigger undesired immunological responses.",
  author = "Mendes, M. F. and Antunes, D. A. and Rigo, M. M. and Sinigaglia, M. and Vieira, G. F.",
  title = "Improved structural method for {T}-cell cross-reactivity prediction",
  journal = "Molecular Immunology",
  year = "2015",
  volume = "67",
  number = "2 Pt B",
  pages = "303--310",
  month = oct
}

Abstract

Cytotoxic T-lymphocytes (CTLs) are the key players of adaptive cellular immunity, being able to identify and eliminate infected cells through the interaction with peptide-loaded major histocompatibility complexes class I (pMHC-I). Despite the high specificity of this interaction, a given lymphocyte is actually able to recognize more than just one pMHC-I complex, a phenomenon referred as cross-reactivity. In the present work we describe the use of pMHC-I structural features as input for multivariate statistical methods, to perform standardized structure-based predictions of cross-reactivity among viral epitopes. Our improved approach was able to successfully identify cross-reactive targets among 28 naturally occurring hepatitis C virus (HCV) variants and among eight epitopes from the four dengue virus serotypes. In both cases, our results were supported by multiscale bootstrap resampling and by data from previously published in vitro experiments. The combined use of data from charges and accessible surface area (ASA) of selected residues over the pMHC-I surface provided a powerful way of assessing the structural features involved in triggering cross-reactive responses. Moreover, the use of an R package (pvclust) for assessing the uncertainty in the hierarchical cluster analysis provided a statistical support for the interpretation of results. Taken together, these methods can be applied to vaccine design, both for the selection of candidates capable of inducing immunity against different targets, or to identify epitopes that could trigger undesired immunological responses.

S. Zhang, R. K. Bakshi, P. V. Suneetha, P. Fytili, D. A. Antunes, G. F. Vieira, R. Jacobs, C. S. Klade, M. P. Manns, A. R. Kraft, H. Wedemeyer, V. Schlaphoff, and M. Cornberg, “Frequency, private specificity, and cross-reactivity of preexisting hepatitis C virus (HCV)-specific CD8+ T cells in HCV-seronegative individuals: implications for vaccine responses,” Journal of Virology, vol. 89, no. 16, pp. 8304–8317, Aug. 2015.

publisher

BibTeX

@article{Zhang2015,
  doi = "10.1128/JVI.00539-15",
  abstract = "T cell responses play a critical role in controlling or clearing viruses. Therefore, strategies to prevent or treat infections include boosting T cell responses. T cells specific for various pathogens have been reported in unexposed individuals and an influence of such cells on the response toward vaccines is conceivable. However, little is known about their frequency, repertoire, and impact on vaccination. We performed a detailed characterization of CD8+ T cells specific to a hepatitis C virus (HCV) epitope (NS3-1073) in 121 HCV-seronegative individuals. We show that in vitro HCV NS3-1073-specific CD8+ T cell responses were rather abundantly detectable in one-third of HCV-seronegative individuals irrespective of risk factors for HCV exposure. Ex vivo, these NS3-1073-specific CD8+ T cells were found to be both naive and memory cells. Importantly, recognition of various peptides derived from unrelated viruses by NS3-1073-specific CD8+ T cells showed a considerable degree of T cell cross-reactivity, suggesting that they might in part originate from previous heterologous infections. Finally, we further provide evidence that preexisting NS3-1073-specific CD8+ T cells can impact the T cell response toward peptide vaccination. Healthy, vaccinated individuals who showed an in vitro response toward NS3-1073 already before vaccination displayed a more vigorous and earlier response toward the vaccine.",
  author = "Zhang, S. and Bakshi, R. K. and Suneetha, P. V. and Fytili, P. and Antunes, D. A. and Vieira, G. F. and Jacobs, R. and Klade, C. S. and Manns, M. P. and Kraft, A. R. and Wedemeyer, H. and Schlaphoff, V. and Cornberg, M.",
  title = "{F}requency, private specificity, and cross-reactivity of preexisting hepatitis {C} virus ({H}{C}{V})-specific {C}{D}8+ {T} cells in {H}{C}{V}-seronegative individuals: implications for vaccine responses",
  journal = "Journal of Virology",
  year = "2015",
  volume = "89",
  number = "16",
  pages = "8304--8317",
  month = aug
}

Abstract

T cell responses play a critical role in controlling or clearing viruses. Therefore, strategies to prevent or treat infections include boosting T cell responses. T cells specific for various pathogens have been reported in unexposed individuals and an influence of such cells on the response toward vaccines is conceivable. However, little is known about their frequency, repertoire, and impact on vaccination. We performed a detailed characterization of CD8+ T cells specific to a hepatitis C virus (HCV) epitope (NS3-1073) in 121 HCV-seronegative individuals. We show that in vitro HCV NS3-1073-specific CD8+ T cell responses were rather abundantly detectable in one-third of HCV-seronegative individuals irrespective of risk factors for HCV exposure. Ex vivo, these NS3-1073-specific CD8+ T cells were found to be both naive and memory cells. Importantly, recognition of various peptides derived from unrelated viruses by NS3-1073-specific CD8+ T cells showed a considerable degree of T cell cross-reactivity, suggesting that they might in part originate from previous heterologous infections. Finally, we further provide evidence that preexisting NS3-1073-specific CD8+ T cells can impact the T cell response toward peptide vaccination. Healthy, vaccinated individuals who showed an in vitro response toward NS3-1073 already before vaccination displayed a more vigorous and earlier response toward the vaccine.

D. A. Antunes, D. Devaurs, and L. E. Kavraki, “Understanding the challenges of protein flexibility in drug design,” Expert Opinion on Drug Discovery, vol. 10, no. 12, pp. 1301–1313, 2015.

pdf publisher

BibTeX

@article{antunes-15-eodd,
  grants = "NSF AF 1423304,NSF ABI 1262491",
  author = "Antunes, Dinler A. and Devaurs, Didier and Kavraki, Lydia E.",
  title = "Understanding the challenges of protein flexibility in drug design",
  journal = "Expert Opinion on Drug Discovery",
  year = "2015",
  volume = "10",
  number = "12",
  pages = "1301--1313",
  keywords = "proteins and drugs",
  doi = "10.1517/17460441.2015.1094458",
  pmid = "26414598",
  abstract = "Introduction: Protein–ligand interactions play key roles in various metabolic pathways, and the proteins involved in these interactions represent major targets for drug discovery. Molecular docking is widely used to predict the structure of protein–ligand complexes, and protein flexibility stands out as one of the most important and challenging issues for binding mode prediction. Various docking methods accounting for protein flexibility have been proposed, tackling problems of ever-increasing dimensionality.
  
  Areas covered: This paper presents an overview of conformational sampling methods treating target flexibility during molecular docking. Special attention is given to approaches considering full protein flexibility. Contrary to what is frequently done, this review does not rely on classical biomolecular recognition models to classify existing docking methods. Instead, it applies algorithmic considerations, focusing on the level of flexibility accounted for. This review also discusses the diversity of docking applications, from virtual screening (VS) of small drug-like compounds to geometry prediction (GP) of protein–peptide complexes.
  
  Expert opinion: Considering the diversity of docking methods presented here, deciding which one is the best at treating protein flexibility depends on the system under study and the research application. In VS experiments, ensemble docking can be used to implicitly account for large-scale conformational changes, and selective docking can additionally consider local binding-site rearrangements. In other cases, on-the-fly exploration of the whole protein–ligand complex might be needed for accurate GP of the binding mode. Among other things, future methods are expected to provide alternative binding modes, which will better reflect the dynamic nature of protein–ligand interactions."
}

Abstract

Introduction: Protein–ligand interactions play key roles in various metabolic pathways, and the proteins involved in these interactions represent major targets for drug discovery. Molecular docking is widely used to predict the structure of protein–ligand complexes, and protein flexibility stands out as one of the most important and challenging issues for binding mode prediction. Various docking methods accounting for protein flexibility have been proposed, tackling problems of ever-increasing dimensionality. Areas covered: This paper presents an overview of conformational sampling methods treating target flexibility during molecular docking. Special attention is given to approaches considering full protein flexibility. Contrary to what is frequently done, this review does not rely on classical biomolecular recognition models to classify existing docking methods. Instead, it applies algorithmic considerations, focusing on the level of flexibility accounted for. This review also discusses the diversity of docking applications, from virtual screening (VS) of small drug-like compounds to geometry prediction (GP) of protein–peptide complexes. Expert opinion: Considering the diversity of docking methods presented here, deciding which one is the best at treating protein flexibility depends on the system under study and the research application. In VS experiments, ensemble docking can be used to implicitly account for large-scale conformational changes, and selective docking can additionally consider local binding-site rearrangements. In other cases, on-the-fly exploration of the whole protein–ligand complex might be needed for accurate GP of the binding mode. Among other things, future methods are expected to provide alternative binding modes, which will better reflect the dynamic nature of protein–ligand interactions.

