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References from Linear antibody epitope prediction using AlphaFold2. Local targets link to admitted publications; unresolved targets remain external evidence.
Immunebuilder: deep-learning models for predicting the structures of immune proteins
10.1038/s42003-023-04927-7 · 2023 · External reference
OpenFold: retraining alphaFold2 yields new insights into its learning mechanisms and capacity for generalization
10.1101/2022.11.20.517210 · 2022 · External reference
Modeling antibody-antigen complexes by information-driven docking
10.1016/j.str.2019.10.011 · 2020 · External reference
Pretrainable geometric graph neural network for antibody affinity maturation
10.1038/s41467-024-51563-8 · 2021 · External reference
ZDOCK: an initial-stage protein-docking algorithm
10.1002/prot.10389 · 2003 · External reference
Crystal structure of a peptide complex of anti-influenza peptide antibody Fab 26/9: Comparison of two different antibodies bound to the same peptide antigen
10.1006/jmbi.1994.1530 · 1994 · External reference
PAbFold
2024 · External reference
The ClusPro AbEMap web server for the prediction of antibody epitopes
10.1038/s41596-023-00826-7 · 2023 · External reference
Mapping of antibody epitopes based on docking and homology modeling
10.1002/prot.26420 · 2023 · External reference
HADDOCK: a protein-protein docking approach based on biochemical or biophysical information
10.1021/ja026939x · 2003 · External reference
Antibody recognition of a highly conserved influenza virus epitope: implications for universal prevention and therapy
10.1126/science.1171491 · 2009 · External reference
Protein complex prediction with alphaFold-Multimer
10.1101/2021.10.04.463034 · 2022 · External reference
A single-chain antibody/epitope system for functional analysis of protein-protein interactions
10.1021/bi0263309 · 2002 · External reference
Improved docking of protein models by a combination of alphafold2 and ClusPro
10.1101/2021.09.07.459290 · 2022 · External reference
Towards the accurate modelling of antibody-antigen complexes from sequence using machine learning and information-driven docking
10.1101/2023.11.17.567543 · 2023 · External reference
Computational methods in immunology and vaccinology: design and development of antibodies and immunogens
10.1021/acs.jctc.3c00513 · 2023 · External reference
De novo generation of antibody CDRH3 with a pre-trained generative large language model
10.1038/s41467-024-50903-y · 2023 · External reference
Advances in computational structure-based antibody design
10.1016/j.sbi.2022.102379 · 2022 · External reference
Structural modeling of antibody variable regions using deep learning-progress and perspectives on drug discovery
10.3389/fmolb.2023.1214424 · 2023 · External reference
DSMBind: SE(3) denoising score matching for unsupervised binding energy prediction and nanobody design
10.1101/2023.12.10.570461 · 2023 · External reference
Kabat database and its applications: 30 years after the first variability plot
10.1093/nar/28.1.214 · 2000 · External reference
Highly accurate protein structure prediction with AlphaFold
10.1038/s41586-021-03819-2 · 2021 · External reference
A discussion of the solution for the best rotation to relate two sets of vectors
10.1107/s0567739478001680 · 1978 · External reference
Can AlphaFold2 predict protein-peptide complex structures accurately?
10.1101/2021.07.27.453972 · 2021 · External reference
The structure of the anti-c-myc antibody 9E10 Fab fragment/epitope peptide complex reveals a novel binding mode dominated by the heavy chain hypervariable loops
10.1002/prot.22080 · 2008 · External reference
Improved method for predicting linear B-cell epitopes
10.1186/1745-7580-2-2 · 2006 · External reference
A purely algebraic justification of the kabsch-umeyama algorithm
10.6028/jres.124.028 · 2019 · External reference
Equifold: protein structure prediction with a novel coarse-grained structure representation
10.1101/2022.10.07.511322 · 2023 · External reference
Evolutionary-scale prediction of atomic-level protein structure with a language model
10.1126/science.ade2574 · 2023 · External reference
Conformational epitope matching and prediction based on protein surface spiral features
10.1186/s12864-020-07303-5 · 2021 · External reference
lDDT: a local superposition-free score for comparing protein structures and models using distance difference tests
10.1093/bioinformatics/btt473 · 2013 · External reference
Fast and sensitive taxonomic assignment to metagenomic contigs
10.1093/bioinformatics/btab184 · 2021 · External reference
ColabFold: making protein folding accessible to all
10.1038/s41592-022-01488-1 · 2022 · External reference
MMseqs2
2026 · External reference
