ReviewCurrent topics in medicinal chemistry2018
Structure-based Methods for Binding Mode and Binding Affinity Prediction for Peptide-MHC Complexes.
Review in Current topics in medicinal chemistry, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
42 citing papers in PubMed.
- Benchmarking sequence-based and AlphaFold-based methods for pMHC-II binding core prediction: distinct strengths and consensus approaches.BMC medical genomics · 2026Article
- SwiftTCR: efficient computational docking protocol of TCRpMHC-I complexes using restricted rotation matrices.Briefings in bioinformatics · 2026Article
- A high-speed attention network for MHC-bound peptide identification and 3D modeling.Cell reports methods · 2026Article
- Review
- Potent and dose-sparing next-generation SARS-CoV-2 vaccine, mRNA-1283, induces polyfunctional and durable T cell immunity.NPJ vaccines · 2026Article
- Exploring Ketones in Chrysopogon zizanioides: A Computational Molecular Dynamic Approach to c-Met Modulation.Molecular biotechnology · 2026Article
- Multi-strategy embedded framework for neoantigen vaccine maturation.Scientific reports · 2026Article
- STRUMP-I: Structure-Based Machine Learning Approach to pMHC-I Binding Prediction Using Force Field Energy Features.Computational and structural biotechnology journal · 2026Article
- STRUMP-I: Structure-based machine learning approach to pMHC-I binding prediction using force field energy features.bioRxiv : the preprint server for biology · 2025Article
- Computational methods and data resources for predicting tumor neoantigens.Briefings in bioinformatics · 2025Review
- RankMHC: Learning to Rank Class-I Peptide-MHC Structural Models.Journal of chemical information and modeling · 2024Article
- Strengths and limitations of web servers for the modeling of TCRpMHC complexes.Computational and structural biotechnology journal · 2024Article
- Advances of computational methods enhance the development of multi-epitope vaccines.Briefings in bioinformatics · 2024Review
- Can AlphaFold's breakthrough in protein structure help decode the fundamental principles of adaptive cellular immunity?Nature methods · 2024Review
- APE-Gen2.0: Expanding Rapid Class I Peptide-Major Histocompatibility Complex Modeling to Post-Translational Modifications and Noncanonical Peptide Geometries.Journal of chemical information and modeling · 2024Article
- Accurate modeling of peptide-MHC structures with AlphaFold.Structure (London, England : 1993) · 2024Article
- Editorial: Quantification and prediction of T-cell cross-reactivity through experimental and computational methods.Frontiers in immunology · 2024Article
- Conformational plasticity of RAS Q61 family of neoepitopes results in distinct features for targeted recognition.Nature communications · 2023Article
- Neoantigen-targeted TCR-engineered T cell immunotherapy: current advances and challenges.Biomarker research · 2023Review
- HLA3DB: comprehensive annotation of peptide/HLA complexes enables blind structure prediction of T cell epitopes.Nature communications · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.