2014

D. F. Figueiredo, D. A. Antunes, M. M. Rigo, M. F. de Almeida Mendes, J. P. Silva, F. Q. Mayer, U. Matte, R. Giugliani, G. F. Vieira, and M. Sinigaglia, “Lessons from molecular modeling human α-L-iduronidase,” Journal of Molecular Graphics and Modelling, vol. 54, pp. 107–113, Nov. 2014.

publisher

BibTeX

@article{Figueiredo2014-idua,
  pmid = "25459762",
  doi = "10.1016/j.jmgm.2014.10.004",
  author = "Figueiredo, Danieli Forgiarini and Antunes, Dinler Amaral and Rigo, Maur\'{i}cio Menegatti and de Almeida Mendes, Marcus Fabiano and Silva, Jader Peres and Mayer, Fabiana Qoos and Matte, Ursula and Giugliani, Roberto and Vieira, Gustavo Fioravanti and Sinigaglia, Marialva",
  title = "Lessons from molecular modeling human $\alpha$-L-iduronidase",
  journal = "Journal of Molecular Graphics and Modelling",
  year = "2014",
  volume = "54",
  pages = "107--113",
  month = nov,
  abstract = "Human $\alpha$-L-iduronidase (IDUA) is a member of glycoside hydrolase family and is involved in the catabolism of glycosaminoglycans (GAGs), heparan sulfate (HS) and dermatan sulfate (DS). Mutations in this enzyme are responsible for mucopolysaccharidosis I (MPS I), an inherited lysosomal storage disorder. Despite great interest in determining and studying this enzyme structure, the lack of a high identity to templates and other technical issues have challenged both bioinformaticians and crystallographers, until the recent publication of an IDUA crystal structure (PDB: 4JXP). In the present work, four alternative IDUA models, generated and evaluated prior to crystallographic determination, were compared to the 4JXP structure. A combined analysis using several viability assessment tools and molecular dynamics simulations highlights the strengths and limitations of different comparative modeling protocols, all of which are based on the same low identity template (only 22\%). Incorrect alignment between the target and template was confirmed to be a major bottleneck in homology modeling, regardless of the modeling software used. Moreover, secondary structure analysis during a 50ns simulation seems to be useful for indicating alignment errors and structural instabilities. The best model was achieved through the combined use of Phyre 2 and Modeller, suggesting the use of this protocol for the modeling of other proteins that still lack high identity templates."
}

Abstract

Human α-L-iduronidase (IDUA) is a member of glycoside hydrolase family and is involved in the catabolism of glycosaminoglycans (GAGs), heparan sulfate (HS) and dermatan sulfate (DS). Mutations in this enzyme are responsible for mucopolysaccharidosis I (MPS I), an inherited lysosomal storage disorder. Despite great interest in determining and studying this enzyme structure, the lack of a high identity to templates and other technical issues have challenged both bioinformaticians and crystallographers, until the recent publication of an IDUA crystal structure (PDB: 4JXP). In the present work, four alternative IDUA models, generated and evaluated prior to crystallographic determination, were compared to the 4JXP structure. A combined analysis using several viability assessment tools and molecular dynamics simulations highlights the strengths and limitations of different comparative modeling protocols, all of which are based on the same low identity template (only 22%). Incorrect alignment between the target and template was confirmed to be a major bottleneck in homology modeling, regardless of the modeling software used. Moreover, secondary structure analysis during a 50ns simulation seems to be useful for indicating alignment errors and structural instabilities. The best model was achieved through the combined use of Phyre 2 and Modeller, suggesting the use of this protocol for the modeling of other proteins that still lack high identity templates.

D. A. Antunes, “Peptide-MHC structural similarity as a probability for cross-reactive T cell responses,” PhD thesis, Federal University of Rio Grande do Sul, Graduate Program in Genetics and Molecular Biology (PPGBM), 2014. Language: Portuguese

pdf publisher

BibTeX

@phdthesis{Antunes-DS,
  author = "Antunes, D. A.",
  title = "Peptide-MHC structural similarity as a probability for cross-reactive T cell responses",
  school = "Federal University of Rio Grande do Sul, Graduate Program in Genetics and Molecular Biology (PPGBM)",
  year = "2014",
  month = aug,
  note = "Language: Portuguese",
  url = "https://www.lume.ufrgs.br/handle/10183/104800",
  abstract = "Host-pathogen coevolution can be implicated as one of the main features driving the great diversity of genes involved with immunological response. The so-called “MHC region” (Major Histocompatibility Complex), located at the short arm of human chromosome 6, is the most polymorphic and dense region of our genome. The three most polymorphic genes in this locus encode the heavy chain of a complex referred as MHC class I, which is responsible for presentation (at cell surface) of peptides derived from the digestion of cytosolic proteins. This mechanism plays a key role in antiviral immune response, allowing infected cells to be identified and eliminated by Cytotoxic T Lymphocytes. Although structurally similar, each MHC molecule presents higher affinity for peptides with certain biochemical properties. Therefore, the greater the variability of MHCs in a given population, the smaller the risk that all individuals are unable to present at least some targets derived from a given virus. On the other hand, cellular immune response and memory generation against the target presented by the MHC, depends on specific recognition of this peptide:MHC (pMHC) complex by a given T cell population. In this work, we use bioinformatics tools to perform structural analysis of pMHC complexes, identifying features involved in triggering cellular immune responses. Our in silico results, corroborated by in vitro and ex vivo experiments suggest that structural similarity among pMHC complexes (topography and electrostatic potential) plays a central role in cross-reactivity of cytotoxic T cells, with implications over heterologous immunity, immunopathology and vaccine development."
}

Abstract

Host-pathogen coevolution can be implicated as one of the main features driving the great diversity of genes involved with immunological response. The so-called “MHC region” (Major Histocompatibility Complex), located at the short arm of human chromosome 6, is the most polymorphic and dense region of our genome. The three most polymorphic genes in this locus encode the heavy chain of a complex referred as MHC class I, which is responsible for presentation (at cell surface) of peptides derived from the digestion of cytosolic proteins. This mechanism plays a key role in antiviral immune response, allowing infected cells to be identified and eliminated by Cytotoxic T Lymphocytes. Although structurally similar, each MHC molecule presents higher affinity for peptides with certain biochemical properties. Therefore, the greater the variability of MHCs in a given population, the smaller the risk that all individuals are unable to present at least some targets derived from a given virus. On the other hand, cellular immune response and memory generation against the target presented by the MHC, depends on specific recognition of this peptide:MHC (pMHC) complex by a given T cell population. In this work, we use bioinformatics tools to perform structural analysis of pMHC complexes, identifying features involved in triggering cellular immune responses. Our in silico results, corroborated by in vitro and ex vivo experiments suggest that structural similarity among pMHC complexes (topography and electrostatic potential) plays a central role in cross-reactivity of cytotoxic T cells, with implications over heterologous immunity, immunopathology and vaccine development.

D. A. Antunes, M. M. Rigo, M. Sinigaglia, R. M. de Medeiros, D. M. Junqueira, S. E. Almeida, and G. F. Vieira, “New insights into the in silico prediction of HIV protease resistance to nelfinavir,” PLoS ONE, vol. 9, no. 1, p. e87520, 2014.

publisher

BibTeX

@article{Antunes2014-hiv,
  pmid = "24498124",
  doi = "10.1371/journal.pone.0087520",
  author = "Antunes, D. A. and Rigo, M. M. and Sinigaglia, M. and de Medeiros, R. M. and Junqueira, D. M. and Almeida, S. E. and Vieira, G. F.",
  title = "{N}ew insights into the in silico prediction of {H}{I}{V} protease resistance to nelfinavir",
  journal = "PLoS ONE",
  year = "2014",
  volume = "9",
  number = "1",
  pages = "e87520",
  abstract = "The Human Immunodeficiency Virus type 1 protease enzyme (HIV-1 PR) is one of the most important targets of antiretroviral therapy used in the treatment of AIDS patients. The success of protease-inhibitors (PIs), however, is often limited by the emergence of protease mutations that can confer resistance to a specific drug, or even to multiple PIs. In the present study, we used bioinformatics tools to evaluate the impact of the unusual mutations D30V and V32E over the dynamics of the PR-Nelfinavir complex, considering that codons involved in these mutations were previously related to major drug resistance to Nelfinavir. Both studied mutations presented structural features that indicate resistance to Nelfinavir, each one with a different impact over the interaction with the drug. The D30V mutation triggered a subtle change in the PR structure, which was also observed for the well-known Nelfinavir resistance mutation D30N, while the V32E exchange presented a much more dramatic impact over the PR flap dynamics. Moreover, our in silico approach was also able to describe different binding modes of the drug when bound to different proteases, identifying specific features of HIV-1 subtype B and subtype C proteases."
}

Abstract

The Human Immunodeficiency Virus type 1 protease enzyme (HIV-1 PR) is one of the most important targets of antiretroviral therapy used in the treatment of AIDS patients. The success of protease-inhibitors (PIs), however, is often limited by the emergence of protease mutations that can confer resistance to a specific drug, or even to multiple PIs. In the present study, we used bioinformatics tools to evaluate the impact of the unusual mutations D30V and V32E over the dynamics of the PR-Nelfinavir complex, considering that codons involved in these mutations were previously related to major drug resistance to Nelfinavir. Both studied mutations presented structural features that indicate resistance to Nelfinavir, each one with a different impact over the interaction with the drug. The D30V mutation triggered a subtle change in the PR structure, which was also observed for the well-known Nelfinavir resistance mutation D30N, while the V32E exchange presented a much more dramatic impact over the PR flap dynamics. Moreover, our in silico approach was also able to describe different binding modes of the drug when bound to different proteases, identifying specific features of HIV-1 subtype B and subtype C proteases.