Structure and mechanistic analysis of the anti-human immunodeficiency virus type 1 antibody 2F5 in complex with its gp41 epitope
10.1128/jvi.78.19.10724-10737.2004 · 2004 · External reference
ColabFold
2026 · External reference
A helix propensity scale based on experimental studies of peptides and proteins
10.1016/s0006-3495(98)77529-0 · 1998 · External reference
Evaluation of the ability of alphafold to predict the three-dimensional structures of antibodies and epitopes
10.4049/jimmunol.2300150 · 2023 · External reference
ElliPro: a new structure-based tool for the prediction of antibody epitopes
10.1186/1471-2105-9-514 · 2008 · External reference
Fast, accurate antibody structure prediction from deep learning on massive set of natural antibodies
10.1016/j.bpj.2021.11.1942 · 2022 · External reference
Antibody structure prediction using interpretable deep learning
10.1016/j.patter.2021.100406 · 2022 · External reference
Prediction of continuous B-cell epitopes in an antigen using recurrent neural network
10.1002/prot.21078 · 2006 · External reference
A genetically encoded probe for live-cell imaging of H4K20 Monomethylation
10.1016/j.jmb.2016.08.010 · 2016 · External reference
SEMA: Antigen B-cell conformational epitope prediction using deep transfer learning
10.3389/fimmu.2022.960985 · 2022 · External reference
Structural rationale for the broad neutralization of HIV-1 by human monoclonal antibody 447-52D
10.1016/j.str.2004.01.003 · 2004 · External reference
Development of a SARS-CoV-2 nucleocapsid specific monoclonal antibody
10.1016/j.virol.2021.01.003 · 2021 · External reference
Harnessing protein folding neural networks for peptide-protein docking
10.1038/s41467-021-27838-9 · 2022 · External reference
The international immunogenetics database IMGT
10.1016/s0145-305x(02)00094-0 · 2003 · External reference
Identifying B-cell epitopes using AlphaFold2 predicted structures and pretrained language model
10.1093/bioinformatics/btad187 · 2023 · External reference
A genetically encoded probe for imaging nascent and mature HA-tagged proteins in vivo
10.1038/s41467-019-10846-1 · 2019 · External reference
Structural definition of a conserved neutralization epitope on HIV-1 gp120
10.1038/nature05580 · 2007 · External reference
PAbFold: Linear Antibody Epitope Prediction using AlphaFold2
10.5281/zenodo.10884181 · 2024 · External reference
ZDOCK: an initial-stage protein-docking algorithm
10.1002/prot.10389 · ExternalCitation · doi-reference
Prediction of continuous B-cell epitopes in an antigen using recurrent neural network
10.1002/prot.21078 · ExternalCitation · doi-reference
The structure of the anti-c-myc antibody 9E10 Fab fragment/epitope peptide complex reveals a novel binding mode dominated by the heavy chain hypervariable loops
10.1002/prot.22080 · ExternalCitation · doi-reference
Mapping of antibody epitopes based on docking and homology modeling
10.1002/prot.26420 · ExternalCitation · doi-reference
Crystal structure of a peptide complex of anti-influenza peptide antibody Fab 26/9: Comparison of two different antibodies bound to the same peptide antigen
10.1006/jmbi.1994.1530 · ExternalCitation · doi-reference
Fast, accurate antibody structure prediction from deep learning on massive set of natural antibodies
10.1016/j.bpj.2021.11.1942 · ExternalCitation · doi-reference
A genetically encoded probe for live-cell imaging of H4K20 Monomethylation
10.1016/j.jmb.2016.08.010 · ExternalCitation · doi-reference
Antibody structure prediction using interpretable deep learning
10.1016/j.patter.2021.100406 · ExternalCitation · doi-reference
Advances in computational structure-based antibody design
10.1016/j.sbi.2022.102379 · ExternalCitation · doi-reference
Structural rationale for the broad neutralization of HIV-1 by human monoclonal antibody 447-52D
10.1016/j.str.2004.01.003 · ExternalCitation · doi-reference
Modeling antibody-antigen complexes by information-driven docking
10.1016/j.str.2019.10.011 · ExternalCitation · doi-reference
Development of a SARS-CoV-2 nucleocapsid specific monoclonal antibody
10.1016/j.virol.2021.01.003 · ExternalCitation · doi-reference
A helix propensity scale based on experimental studies of peptides and proteins
10.1016/s0006-3495(98)77529-0 · ExternalCitation · doi-reference
The international immunogenetics database IMGT
10.1016/s0145-305x(02)00094-0 · ExternalCitation · doi-reference
Computational methods in immunology and vaccinology: design and development of antibodies and immunogens
10.1021/acs.jctc.3c00513 · ExternalCitation · doi-reference
A single-chain antibody/epitope system for functional analysis of protein-protein interactions
10.1021/bi0263309 · ExternalCitation · doi-reference
HADDOCK: a protein-protein docking approach based on biochemical or biophysical information
