ArticleProceedings of the National Academy of Sciences of the United States of America2017
Principles for computational design of binding antibodies.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers.
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Who cites it
70 citing papers in PubMed, 144 citations in OpenAlex.
- Humanized Anti-PD-1 Antibodies Generated Using The Conditional Kernel-Elastic Autoencoder.bioRxiv : the preprint server for biology · 2026Article
- Confidence scoring for deep learning-predicted antibody-antigen complexes: AntiConf as a precision-driven metric.Briefings in bioinformatics · 2026Article
- ImmunoMatch learns and predicts cognate pairing of heavy and light immunoglobulin chains.Nature methods · 2026Article
- Optimizing the breadth of SARS-CoV-2-neutralizing antibodies in vivo and in silico.Human vaccines & immunotherapeutics · 2025Review
- Artificial intelligence in antibody design and development: harnessing the power of computational approaches.Medical & biological engineering & computing · 2025Review
- Article
- Structural insights and predictive modelling of a novel anti-HER2 scFv and Leptulipin: a newly designed immunotoxin protein for HER2 positive cancers.Toxicology research · 2025Article
- Evolutionary paths that link orthogonal pairs of binding proteins.Cell systems · 2025Article
- Design of nanobody targeting SARS-CoV-2 spike glycoprotein using CDR-grafting assisted by molecular simulation and machine learning.PLoS computational biology · 2025Article
- Revolutionizing oncology: the role of Artificial Intelligence (AI) as an antibody design, and optimization tools.Biomarker research · 2025Review
- Turn TRAIL Into Better Anticancer Therapeutic Through TRAIL Fusion Proteins.Cancer medicine · 2025Review
- Harnessing Deep Learning Methods for Voltage-Gated Ion Channel Drug Discovery.Physiology (Bethesda, Md.) · 2025Review
- Multiplexed volumetric CLEM enabled by scFvs provides insights into the cytology of cerebellar cortex.Nature communications · 2024Article
- Opportunities and challenges in design and optimization of protein function.Nature reviews. Molecular cell biology · 2024Review
- rAbDesFlow: a novel workflow for computational recombinant antibody design for healthcare engineering.Antibody therapeutics · 2024Article
- Computational optimization of antibody humanness and stability by systematic energy-based ranking.Nature biomedical engineering · 2024Article
- Biophysical Analysis of Therapeutic Antibodies in the Early Development Pipeline.Biologics : targets & therapy · 2024Review
- Exploring stevioside binding affinity with various proteins and receptors actively involved in the signaling pathway and a future candidate for diabetic patients.Frontiers in pharmacology · 2024Article
- "Redirecting an anti-IL-1β antibody to bind a new, unrelated and computationally predicted epitope on hIL-17A".Communications biology · 2023Article
- Protein engineering via sequence-performance mapping.Cell systems · 2023Review
10 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
9 authors at 2 institutions in 2 countries.
Funding
Abstract
Natural proteins must both fold into a stable conformation and exert their molecular function. To date, computational design has successfully produced stable and atomically accurate proteins by using so-called "ideal" folds rich in regular secondary structures and almost devoid of loops and destabilizing elements, such as cavities. Molecular function, such as binding and catalysis, however, often demands nonideal features, including large and irregular loops and buried polar interaction networks, which have remained challenging for fold design. Through five design/experiment cycles, we learned principles for designing stable and functional antibody variable fragments (Fvs). Specifically, we (
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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.