2013

M. Sinigaglia, D. A. Antunes, M. M. Rigo, J. A. Chies, and G. F. Vieira, “CrossTope: a curate repository of 3D structures of immunogenic peptide: MHC complexes,” Database (Oxford), vol. 2013, p. bat002, 2013.

pdf publisher

BibTeX

@article{sinigaglia2013-crosstope,
  doi = "10.1093/database/bat002",
  abstract = "The CrossTope is a highly curate repository of three-dimensional structures of peptide:major histocompatibility complex (MHC) class I complexes (pMHC-I). The complexes hosted by this databank were obtained in protein databases and by large-scale in silico construction of pMHC-I structures, using a new approach developed by our group. At this moment, the database contains 182 'non-redundant' pMHC-I complexes from two human and two murine alleles. A web server provides interface for database query. The user can download (i) structure coordinate files and (ii) topological and charges distribution maps images from the T-cell receptor-interacting surface of pMHC-I complexes. The retrieved structures and maps can be used to cluster similar epitopes in cross-reactivity approaches, to analyse viral escape mutations in a structural level or even to improve the immunogenicity of tumour antigens. Database URL: http://www.crosstope.com.br.",
  author = "Sinigaglia, M. and Antunes, D. A. and Rigo, M. M. and Chies, J. A. and Vieira, G. F.",
  title = "{C}ross{T}ope: a curate repository of 3{D} structures of immunogenic peptide: {M}{H}{C} complexes",
  journal = "Database (Oxford)",
  year = "2013",
  volume = "2013",
  pages = "bat002"
}

Abstract

The CrossTope is a highly curate repository of three-dimensional structures of peptide:major histocompatibility complex (MHC) class I complexes (pMHC-I). The complexes hosted by this databank were obtained in protein databases and by large-scale in silico construction of pMHC-I structures, using a new approach developed by our group. At this moment, the database contains 182 ’non-redundant’ pMHC-I complexes from two human and two murine alleles. A web server provides interface for database query. The user can download (i) structure coordinate files and (ii) topological and charges distribution maps images from the T-cell receptor-interacting surface of pMHC-I complexes. The retrieved structures and maps can be used to cluster similar epitopes in cross-reactivity approaches, to analyse viral escape mutations in a structural level or even to improve the immunogenicity of tumour antigens. Database URL: http://www.crosstope.com.br.

2012

M. M. Rigo, D. A. Antunes, S. P. Cibulski, M. Sinigaglia, J. A. Chies, and G. F. Vieira, “Immunogenic epitopes of Hantaviruses’ N protein are restricted to conserved regions,” Frontiers in Bioscience (Landmark Ed), vol. 17, pp. 1582–1588, Jan. 2012.

publisher

BibTeX

@article{Rigo2012-hanta,
  pmid = "22201821",
  doi = "10.2741/4004",
  author = "Rigo, M. M. and Antunes, D. A. and Cibulski, S. P. and Sinigaglia, M. and Chies, J. A. and Vieira, G. F.",
  title = "{I}mmunogenic epitopes of {H}antaviruses' {N} protein are restricted to conserved regions",
  journal = "Frontiers in Bioscience (Landmark Ed)",
  year = "2012",
  volume = "17",
  pages = "1582--1588",
  month = jan,
  abstract = "The Bunyaviridae virus family is composed by five genera, of which the Hantavirus genus is one of the most important representatives. Occasionally, these viruses can be transmitted to humans, giving rise to severe diseases that present high mortality rates. We analyzed the amino acid sequences of the nucleocapsid (N) proteins of 34 different hantaviruses to investigate the potential mechanisms involved in immunogenicity against hantaviruses. Immunogenic epitopes described in the literature through experimental analyses for Sin Nombre (SNV), Puumala (PUUV), and Hantaan (HTNV) viruses' species were retrieved. We identified and characterized the regions believed to be responsible for the induction of immune response in hosts. We found that N protein epitopes described in the literature for PUUV, SNV and HTNV viruses are all located in highly conserved regions of the protein. The high conservation of these regions suggests that a cross-reactive immune response among different hantaviruses can be induced."
}

Abstract

The Bunyaviridae virus family is composed by five genera, of which the Hantavirus genus is one of the most important representatives. Occasionally, these viruses can be transmitted to humans, giving rise to severe diseases that present high mortality rates. We analyzed the amino acid sequences of the nucleocapsid (N) proteins of 34 different hantaviruses to investigate the potential mechanisms involved in immunogenicity against hantaviruses. Immunogenic epitopes described in the literature through experimental analyses for Sin Nombre (SNV), Puumala (PUUV), and Hantaan (HTNV) viruses’ species were retrieved. We identified and characterized the regions believed to be responsible for the induction of immune response in hosts. We found that N protein epitopes described in the literature for PUUV, SNV and HTNV viruses are all located in highly conserved regions of the protein. The high conservation of these regions suggests that a cross-reactive immune response among different hantaviruses can be induced.

M. M. Rigo, D. A. Antunes, M. Sinigaglia, J. A. B. Chies, and G. F. Vieira, “MHC, Viral Infection and Immunoinformatics,” in Major Histocompatibility Complex: Biology, Functions and Roles in Disease, Nova Science Publishers, 2012, pp. 69–85.

publisher

BibTeX

@inbook{Rigo-NP12,
  author = "Rigo, M. M. and Antunes, D. A. and Sinigaglia, M. and Chies, J. A. B. and Vieira, GF.",
  title = "MHC, Viral Infection and Immunoinformatics",
  booktitle = "Major Histocompatibility Complex: Biology, Functions and Roles in Disease",
  series = "Immunology and Immune System Disorders",
  pages = "69--85",
  publisher = "Nova Science Publishers",
  year = "2012",
  isbn = "978-1-61942-999-4",
  url = "https://novapublishers.com/shop/major-histocompatibility-complex-biology-functions-and-roles-in-disease/",
  abstract = "The immunologic surveillance is performed by several molecules (e.g. antibodies and complement system) and cells (e.g. T lymphocytes, Natural Killer cells) which are triggered depending on the type of infection. In the specific context of the viral infection, a special set of molecules, named Major Complex of Histocompatibility class I (MHC-I), which is represented by the Human Leukocyte Antigen (HLA) genes in humans, perform an essential role. These molecules are responsible for the presentation of small peptides from viruses, parasites, bacteria or even from human proteins to the T Cell Lymphocytes, which will or will not trigger an immune response, through the T Cell Receptor (TCR) interaction. There are two classes of MHC: MHC-I and MHC-II. The MHC-I is responsible for the presentation of small peptides (8-12 amino acids long) generated by endogenous processing, while the MHC-II presents longer peptides (up to 30 amino acids) from exogenous environment. Regarding MHC-I presentation it is known that topologies and electrostatics patterns of the peptide:MHC (pMHC) interacting region are important for TCR recognition. Also, the affinity and stability between the peptide (epitope) and the MHC (receptor) play a crucial role, especially on what concerns electrostatics and non-hydrophobic interactions between the MHC and anchor residues of the peptide. All these features stand for the peptide immunogenicity. The knowledgment of issues regarding peptide affinity by MHC cleft and the stability of resulting complex is pivotal for vaccine development field. Nowadays, there are several immunoinformatics tools available to assist the resolution of this task. For instance, peptide binding affinity could be predicted through several computational methods (i.e. using tools that consider amino acid sequence composition and preferential anchor residues occurrence). There are also bioinformatics tools that are not specific for immunological issues, but can be used for this purpose, such as molecular docking and molecular dynamics. The latter can be used to assess pMHC complex stability, one of the main factors involved in peptide presentation. In the present chapter we intend to review basic molecular aspects regarding the MHC-I molecule and its interaction with different epitopes. Also, the use of immunoinformatics aiming to understand the different levels of MHC-I interaction will be discussed."
}