10.1021/ja026939x · ExternalCitation · doi-reference
Structural definition of a conserved neutralization epitope on HIV-1 gp120
10.1038/nature05580 · ExternalCitation · doi-reference
A genetically encoded probe for imaging nascent and mature HA-tagged proteins in vivo
10.1038/s41467-019-10846-1 · ExternalCitation · doi-reference
Harnessing protein folding neural networks for peptide-protein docking
10.1038/s41467-021-27838-9 · ExternalCitation · doi-reference
De novo generation of antibody CDRH3 with a pre-trained generative large language model
10.1038/s41467-024-50903-y · ExternalCitation · doi-reference
Pretrainable geometric graph neural network for antibody affinity maturation
10.1038/s41467-024-51563-8 · ExternalCitation · doi-reference
Highly accurate protein structure prediction with AlphaFold
10.1038/s41586-021-03819-2 · ExternalCitation · doi-reference
ColabFold: making protein folding accessible to all
10.1038/s41592-022-01488-1 · ExternalCitation · doi-reference
The ClusPro AbEMap web server for the prediction of antibody epitopes
10.1038/s41596-023-00826-7 · ExternalCitation · doi-reference
Immunebuilder: deep-learning models for predicting the structures of immune proteins
10.1038/s42003-023-04927-7 · ExternalCitation · doi-reference
Fast and sensitive taxonomic assignment to metagenomic contigs
10.1093/bioinformatics/btab184 · ExternalCitation · doi-reference
Identifying B-cell epitopes using AlphaFold2 predicted structures and pretrained language model
10.1093/bioinformatics/btad187 · ExternalCitation · doi-reference
lDDT: a local superposition-free score for comparing protein structures and models using distance difference tests
10.1093/bioinformatics/btt473 · ExternalCitation · doi-reference
Kabat database and its applications: 30 years after the first variability plot
10.1093/nar/28.1.214 · ExternalCitation · doi-reference
Can AlphaFold2 predict protein-peptide complex structures accurately?
10.1101/2021.07.27.453972 · ExternalCitation · doi-reference
Improved docking of protein models by a combination of alphafold2 and ClusPro
10.1101/2021.09.07.459290 · ExternalCitation · doi-reference
Protein complex prediction with alphaFold-Multimer
10.1101/2021.10.04.463034 · ExternalCitation · doi-reference
Equifold: protein structure prediction with a novel coarse-grained structure representation
10.1101/2022.10.07.511322 · ExternalCitation · doi-reference
OpenFold: retraining alphaFold2 yields new insights into its learning mechanisms and capacity for generalization
10.1101/2022.11.20.517210 · ExternalCitation · doi-reference
Towards the accurate modelling of antibody-antigen complexes from sequence using machine learning and information-driven docking
10.1101/2023.11.17.567543 · ExternalCitation · doi-reference
DSMBind: SE(3) denoising score matching for unsupervised binding energy prediction and nanobody design
10.1101/2023.12.10.570461 · ExternalCitation · doi-reference
A discussion of the solution for the best rotation to relate two sets of vectors
10.1107/s0567739478001680 · ExternalCitation · doi-reference
Antibody recognition of a highly conserved influenza virus epitope: implications for universal prevention and therapy
10.1126/science.1171491 · ExternalCitation · doi-reference
Evolutionary-scale prediction of atomic-level protein structure with a language model
10.1126/science.ade2574 · ExternalCitation · doi-reference
Structure and mechanistic analysis of the anti-human immunodeficiency virus type 1 antibody 2F5 in complex with its gp41 epitope
10.1128/jvi.78.19.10724-10737.2004 · ExternalCitation · doi-reference
ElliPro: a new structure-based tool for the prediction of antibody epitopes
10.1186/1471-2105-9-514 · ExternalCitation · doi-reference
Improved method for predicting linear B-cell epitopes
10.1186/1745-7580-2-2 · ExternalCitation · doi-reference
Conformational epitope matching and prediction based on protein surface spiral features
10.1186/s12864-020-07303-5 · ExternalCitation · doi-reference
SEMA: Antigen B-cell conformational epitope prediction using deep transfer learning
10.3389/fimmu.2022.960985 · ExternalCitation · doi-reference
Structural modeling of antibody variable regions using deep learning-progress and perspectives on drug discovery
10.3389/fmolb.2023.1214424 · ExternalCitation · doi-reference
Evaluation of the ability of alphafold to predict the three-dimensional structures of antibodies and epitopes
10.4049/jimmunol.2300150 · ExternalCitation · doi-reference
PAbFold: Linear Antibody Epitope Prediction using AlphaFold2
10.5281/zenodo.10884181 · ExternalCitation · doi-reference
A purely algebraic justification of the kabsch-umeyama algorithm
10.6028/jres.124.028 · ExternalCitation · doi-reference
