ArticleBioinformatics (Oxford, England)2019
AbPredict 2: a server for accurate and unstrained structure prediction of antibody variable domains.
Article in Bioinformatics (Oxford, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- AI-Driven Design Platforms of Next-Generation Antibody Therapeutics.Topics in current chemistry (Cham) · 2026Review
- Artificial intelligence in antibody design and development: harnessing the power of computational approaches.Medical & biological engineering & computing · 2025Review
- Nanobodies: From Discovery to AI-Driven Design.Biology · 2025Review
- Antibody-Antibiotic Conjugates: A Comprehensive Review on Their Therapeutic Potentials Against BacterialInfections.Journal of clinical laboratory analysis · 2024Review
- Computational Methods in Immunology and Vaccinology: Design and Development of Antibodies and Immunogens.Journal of chemical theory and computation · 2023Review
- Automated optimisation of solubility and conformational stability of antibodies and proteins.Nature communications · 2023Article
- How can we discover developable antibody-based biotherapeutics?Frontiers in molecular biosciences · 2023Review
- VInternational journal of molecular sciences · 2022Review
- NanoNet: Rapid and accurate end-to-end nanobody modeling by deep learning.Frontiers in immunology · 2022Article
- Article
- The neutralization potency of anti-SARS-CoV-2 therapeutic human monoclonal antibodies is retained against viral variants.Cell reports · 2021Article
- The AbDesign computational pipeline for modular backbone assembly and design of binders and enzymes.Protein science : a publication of the Protein Society · 2021Article
- Computational approaches to therapeutic antibody design: established methods and emerging trends.Briefings in bioinformatics · 2020Review
- How repertoire data are changing antibody science.The Journal of biological chemistry · 2020Review
- Macromolecular modeling and design in Rosetta: recent methods and frameworks.Nature methods · 2020Review
- Optimizing antibody affinity and stability by the automated design of the variable light-heavy chain interfaces.PLoS computational biology · 2019Article
- Review
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
summaryMethods for antibody structure prediction rely on sequence homology to experimentally determined structures. Resulting models may be accurate but are often stereochemically strained, limiting their usefulness in modeling and design workflows. We present the AbPredict 2 web-server, which instead of using sequence homology, conducts a Monte Carlo-based search for low-energy combinations of backbone conformations to yield accurate and unstrained antibody structures. AVAILABILITY AND IMPLEMENTATION: We introduce several important improvements over the previous AbPredict implementation: (i) backbones and sidechains are now modeled using ideal bond lengths and angles, substantially reducing stereochemical strain, (ii) sampling of the rigid-body orientation at the light-heavy chain interface is improved, increasing model accuracy and (iii) runtime is reduced 20-fold without compromising accuracy, enabling the implementation of AbPredict 2 as a fully automated web-server (http://abpredict.weizmann.ac.il). Accurate and unstrained antibody model structures may in some cases obviate the need for experimental structures in antibody optimization workflows.
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Registered trials
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