Abstract

The immunologic surveillance is performed by several molecules (e.g. antibodies and complement system) and cells (e.g. T lymphocytes, Natural Killer cells) which are triggered depending on the type of infection. In the specific context of the viral infection, a special set of molecules, named Major Complex of Histocompatibility class I (MHC-I), which is represented by the Human Leukocyte Antigen (HLA) genes in humans, perform an essential role. These molecules are responsible for the presentation of small peptides from viruses, parasites, bacteria or even from human proteins to the T Cell Lymphocytes, which will or will not trigger an immune response, through the T Cell Receptor (TCR) interaction. There are two classes of MHC: MHC-I and MHC-II. The MHC-I is responsible for the presentation of small peptides (8-12 amino acids long) generated by endogenous processing, while the MHC-II presents longer peptides (up to 30 amino acids) from exogenous environment. Regarding MHC-I presentation it is known that topologies and electrostatics patterns of the peptide:MHC (pMHC) interacting region are important for TCR recognition. Also, the affinity and stability between the peptide (epitope) and the MHC (receptor) play a crucial role, especially on what concerns electrostatics and non-hydrophobic interactions between the MHC and anchor residues of the peptide. All these features stand for the peptide immunogenicity. The knowledgment of issues regarding peptide affinity by MHC cleft and the stability of resulting complex is pivotal for vaccine development field. Nowadays, there are several immunoinformatics tools available to assist the resolution of this task. For instance, peptide binding affinity could be predicted through several computational methods (i.e. using tools that consider amino acid sequence composition and preferential anchor residues occurrence). There are also bioinformatics tools that are not specific for immunological issues, but can be used for this purpose, such as molecular docking and molecular dynamics. The latter can be used to assess pMHC complex stability, one of the main factors involved in peptide presentation. In the present chapter we intend to review basic molecular aspects regarding the MHC-I molecule and its interaction with different epitopes. Also, the use of immunoinformatics aiming to understand the different levels of MHC-I interaction will be discussed.

D. A. Antunes, M. M. Rigo, M. Sinigaglia, and G. F. Vieira, “Structural Immunoinformatics and Vaccine Development,” in Bioinformatics Research: New Developments, Nova Science Publishers, 2012, pp. 1–33.

publisher

BibTeX

@inbook{Antunes-NP12,
  author = "Antunes, D. A. and Rigo, M. M. and Sinigaglia, M. and Vieira, G. F.",
  title = "Structural Immunoinformatics and Vaccine Development",
  booktitle = "Bioinformatics Research: New Developments",
  series = " Biotechnology in Agriculture, Industry and Medicine",
  pages = "1--33",
  publisher = "Nova Science Publishers",
  year = "2012",
  isbn = "978-1-61942-363-3",
  url = "http://www.novapublishers.org/catalog/product_info.php?products_id=27160",
  abstract = "Bioinformatics is a new field of research, with roots in computer science, physics, statistics and molecular biology. Its growth was fueled by the genome sequencing initiatives and the great amount of data produced by them, having quickly spread to all other fields of biological research. This innovative way of making science proved to be especially useful to immunology, allowing the development of a range of tools to predict critical steps in the immune response. The Immunological bioinformatics, or just Immunoinformatics, has emerged as a promising field, with possible applications in cancer research and vaccine development. Most of these immunoinformatics tools and databases are based on sequence analysis, which brings advantages, but also some limitations. Bioinformatics, however, has already developed ways to deal with tridimensional structures, allowing studying protein-protein interaction at an atomic level and extract, from each amino acid in these proteins, much more information than that provided by the linear sequence. In this chapter, we will discuss new uses of structural bioinformatics to study immunological problems, focusing on the Major Histocompatibility Complex (MHC). The MHC molecule plays a key role in the cellular immune response, presenting peptides derived from intracellular proteins to Cytotoxic T Lymphocytes (CTLs). Through the interaction between these peptide:MHC complexes (pMHCs) and the T Cell Receptors (TCRs), these CTLs are capable of identifying non-self peptides and eliminate infected or transformed cells. Structural bioinformatics tools, such as Molecular Docking and Molecular Dynamics, are being used to build the tridimensional structure of unknown pMHC complexes – not yet determined by classical experimental methods – and to assess molecular aspects of these structures. For instance, the electrostatic potential of the TCR-interacting surface of these pMHCs, as well as Accessible Surface Area (ASA) of the peptide inside the MHC cleft, can be related to the immunogenicity of a given virus-derived epitope. Moreover, these features can be included in one global analysis that can cover most of many details underlying TCR/pMHC interaction, affording to predict the impact of viral escape mutations and selection of epitopes with potential to induce cross-reactive immune responses."
}

Abstract

Bioinformatics is a new field of research, with roots in computer science, physics, statistics and molecular biology. Its growth was fueled by the genome sequencing initiatives and the great amount of data produced by them, having quickly spread to all other fields of biological research. This innovative way of making science proved to be especially useful to immunology, allowing the development of a range of tools to predict critical steps in the immune response. The Immunological bioinformatics, or just Immunoinformatics, has emerged as a promising field, with possible applications in cancer research and vaccine development. Most of these immunoinformatics tools and databases are based on sequence analysis, which brings advantages, but also some limitations. Bioinformatics, however, has already developed ways to deal with tridimensional structures, allowing studying protein-protein interaction at an atomic level and extract, from each amino acid in these proteins, much more information than that provided by the linear sequence. In this chapter, we will discuss new uses of structural bioinformatics to study immunological problems, focusing on the Major Histocompatibility Complex (MHC). The MHC molecule plays a key role in the cellular immune response, presenting peptides derived from intracellular proteins to Cytotoxic T Lymphocytes (CTLs). Through the interaction between these peptide:MHC complexes (pMHCs) and the T Cell Receptors (TCRs), these CTLs are capable of identifying non-self peptides and eliminate infected or transformed cells. Structural bioinformatics tools, such as Molecular Docking and Molecular Dynamics, are being used to build the tridimensional structure of unknown pMHC complexes – not yet determined by classical experimental methods – and to assess molecular aspects of these structures. For instance, the electrostatic potential of the TCR-interacting surface of these pMHCs, as well as Accessible Surface Area (ASA) of the peptide inside the MHC cleft, can be related to the immunogenicity of a given virus-derived epitope. Moreover, these features can be included in one global analysis that can cover most of many details underlying TCR/pMHC interaction, affording to predict the impact of viral escape mutations and selection of epitopes with potential to induce cross-reactive immune responses.

D. A. Antunes, D. F. Figueiredo, M. M. Rigo, J. P. Silva, J. A. Chies, M. Sinigaglia, and G. F. Vieira, “Hierarchical Clustering of pMHC Complexes Based on the Electrostatic Potential of the TCR-Interacting Surface,” in Second International Society for Computational Biology Latin American regional meeting (ISCB-Latin America), 2012. Santiago, Chile (Best poster award)

BibTeX

@inproceedings{Antunes2012-ISCB,
  author = "Antunes, D. A. and Figueiredo, D. F. and Rigo, M. M. and Silva, J. P. and Chies, J. A. and Sinigaglia, M. and Vieira, G. F.",
  title = "Hierarchical Clustering of pMHC Complexes Based on the Electrostatic Potential of the TCR-Interacting Surface",
  booktitle = "Second International Society for Computational Biology Latin American regional meeting (ISCB-Latin America)",
  year = "2012",
  note = "Santiago, Chile (Best poster award)"
}

M. M. Rigo, D. A. Antunes, R. Minozzo, J. P. Silva, D. F. Figueiredo, J. A. Chies, M. Sinigaglia, and G. F. Vieira, “Analysis of Interaction Residues Between HLA-A*02:01 Cleft and Epitopes,” in Second International Society for Computational Biology Latin American regional meeting (ISCB-Latin America), 2012. Santiago, Chile (Short-Article)

BibTeX

@inproceedings{Rigo2012-ISCB,
  author = "Rigo, M. M. and Antunes, D. A. and Minozzo, R. and Silva, J. P. and Figueiredo, D. F. and Chies, J. A. and Sinigaglia, M. and Vieira, G. F.",
  title = "Analysis of Interaction Residues Between HLA-A*02:01 Cleft and Epitopes",
  booktitle = "Second International Society for Computational Biology Latin American regional meeting (ISCB-Latin America)",
  year = "2012",
  note = "Santiago, Chile (Short-Article)"
}

2011

D. A. Antunes, M. M. Rigo, J. P. Silva, S. P. Cibulski, M. Sinigaglia, J. A. Chies, and G. F. Vieira, “Structural in silico analysis of cross-genotype-reactivity among naturally occurring HCV NS3-1073-variants in the context of HLA-A*02:01 allele,” Molecular Immunology, vol. 48, no. 12-13, pp. 1461–1467, Jul. 2011.

