ArticleProteins2015
AbDesign: An algorithm for combinatorial backbone design guided by natural conformations and sequences.
Article in Proteins, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers.
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Who cites it
57 citing papers in PubMed, 110 citations in OpenAlex.
- A Multi-Model Strategy for Optimizing Hepatitis B Virus preS1 Epitope Recognition by the Antibody HzKR127.Current issues in molecular biology · 2026Article
- CoMBCR: Co-Learning Multi-Modalities of BCRs and gene expressions.Bioinformatics (Oxford, England) · 2026Article
- De novo design of epitope-specific antibodies via a structure-driven computational workflow.Nature communications · 2025Article
- Artificial intelligence in protein-based detection and inhibition of AMR pathways.Journal of computer-aided molecular design · 2025Review
- Computational structural optimization enhances IL13Rα2 - B7-H3 tandem CAR T cells to overcome antigen-heterogeneity-mediated tumor escape.Molecular therapy : the journal of the American Society of Gene Therapy · 2025Article
- AntiBMPNN: Structure-Guided Graph Neural Networks for Precision Antibody Engineering.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Nanodesigner: resolving the complex-CDR interdependency with iterative refinement.Journal of cheminformatics · 2025Article
- Progress toward new function and design of extracellular G protein-coupled receptor nanobodies.Molecular pharmacology · 2025Review
- Revolutionizing oncology: the role of Artificial Intelligence (AI) as an antibody design, and optimization tools.Biomarker research · 2025Review
- Applying computational protein design to therapeutic antibody discovery - current state and perspectives.Frontiers in immunology · 2025Review
- Antibody design using deep learning: from sequence and structure design to affinity maturation.Briefings in bioinformatics · 2024Review
- Context-dependent design of induced-fit enzymes using deep learning generates well-expressed, thermally stable and active enzymes.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Computational Methods in Immunology and Vaccinology: Design and Development of Antibodies and Immunogens.Journal of chemical theory and computation · 2023Review
- Improved HIV-1 neutralization breadth and potency of V2-apex antibodies by in silico design.Cell reports · 2023Article
- Designed Loop Extension Followed by Combinatorial Screening Confers High Specificity to a Broad Matrix MetalloproteinaseInhibitor.Journal of molecular biology · 2023Article
- Monoclonal antibody designed for SARS-nCoV-2 spike protein of receptor binding domain on antigenic targeted epitopes for inhibition to prevent viral entry.Molecular diversity · 2023Article
- Towards an optimal monoclonal antibody with higher binding affinity to the receptor-binding domain of SARS-CoV-2 spike proteins from different variants.Colloids and surfaces. B, Biointerfaces · 2023Article
- Rational strategies for enhancing mAb binding to SARS-CoV-2 variants through CDR diversification and antibody-escape prediction.Frontiers in immunology · 2023Article
- Assessing and enhancing foldability in designed proteins.Protein science : a publication of the Protein Society · 2022Article
- Deciphering the language of antibodies using self-supervised learning.Patterns (New York, N.Y.) · 2022Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
Abstract
Computational design of protein function has made substantial progress, generating new enzymes, binders, inhibitors, and nanomaterials not previously seen in nature. However, the ability to design new protein backbones for function--essential to exert control over all polypeptide degrees of freedom--remains a critical challenge. Most previous attempts to design new backbones computed the mainchain from scratch. Here, instead, we describe a combinatorial backbone and sequence optimization algorithm called AbDesign, which leverages the large number of sequences and experimentally determined molecular structures of antibodies to construct new antibody models, dock them against target surfaces and optimize their sequence and backbone conformation for high stability and binding affinity. We used the algorithm to produce antibody designs that target the same molecular surfaces as nine natural, high-affinity antibodies; in five cases interface sequence identity is above 30%, and in four of those the backbone conformation at the core of the antibody binding surface is within 1 Å root-mean square deviation from the natural antibodies. Designs recapitulate polar interaction networks observed in natural complexes, and amino acid sidechain rigidity at the designed binding surface, which is likely important for affinity and specificity, is high compared to previous design studies. In designed anti-lysozyme antibodies, complementarity-determining regions (CDRs) at the periphery of the interface, such as L1 and H2, show greater backbone conformation diversity than the CDRs at the core of the interface, and increase the binding surface area compared to the natural antibody, potentially enhancing affinity and specificity.
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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.