HLA-Arena: A Customizable Environment for the Structural Modeling and Analysis of Peptide-HLA Complexes for Cancer Immunotherapy

dc.citation.firstpage623en_US
dc.citation.issueNumber4en_US
dc.citation.journalTitleJCO Clinical Cancer Informaticsen_US
dc.citation.lastpage636en_US
dc.contributor.authorAntunes, Dinler A.en_US
dc.contributor.authorAbella, Jayvee R.en_US
dc.contributor.authorHall-Swan, Sarahen_US
dc.contributor.authorDevaurs, Didieren_US
dc.contributor.authorConev, Anjaen_US
dc.contributor.authorMoll, Marken_US
dc.contributor.authorLizée, Gregoryen_US
dc.contributor.authorKavraki, Lydia E.en_US
dc.date.accessioned2020-08-12T19:06:09Zen_US
dc.date.available2020-08-12T19:06:09Zen_US
dc.date.issued2020en_US
dc.description.abstractPURPOSE: 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.en_US
dc.identifier.citationAntunes, Dinler A., Abella, Jayvee R., Hall-Swan, Sarah, et al.. "HLA-Arena: A Customizable Environment for the Structural Modeling and Analysis of Peptide-HLA Complexes for Cancer Immunotherapy." <i>JCO Clinical Cancer Informatics,</i> no. 4 (2020) ASCO: 623-636. https://doi.org/10.1200/CCI.19.00123.en_US
dc.identifier.doihttps://doi.org/10.1200/CCI.19.00123en_US
dc.identifier.urihttps://hdl.handle.net/1911/109194en_US
dc.language.isoengen_US
dc.publisherASCOen_US
dc.rightsLicensed under the Creative Commons Attribution 4.0 License: https://creativecommons.org/licenses/by/4.0/en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.titleHLA-Arena: A Customizable Environment for the Structural Modeling and Analysis of Peptide-HLA Complexes for Cancer Immunotherapyen_US
dc.typeJournal articleen_US
dc.type.dcmiTexten_US
dc.type.publicationpublisher versionen_US
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