publisher

BibTeX

@article{Antunes2011,
  doi = "10.1016/j.molimm.2011.03.019",
  abstract = "Cellular immune response plays a central role in outcome of Hepatitis C Virus (HCV) infection. While specific T-cell responses are related to viral clearance, impaired responses can lead to chronic infection, turning HCV variability into a major obstacle for vaccine development. In a recent work, Fytili et al. (2008) studied the cross reactive potential of HCV specific CD8+ T-cells and observed a large variation in immunogenicity among 28 naturally occurring NS3(1073) variants. In this work, we intend to evaluate this immunogenic variation at molecular level, through bioinformatics approaches. The D1-EM-D2 strategy was used to build in silico MHC:peptide complexes (pMHC) of these HCV-derived peptides in the context of HLA-A*02:01 allele. The TCR-interacting surface of these complexes were evaluated using the GRASP2 program. Structural analysis indicated a sharing of topological and electrostatic features among complexes that induced strong response in vitro. Besides, complexes that induced low response presented an important positively charged spot in the center of TCR-interacting area. This spot was seen even in complexes with conservative amino acid changes and is consistent with the impairment of recognition by wild-type-specific T-cells, observed in vitro. Furthermore, the most remarkable difference in electrostatic potential was seen precisely in the only complex unable to induce in vitro stimulation. All these observations were confirmed by Principal Component Analysis (PCA) and this approach was also applied to a set of 45 non-related immunogenic viral epitopes, indicating possible new targets for cross-reactivity studies. Our results suggest structural in silico analysis of pMHC complexes as a reliable tool for vaccine development, affording to predict the impact of viral escape mutations and selection of epitopes with potential to induce cross-reactive immune responses.",
  author = "Antunes, D. A. and Rigo, M. M. and Silva, J. P. and Cibulski, S. P. and Sinigaglia, M. and Chies, J. A. and Vieira, G. F.",
  title = "{S}tructural in silico analysis of cross-genotype-reactivity among naturally occurring {H}{C}{V} {N}{S}3-1073-variants in the context of {H}{L}{A}-{A}*02:01 allele",
  journal = "Molecular Immunology",
  year = "2011",
  volume = "48",
  number = "12-13",
  pages = "1461--1467",
  month = jul
}

Abstract

Cellular immune response plays a central role in outcome of Hepatitis C Virus (HCV) infection. While specific T-cell responses are related to viral clearance, impaired responses can lead to chronic infection, turning HCV variability into a major obstacle for vaccine development. In a recent work, Fytili et al. (2008) studied the cross reactive potential of HCV specific CD8+ T-cells and observed a large variation in immunogenicity among 28 naturally occurring NS3(1073) variants. In this work, we intend to evaluate this immunogenic variation at molecular level, through bioinformatics approaches. The D1-EM-D2 strategy was used to build in silico MHC:peptide complexes (pMHC) of these HCV-derived peptides in the context of HLA-A*02:01 allele. The TCR-interacting surface of these complexes were evaluated using the GRASP2 program. Structural analysis indicated a sharing of topological and electrostatic features among complexes that induced strong response in vitro. Besides, complexes that induced low response presented an important positively charged spot in the center of TCR-interacting area. This spot was seen even in complexes with conservative amino acid changes and is consistent with the impairment of recognition by wild-type-specific T-cells, observed in vitro. Furthermore, the most remarkable difference in electrostatic potential was seen precisely in the only complex unable to induce in vitro stimulation. All these observations were confirmed by Principal Component Analysis (PCA) and this approach was also applied to a set of 45 non-related immunogenic viral epitopes, indicating possible new targets for cross-reactivity studies. Our results suggest structural in silico analysis of pMHC complexes as a reliable tool for vaccine development, affording to predict the impact of viral escape mutations and selection of epitopes with potential to induce cross-reactive immune responses.

D. A. Antunes, “In silico study of the molecular basis for cross-reactivity between viral epitopes restricted to HLA-A*02:01,” Master's thesis, Federal University of Rio Grande do Sul, Graduate Program in Genetics and Molecular Biology (PPGBM), 2011. Language: Portuguese

pdf publisher

BibTeX

@mastersthesis{Antunes-MS,
  author = "Antunes, D. A.",
  title = "In silico study of the molecular basis for cross-reactivity between viral epitopes restricted to {HLA-A}*02:01",
  school = "Federal University of Rio Grande do Sul, Graduate Program in Genetics and Molecular Biology (PPGBM)",
  year = "2011",
  month = mar,
  note = "Language: Portuguese",
  url = "https://www.lume.ufrgs.br/handle/10183/54417",
  abstract = "Recognition of the Major Histocompatibility Complex (MHC) by Cytotoxic T Lymphocytes (CTLs) is the final step of an important intracellular pathway, responsible for presenting endogenous peptides. This route allows the Immune System to perform a persistent surveillance of the cytoplasmic content of all nucleated cells, being a pivotal mechanism in antiviral and antitumoral defense. The understanding of molecular issues underlying the stimulation of a given T cell population by a specific peptide:MHC (pMHC) complex is essential for vaccine development, having special application to study the immunity against Hepatits C Virus (HCV). In a recent work, Paraskevi Fytili and colleagues evaluated the immunogenicity of an HCV-NS31073 variants subset against a CTL population previously stimulated with the wild-type epitope. Both natural and synthetic variants were used, and a large variation of IFN-gamma production by wildtype- specific T cells was observed. In this work, we intend to evaluate this variability at molecular level, through bioinformatics approaches. The prior identification of allele-specific patterns, presented by epitopes in the MHC cleft, allowed the development of a strategy for in silico construction of pMHC complexes, combining Molecular Docking and Energy Minimization (D1- EM-D2). This innovative approach was used to build 10 complexes presenting synthetic peptides and 28 complexes presenting naturally occurring variants, all in the context of human MHC allele HLA-A*02:01. The molecular surface of these complexes was further evaluated regarding its topology, electrostatic potential and Accessible Surface Area (ASA). Resulting data was used to group the variants according to its similarity with the wild-type-presenting complex, being these groups confronted with in vitro data, previously published by Fytili et al. This analysis, corroborated by multivariate statistical methods, has highlighted the sharing of structural aspects among complexes that stimulate response in vitro, as well as possible molecular issues responsible for abrogation of cellular immune response against certain HCV variants. This work suggests structural in silico analysis of pMHC complexes as a reliable tool for vaccine development, affording to predict the impact of viral escape mutations and selection of epitopes with potential to induce cross-reactive immune responses."
}

Abstract

Recognition of the Major Histocompatibility Complex (MHC) by Cytotoxic T Lymphocytes (CTLs) is the final step of an important intracellular pathway, responsible for presenting endogenous peptides. This route allows the Immune System to perform a persistent surveillance of the cytoplasmic content of all nucleated cells, being a pivotal mechanism in antiviral and antitumoral defense. The understanding of molecular issues underlying the stimulation of a given T cell population by a specific peptide:MHC (pMHC) complex is essential for vaccine development, having special application to study the immunity against Hepatits C Virus (HCV). In a recent work, Paraskevi Fytili and colleagues evaluated the immunogenicity of an HCV-NS31073 variants subset against a CTL population previously stimulated with the wild-type epitope. Both natural and synthetic variants were used, and a large variation of IFN-gamma production by wildtype- specific T cells was observed. In this work, we intend to evaluate this variability at molecular level, through bioinformatics approaches. The prior identification of allele-specific patterns, presented by epitopes in the MHC cleft, allowed the development of a strategy for in silico construction of pMHC complexes, combining Molecular Docking and Energy Minimization (D1- EM-D2). This innovative approach was used to build 10 complexes presenting synthetic peptides and 28 complexes presenting naturally occurring variants, all in the context of human MHC allele HLA-A*02:01. The molecular surface of these complexes was further evaluated regarding its topology, electrostatic potential and Accessible Surface Area (ASA). Resulting data was used to group the variants according to its similarity with the wild-type-presenting complex, being these groups confronted with in vitro data, previously published by Fytili et al. This analysis, corroborated by multivariate statistical methods, has highlighted the sharing of structural aspects among complexes that stimulate response in vitro, as well as possible molecular issues responsible for abrogation of cellular immune response against certain HCV variants. This work suggests structural in silico analysis of pMHC complexes as a reliable tool for vaccine development, affording to predict the impact of viral escape mutations and selection of epitopes with potential to induce cross-reactive immune responses.

