ArticlemAbs
Challenges in antibody structure prediction.
Article in mAbs. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
- Article
- Antibody-drug conjugate engineering: from design to efficacy and safety.Signal transduction and targeted therapy · 2026Review
- Humanized Anti-PD-1 Antibodies Generated Using The Conditional Kernel-Elastic Autoencoder.bioRxiv : the preprint server for biology · 2026Article
- Benchmarking sequence-based and AlphaFold-based methods for pMHC-II binding core prediction: distinct strengths and consensus approaches.BMC medical genomics · 2026Article
- Repertoire-scale antibody structural prediction informs therapeutic design.Science advances · 2026Article
- NanoBondy Reaction through NeissLock Anhydride Allows Covalent Immune Cell Decoration.Bioconjugate chemistry · 2026Article
- Disulphide and sequence-encoded conformational priors guide nanobody structure prediction.bioRxiv : the preprint server for biology · 2026Article
- Integrating deep learning with physics based modeling enables high precision antibody antigen interface prediction.Scientific reports · 2026Article
- Structural quality-tier assessment for TCR-pMHC functional enrichment.Frontiers in immunology · 2026Article
- Benchmarking antibody modeling tools across structure prediction, docking, and paratope-epitope interface analysis.Bioinformatics advances · 2026Article
- Nanobodies in biomedicine: from molecular characteristics to fabrication and clinical translation.Military Medical Research · 2026Review
- Multiscale Computational Studies of PEG Chain Length Effects on HER2 mAb Fc Structure and Binding Energetics.ACS omega · 2025Article
- Resolving the conformational ensemble of a membrane protein by integrating small-angle scattering with AlphaFold.PLoS computational biology · 2025Article
- Unveiling the influence of fastest nobel prize winner discovery: alphafold's algorithmic intelligence in medical sciences.Journal of molecular modeling · 2025Review
- Comparison of sequence- and structure-based antibody clustering approaches on simulated repertoire sequencing data.PLoS computational biology · 2025Article
- Structure-Based Epitope Profiling with the Structural Profiling of Antibodies to Cluster by Epitope 2 (SPACE2) Algorithm.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Biophysical cartography of the native and human-engineered antibody landscapes quantifies the plasticity of antibody developability.Communications biology · 2024Article
- Protein loop structure prediction by community-based deep learning and its application to antibody CDR H3 loop modeling.PLoS computational biology · 2024Article
- Experimental Structures of Antibody/MHC-I Complexes Reveal Details of Epitopes Overlooked by Computational Prediction.Journal of immunology (Baltimore, Md. : 1950) · 2024Article
- Building Representation Learning Models for Antibody Comprehension.Cold Spring Harbor perspectives in biology · 2024Review
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Advances in structural biology and the exponential increase in the amount of high-quality experimental structural data available in the Protein Data Bank has motivated numerous studies to tackle the grand challenge of predicting protein structures. In 2020 AlphaFold2 revolutionized the field using a combination of artificial intelligence and the evolutionary information contained in multiple sequence alignments. Antibodies are one of the most important classes of biotherapeutic proteins. Accurate structure models are a prerequisite to advance biophysical property predictions and consequently antibody design. Specialized tools used to predict antibody structures based on different principles have profited from current advances in protein structure prediction based on artificial intelligence. Here, we emphasize the importance of reliable protein structure models and highlight the enormous advances in the field, but we also aim to increase awareness that protein structure models, and in particular antibody models, may suffer from structural inaccuracies, namely incorrect cis-amide bonds, wrong stereochemistry or clashes. We show that these inaccuracies affect biophysical property predictions such as surface hydrophobicity. Thus, we stress the importance of carefully reviewing protein structure models before investing further computing power and setting up experiments. To facilitate the assessment of model quality, we provide a tool "TopModel" to validate structure models.
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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.