F. S. Campos, D. Dezen, D. A. Antunes, H. F. Santos, T. S. Arantes, A. Cenci, F. Gomes, F. E. Lima, W. M. Brito, H. C. Filho, H. B. Batista, F. R. Spilki, A. C. Franco, F. A. Rijsewijk, and P. M. Roehe, “Efficacy of an inactivated, recombinant bovine herpesvirus type 5 (BoHV-5) vaccine,” Veterinary Microbiology, vol. 148, no. 1, pp. 18–26, Feb. 2011.

publisher

BibTeX

@article{Campos2011-bhv5,
  pmid = "20828945",
  doi = "10.1016/j.vetmic.2010.08.004",
  author = "Campos, F. S. and Dezen, D. and Antunes, D. A. and Santos, H. F. and Arantes, T. S. and Cenci, A. and Gomes, F. and Lima, F. E. and Brito, W. M. and Filho, H. C. and Batista, H. B. and Spilki, F. R. and Franco, A. C. and Rijsewijk, F. A. and Roehe, P. M.",
  title = "{E}fficacy of an inactivated, recombinant bovine herpesvirus type 5 ({B}o{H}{V}-5) vaccine",
  journal = "Veterinary Microbiology",
  year = "2011",
  volume = "148",
  number = "1",
  pages = "18--26",
  month = feb,
  abstract = "Bovine herpesvirus type 5 (BoHV-5) is the causative agent of bovine herpetic encephalitis. In countries where BoHV-5 is prevalent, attempts to vaccinate cattle to prevent clinical signs from BoHV-5-induced disease have relied essentially on vaccination with BoHV-1 vaccines. However, such practice has been shown not to confer full protection to BoHV-5 challenge. In the present study, an inactivated, oil adjuvanted vaccine prepared with a recombinant BoHV-5 from which the genes coding for glycoprotein I (gI), glycoprotein E (gE) and membrane protein US9 were deleted (BoHV-5 gI/gE/US9−), was evaluated in cattle in a vaccination/challenge experiment. The vaccine was prepared from a virus suspension containing a pre-inactivation antigenic mass equivalent to 10{7.69} TCID50/dose. Three mL of the inactivated vaccine were administered subcutaneously to eight calves serologically negative for BoHV-5 (vaccinated group). Four other calves were mock-vaccinated with an equivalent preparation without viral antigens (control group). Both groups were boostered 28 days later. Neither clinical signs of disease nor adverse effects were observed during or after vaccination. A specific serological response, revealed by the development of neutralizing antibodies, was detected in all vaccinated animals after the first dose of vaccine, whereas control animals remained seronegative. Calves were subsequently challenged on day 77 post-vaccination (pv) with 109.25 TCID50 of the wild-type BoHV-5 (parental strain EVI 88/95). After challenge, vaccinated cattle displayed mild signs of respiratory disease, whereas the control group developed respiratory disease and severe encephalitis, which led to culling of 2/4 calves. Searches for viral DNA in the central nervous system (CNS) of vaccinated calves indicated that wild-type BoHV-5 did not replicate, whereas in CNS tissues of calves on the control group, viral DNA was widely distributed. BoHV-5 shedding in nasal secretions was significantly lower in vaccinated calves than in the control group on days 2, 3, 4 and 6 post-challenge (pc). In addition, the duration of virus shedding was significantly shorter in the vaccinated (7 days) than in controls (12 days). Attempts to reactivate latent infection by administration of dexamethasone at 147 days pv led to recrudescence of mild signs of respiratory disease in both vaccinated and control groups. Infectious virus shedding in nasal secretions was detected at reactivation and was significantly lower in vaccinated cattle than in controls on days 11–13 post-reactivation (pr). It is concluded that the inactivated vaccine prepared with the BoHV-5 gI/gE/US9− recombinant was capable of conferring protection to encephalitis when vaccinated cattle were challenged with a large infectious dose of the parental wild type BoHV-5. However, it did not avoid the establishment of latency nor impeded dexamethasone-induced reactivation of the virus, despite a significant reduction in virus shedding after challenge and at reactivation on vaccinated calves."
}

Abstract

Bovine herpesvirus type 5 (BoHV-5) is the causative agent of bovine herpetic encephalitis. In countries where BoHV-5 is prevalent, attempts to vaccinate cattle to prevent clinical signs from BoHV-5-induced disease have relied essentially on vaccination with BoHV-1 vaccines. However, such practice has been shown not to confer full protection to BoHV-5 challenge. In the present study, an inactivated, oil adjuvanted vaccine prepared with a recombinant BoHV-5 from which the genes coding for glycoprotein I (gI), glycoprotein E (gE) and membrane protein US9 were deleted (BoHV-5 gI/gE/US9−), was evaluated in cattle in a vaccination/challenge experiment. The vaccine was prepared from a virus suspension containing a pre-inactivation antigenic mass equivalent to 107.69 TCID50/dose. Three mL of the inactivated vaccine were administered subcutaneously to eight calves serologically negative for BoHV-5 (vaccinated group). Four other calves were mock-vaccinated with an equivalent preparation without viral antigens (control group). Both groups were boostered 28 days later. Neither clinical signs of disease nor adverse effects were observed during or after vaccination. A specific serological response, revealed by the development of neutralizing antibodies, was detected in all vaccinated animals after the first dose of vaccine, whereas control animals remained seronegative. Calves were subsequently challenged on day 77 post-vaccination (pv) with 109.25 TCID50 of the wild-type BoHV-5 (parental strain EVI 88/95). After challenge, vaccinated cattle displayed mild signs of respiratory disease, whereas the control group developed respiratory disease and severe encephalitis, which led to culling of 2/4 calves. Searches for viral DNA in the central nervous system (CNS) of vaccinated calves indicated that wild-type BoHV-5 did not replicate, whereas in CNS tissues of calves on the control group, viral DNA was widely distributed. BoHV-5 shedding in nasal secretions was significantly lower in vaccinated calves than in the control group on days 2, 3, 4 and 6 post-challenge (pc). In addition, the duration of virus shedding was significantly shorter in the vaccinated (7 days) than in controls (12 days). Attempts to reactivate latent infection by administration of dexamethasone at 147 days pv led to recrudescence of mild signs of respiratory disease in both vaccinated and control groups. Infectious virus shedding in nasal secretions was detected at reactivation and was significantly lower in vaccinated cattle than in controls on days 11–13 post-reactivation (pr). It is concluded that the inactivated vaccine prepared with the BoHV-5 gI/gE/US9− recombinant was capable of conferring protection to encephalitis when vaccinated cattle were challenged with a large infectious dose of the parental wild type BoHV-5. However, it did not avoid the establishment of latency nor impeded dexamethasone-induced reactivation of the virus, despite a significant reduction in virus shedding after challenge and at reactivation on vaccinated calves.

M. M. Rigo, D. A. Antunes, M. Sinigaglia, C. C. Fülber, J. A. B. Chies, and G. F. Vieira, “Molecular aspects involved in the immunogenicity against viral epitopes: an immunoinformatic perspective,” in Immunogenicity, Nova Science Publishers, 2011, pp. 1–24.

publisher

BibTeX

@inbook{Rigo-NP10,
  author = "Rigo, M. M. and Antunes, D. A. and Sinigaglia, M. and F\"{u}lber, C. C. and Chies, J. A. B. and Vieira, G. F.",
  title = "Molecular aspects involved in the immunogenicity against viral epitopes: an immunoinformatic perspective",
  booktitle = "Immunogenicity",
  series = "Immunology and Immune System Disorders",
  pages = "1--24",
  publisher = "Nova Science Publishers",
  year = "2011",
  isbn = "978-1-61761-591-7",
  url = "http://www.novapublishers.org/catalog/product_info.php?products_id=25425",
  abstract = "Since the beginning of studies about immune response stimulation against viral infections, many pieces have already been added to complete this puzzle. Once uncovered, it will provide the key elements to the development of more efficient vaccines against a wide diversity of infectious diseases. A thorough understanding of this system involves not only the analysis of epitopes that are presented to the immune system but also the elucidation of the steps required for the generation and selection of immunogenic epitopes, such as the proteolysis mediated by proteasomes, transport associated with antigen processing (carried out by TAP protein) and binding of epitopes to the Major Histocompatibility Complex (MHC). Besides the steps in the antigen intracellular processing pathway, other aspects involved in the selection of immunogenic epitopes, such as its intrinsic avidity by the MHC cleft (on the extracellular surface) and the epitope constitution , are necessary to stimulate the T cell receptor (TCR). Certainly, the epitopes linear sequences are important; however, an epitope is much more than a simple combination of amino acids, which present a distribution of charges and topological features that actively interact with the other elements that form the MHC cleft. These elements will be essential for the induction (or not) of an immune response. In this chapter, we will discuss several aspects involved in the recognition of a viral infection.  What are the typical elements of a viral infection and how does the immune system recognize them? How could different amino acid sequences stimulate the same TCR generating cross-reactive responses? In which way can a virus infection trigger an autoimmune disease? Allied to all these immunological approaches, we intend to present how bioinformatics - or more specifically immunoinformatics - tools can be used to elucidate these processes. Thus, several tools, such as docking and molecular dynamics, peptide:MHC binding and proteasome cleavage predictors will be presented. We will also present and discuss the main molecular immunological databases, including SYFPEITHI, IEDB and IMGT. In summary, we will discuss how population, immunological, and molecular aspects are essential in the comprehension of vaccine design and autoimmunity."
}

Abstract

Since the beginning of studies about immune response stimulation against viral infections, many pieces have already been added to complete this puzzle. Once uncovered, it will provide the key elements to the development of more efficient vaccines against a wide diversity of infectious diseases. A thorough understanding of this system involves not only the analysis of epitopes that are presented to the immune system but also the elucidation of the steps required for the generation and selection of immunogenic epitopes, such as the proteolysis mediated by proteasomes, transport associated with antigen processing (carried out by TAP protein) and binding of epitopes to the Major Histocompatibility Complex (MHC). Besides the steps in the antigen intracellular processing pathway, other aspects involved in the selection of immunogenic epitopes, such as its intrinsic avidity by the MHC cleft (on the extracellular surface) and the epitope constitution , are necessary to stimulate the T cell receptor (TCR). Certainly, the epitopes linear sequences are important; however, an epitope is much more than a simple combination of amino acids, which present a distribution of charges and topological features that actively interact with the other elements that form the MHC cleft. These elements will be essential for the induction (or not) of an immune response. In this chapter, we will discuss several aspects involved in the recognition of a viral infection. What are the typical elements of a viral infection and how does the immune system recognize them? How could different amino acid sequences stimulate the same TCR generating cross-reactive responses? In which way can a virus infection trigger an autoimmune disease? Allied to all these immunological approaches, we intend to present how bioinformatics - or more specifically immunoinformatics - tools can be used to elucidate these processes. Thus, several tools, such as docking and molecular dynamics, peptide:MHC binding and proteasome cleavage predictors will be presented. We will also present and discuss the main molecular immunological databases, including SYFPEITHI, IEDB and IMGT. In summary, we will discuss how population, immunological, and molecular aspects are essential in the comprehension of vaccine design and autoimmunity.

2010

A. P. Varela, C. L. Holz, S. P. Cibulski, T. F. Teixeira, D. A. Antunes, A. C. Franco, L. R. Roehe, M. T. Oliveira, F. S. Campos, D. Dezen, A. Cenci, W. D. Brito, and P. M. Roehe, “Neutralizing antibodies to bovine herpesvirus types 1 (BoHV-1) and 5 (BoHV-5) and its subtypes,” Veterinary Microbiology, vol. 142, no. 3-4, pp. 254–260, May 2010.

publisher

BibTeX

@article{Varela2010-bhv5,
  pubmed = "19926411",
  doi = "10.1016/j.vetmic.2009.10.016",
  author = "Varela, A. P. and Holz, C. L. and Cibulski, S. P. and Teixeira, T. F. and Antunes, D. A. and Franco, A. C. and Roehe, L. R. and Oliveira, M. T. and Campos, F. S. and Dezen, D. and Cenci, A. and Brito, W. D. and Roehe, P. M.",
  title = "{N}eutralizing antibodies to bovine herpesvirus types 1 ({B}o{H}{V}-1) and 5 ({B}o{H}{V}-5) and its subtypes",
  journal = "Veterinary Microbiology",
  year = "2010",
  volume = "142",
  number = "3-4",
  pages = "254--260",
  month = may,
  abstract = "This study was carried out to determine whether the sensitivity of serum neutralization (SN) tests would be affected by the use of distinct subtypes of bovine herpesvirus 1 (BoHV-1) and 5 (BoHV-5) as test challenge viruses. Bovine sera collected from a randomized sample (n=287) were tested in a 24h incubation SN against three type 1 viruses (BoHV-1.1 strains "Los Angeles" (LA) and "EVI 123"; BoHV-1.2a strain "SV 265") and three type 5 viruses (BoHV-5a strain "EVI 88"; BoHV-5b strain "A 663" and BoHV-5c "ISO 97"). SN sensitivity varied greatly depending on the test challenge virus used in the test, particularly when results against each virus were considered individually, where it ranged from 77% (detecting 80 out of 104 antibody-positive sera) with ISO 97 to 91% (95/104) with BoHV-1.1 strain LA. All tests to single viruses revealed a significantly low sensitivity (McNemar's; p<0.05). Maximum sensitivity (104/104) was achieved when positive results to a particular combination of four of the challenge viruses (LA+EVI 123+SV 265+A 663) or some combinations of five viruses (or all six viruses) were added cumulatively. These results provide evidence for no association between any particular virus type/subtype and higher SN sensitivity. In addition, it was clearly shown that when SN is performed with single test challenge viruses, sensitivity can vary so significantly that might compromise control or eradication efforts. Performing SN against a number of different viruses demonstrated to improve significantly the test's sensitivity."
}

Abstract

This study was carried out to determine whether the sensitivity of serum neutralization (SN) tests would be affected by the use of distinct subtypes of bovine herpesvirus 1 (BoHV-1) and 5 (BoHV-5) as test challenge viruses. Bovine sera collected from a randomized sample (n=287) were tested in a 24h incubation SN against three type 1 viruses (BoHV-1.1 strains "Los Angeles" (LA) and "EVI 123"; BoHV-1.2a strain "SV 265") and three type 5 viruses (BoHV-5a strain "EVI 88"; BoHV-5b strain "A 663" and BoHV-5c "ISO 97"). SN sensitivity varied greatly depending on the test challenge virus used in the test, particularly when results against each virus were considered individually, where it ranged from 77% (detecting 80 out of 104 antibody-positive sera) with ISO 97 to 91% (95/104) with BoHV-1.1 strain LA. All tests to single viruses revealed a significantly low sensitivity (McNemar’s; p<0.05). Maximum sensitivity (104/104) was achieved when positive results to a particular combination of four of the challenge viruses (LA+EVI 123+SV 265+A 663) or some combinations of five viruses (or all six viruses) were added cumulatively. These results provide evidence for no association between any particular virus type/subtype and higher SN sensitivity. In addition, it was clearly shown that when SN is performed with single test challenge viruses, sensitivity can vary so significantly that might compromise control or eradication efforts. Performing SN against a number of different viruses demonstrated to improve significantly the test’s sensitivity.

D. A. Antunes, G. F. Vieira, M. M. Rigo, S. P. Cibulski, M. Sinigaglia, and J. A. Chies, “Structural allele-specific patterns adopted by epitopes in the MHC-I cleft and reconstruction of MHC:peptide complexes to cross-reactivity assessment,” PLoS ONE, vol. 5, no. 4, p. e10353, Apr. 2010.

pdf publisher

BibTeX

@article{antunes2010-allele-pattern,
  doi = "10.1371/journal.pone.0010353",
  author = "Antunes, D. A. and Vieira, G. F. and Rigo, M. M. and Cibulski, S. P. and Sinigaglia, M. and Chies, J. A.",
  title = "{S}tructural allele-specific patterns adopted by epitopes in the {M}{H}{C}-{I} cleft and reconstruction of {M}{H}{C}:peptide complexes to cross-reactivity assessment",
  journal = "PLoS ONE",
  year = "2010",
  volume = "5",
  number = "4",
  pages = "e10353",
  month = apr,
  abstract = "The immune system is engaged in a constant antigenic surveillance through the Major Histocompatibility Complex (MHC) class I antigen presentation pathway. This is an efficient mechanism for detection of intracellular infections, especially viral ones. In this work we describe conformational patterns shared by epitopes presented by a given MHC allele and use these features to develop a docking approach that simulates the peptide loading into the MHC cleft. Our strategy, to construct in silico MHC:peptide complexes, was successfully tested by reproducing four different crystal structures of MHC-I molecules available at the Protein Data Bank (PDB). An in silico study of cross-reactivity potential was also performed between the wild-type complex HLA-A2-NS31073 and nine MHC:peptide complexes presenting alanine exchange peptides. This indicates that structural similarities among the complexes can give us important clues about cross reactivity. The approach used in this work allows the selection of epitopes with potential to induce cross-reactive immune responses, providing useful tools for studies in autoimmunity and to the development of more comprehensive vaccines."
}

Abstract

The immune system is engaged in a constant antigenic surveillance through the Major Histocompatibility Complex (MHC) class I antigen presentation pathway. This is an efficient mechanism for detection of intracellular infections, especially viral ones. In this work we describe conformational patterns shared by epitopes presented by a given MHC allele and use these features to develop a docking approach that simulates the peptide loading into the MHC cleft. Our strategy, to construct in silico MHC:peptide complexes, was successfully tested by reproducing four different crystal structures of MHC-I molecules available at the Protein Data Bank (PDB). An in silico study of cross-reactivity potential was also performed between the wild-type complex HLA-A2-NS31073 and nine MHC:peptide complexes presenting alanine exchange peptides. This indicates that structural similarities among the complexes can give us important clues about cross reactivity. The approach used in this work allows the selection of epitopes with potential to induce cross-reactive immune responses, providing useful tools for studies in autoimmunity and to the development of more comprehensive vaccines.

C. C. Fülber, D. A. Antunes, M. M. Rigo, J. A. Chies, M. Sinigaglia, and G. F. Vieira, “Reconstruction of MHC Alleles by Cross Modeling and Structural Assessment,” in International Conference on Bioinformatics and Computational Biology (BIOCOMP’10), 2010, pp. 459–463. Las Vegas, United States (Short-Article)

BibTeX

@inproceedings{Fulber2010-BIOCOMP,
  author = "Fülber, C. C. and Antunes, D. A. and Rigo, M. M. and Chies, J. A. and Sinigaglia, M. and Vieira, G. F.",
  title = "Reconstruction of MHC Alleles by Cross Modeling and Structural Assessment",
  booktitle = "International Conference on Bioinformatics and Computational Biology (BIOCOMP'10)",
  year = "2010",
  pages = "459-463",
  note = "Las Vegas, United States (Short-Article)"
}

2009

M. M. Rigo, D. A. Antunes, G. F. Vieira, and J. A. Chies, “MHC:Peptide Analysis: Implications on the Immunogenicity of Hantaviruses’ N protein,” in Advances in Bioinformatics and Computational Biology - BSB 2009, 2009, pp. 160–163. Porto Alegre, Brazil (Short-Article)

publisher

BibTeX

@inproceedings{Rigo2009,
  doi = "10.1007/978-3-642-03223-3_17",
  author = "Rigo, M. M. and Antunes, D. A. and Vieira, G. F. and Chies, J. A.",
  title = "{MHC:Peptide} Analysis: Implications on the Immunogenicity of Hantaviruses' N protein",
  booktitle = "Advances in Bioinformatics and Computational Biology - BSB 2009",
  year = "2009",
  pages = "160--163",
  publisher = "Springer, Berlin, Heidelberg",
  series = "Lecture Notes in Computer Science",
  editor = "Guimar\~{a}es K.S., Panchenko A., Przytycka T.M",
  note = "Porto Alegre, Brazil (Short-Article)"
}

2008

D. A. Antunes, “Use of bioinformatics tools for the analysis of cross-reactivity likelihood between viral epitopes,” Undergraduate thesis, Federal University of Rio Grande do Sul, Institute of Basic Health Sciences, 2008. Language: Portuguese

pdf publisher

BibTeX

@mastersthesis{Antunes-BS,
  author = "Antunes, D. A.",
  title = "Use of bioinformatics tools for the analysis of cross-reactivity likelihood between viral epitopes",
  school = "Federal University of Rio Grande do Sul, Institute of Basic Health Sciences",
  year = "2008",
  month = aug,
  type = "{U}ndergraduate thesis",
  note = "Language: Portuguese",
  url = "https://www.lume.ufrgs.br/handle/10183/28693",
  abstract = "A reatividade cruzada é definida como a capacidade de um linfócito T em reconhecer, no contexto do Complexo Principal de Histocompatibilidade (MHC), peptídeos não relacionados, provenientes de um mesmo organismo ou mesmo de organismos heterólogos. Este fenômeno já foi descrito em inúmeros trabalhos, embora os mecanismos que permitam este reconhecimento cruzado ainda não tenham sido completamente estabelecidos. O reconhecimento do complexo MHC:peptídeo (pMHC) pelo Receptor de Célula T (TCR) leva à lise da célula apresentadora, o que torna a reatividade cruzada alvo de profundo interesse em estudos que envolvem os mecanismos citotóxicos da resposta imune. Neste trabalho realizamos um estudo in silico da possível ocorrência de reatividade cruzada entre os epitopos virais PA224-233 (Influenza) e HBsAg28-39 (HBV) no contexto do MHC murino H-2Db. O complexo H-2Db:PA224-233 (DbPA224-233) possue estrutura depositada no Protein Data Bank (PDB) sob o código de acesso 1WBY, enquanto a estrutura do complexo DbHBsAg28-39 ainda não foi determinada. Utilizando o programa AutoDock 4 para realizar o docking do epitopo ao MHC e o pacote GROMACS para realizar a minimização de energia (EM) das estruturas geradas, conseguimos construir o complexo DbHBsAg30-39. O programa GRASP2 foi utilizado para as análises de topologia e distribuição de cargas do complexo. A comparação entre a estrutura 1WBY e o complexo gerado indicou forte correlação estrutural, contudo identificamos uma diferença de cargas em uma posição crítica para o reconhecimento pelo TCR. Para contornar esta diferença, construímos um epitopo de Influenza mutado (R7W) e repetimos as análises. Este novo peptídeo apresentou alta afinidade pelo MHC e maior semelhança com o epitopo de HBV, possivelmente induzindo reatividade cruzada. A estratégia desenvolvida para a realização deste trabalho pode ser utilizada para simular complexos pMHC formados com qualquer epitopo e o estudo de topologia/potencial do complexo formado nos permite comparar dois diferentes complexos pMHC sob o ponto de vista do TCR, possibilitando discutir reatividade cruzada in silico. Em conjunto, estas técnicas apresentam grande potencial de aplicação no estudo de patologias autoimunes e no desenvolvimento de vacinas antivirais de amplo espectro."
}

Abstract

A reatividade cruzada é definida como a capacidade de um linfócito T em reconhecer, no contexto do Complexo Principal de Histocompatibilidade (MHC), peptídeos não relacionados, provenientes de um mesmo organismo ou mesmo de organismos heterólogos. Este fenômeno já foi descrito em inúmeros trabalhos, embora os mecanismos que permitam este reconhecimento cruzado ainda não tenham sido completamente estabelecidos. O reconhecimento do complexo MHC:peptídeo (pMHC) pelo Receptor de Célula T (TCR) leva à lise da célula apresentadora, o que torna a reatividade cruzada alvo de profundo interesse em estudos que envolvem os mecanismos citotóxicos da resposta imune. Neste trabalho realizamos um estudo in silico da possível ocorrência de reatividade cruzada entre os epitopos virais PA224-233 (Influenza) e HBsAg28-39 (HBV) no contexto do MHC murino H-2Db. O complexo H-2Db:PA224-233 (DbPA224-233) possue estrutura depositada no Protein Data Bank (PDB) sob o código de acesso 1WBY, enquanto a estrutura do complexo DbHBsAg28-39 ainda não foi determinada. Utilizando o programa AutoDock 4 para realizar o docking do epitopo ao MHC e o pacote GROMACS para realizar a minimização de energia (EM) das estruturas geradas, conseguimos construir o complexo DbHBsAg30-39. O programa GRASP2 foi utilizado para as análises de topologia e distribuição de cargas do complexo. A comparação entre a estrutura 1WBY e o complexo gerado indicou forte correlação estrutural, contudo identificamos uma diferença de cargas em uma posição crítica para o reconhecimento pelo TCR. Para contornar esta diferença, construímos um epitopo de Influenza mutado (R7W) e repetimos as análises. Este novo peptídeo apresentou alta afinidade pelo MHC e maior semelhança com o epitopo de HBV, possivelmente induzindo reatividade cruzada. A estratégia desenvolvida para a realização deste trabalho pode ser utilizada para simular complexos pMHC formados com qualquer epitopo e o estudo de topologia/potencial do complexo formado nos permite comparar dois diferentes complexos pMHC sob o ponto de vista do TCR, possibilitando discutir reatividade cruzada in silico. Em conjunto, estas técnicas apresentam grande potencial de aplicação no estudo de patologias autoimunes e no desenvolvimento de vacinas antivirais de amplo espectro.

M. M. Rigo, D. A. Antunes, G. F. Vieira, and J. A. Chies, “Immunogenic regions on the N protein from hantavirus genus: implications in vaccine development,” in Anals of the 4th International Conference of the Brazilian Association for Bioinformatics and Computational Biology (X-Meeting 2008), 2008. Salvador, Brazil (Short-Article)

BibTeX

@inproceedings{Rigo-XM8,
  author = "Rigo, M. M. and Antunes, D. A. and Vieira, G. F. and Chies, J. A.",
  title = "Immunogenic regions on the N protein from hantavirus genus: implications in vaccine development",
  booktitle = "Anals of the 4th International Conference of the Brazilian Association for Bioinformatics and Computational Biology (X-Meeting 2008)",
  year = "2008",
  note = "Salvador, Brazil (Short-Article)"
}

2007

D. A. Antunes, G. F. Vieira, and J. A. Chies, “Structural analyses of viral epitopes and proteolytic simulation of its proteins,” in Anals of 3rd International Conference of the Brazilian Association for Bioinformatics and Computational Biology (X-Meeting 2007), 2007. São Paulo, Brazil (Short-Article)

BibTeX

@inproceedings{Antunes-XM7,
  author = "Antunes, D. A. and Vieira, G. F. and Chies, J. A.",
  title = "Structural analyses of viral epitopes and proteolytic simulation of its proteins",
  booktitle = "Anals of 3rd International Conference of the Brazilian Association for Bioinformatics and Computational Biology (X-Meeting 2007)",
  year = "2007",
  note = "S\~{a}o Paulo, Brazil (Short-Article)"
}

G. F. Vieira, D. A. Antunes, and J. A. Chies, “Viral epitopes: which is(are) the target(s)?,” in Anals of 3rd International Conference of the Brazilian Association for Bioinformatics and Computational Biology (X-Meeting 2007), 2007. São Paulo, Brazil (Short-Article)

BibTeX

@inproceedings{Vieira-XM7,
  author = "Vieira, G. F. and Antunes, D. A. and Chies, J. A.",
  title = "Viral epitopes: which is(are) the target(s)?",
  booktitle = "Anals of 3rd International Conference of the Brazilian Association for Bioinformatics and Computational Biology (X-Meeting 2007)",
  year = "2007",
  note = "S\~{a}o Paulo, Brazil (Short-Article)"
}

Dinler A. Antunes

2020

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2019

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2018

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2017

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2016

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2015

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2014

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2013

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2012

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2011

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2010

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2009