ArticlePLoS computational biology2019
Optimizing antibody affinity and stability by the automated design of the variable light-heavy chain interfaces.
Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 84 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
84 citing papers in PubMed, 119 citations in OpenAlex.
- ASD: antigen-specific antibody database.mAbs · 2026Article
- Computational design of optimized and preferentially paired human TCR constant regions for improved T cell function.Science advances · 2026Article
- A Review on Applications of Artificial Intelligence (AI) in Monoclonal Antibody (mAb) Manufacturing.Molecules (Basel, Switzerland) · 2026Review
- A Multi-Model Strategy for Optimizing Hepatitis B Virus preS1 Epitope Recognition by the Antibody HzKR127.Current issues in molecular biology · 2026Article
- Multi-objective antibody design and optimization using machine learning.Nature reviews bioengineering · 2026Article
- Selective positive allosteric modulation of βNature communications · 2026Article
- LICHEN enables light-chain immunoglobulin sequence generation conditioned on the heavy chain and experimental needs.Communications biology · 2026Article
- Paraplume: A fast and accurate antibody paratope prediction method provides insights into repertoire-scale binding dynamics.PLoS computational biology · 2026Article
- Learning the language of protein-protein interactions.Nature communications · 2026Article
- ImmunoMatch learns and predicts cognate pairing of heavy and light immunoglobulin chains.Nature methods · 2026Article
- Exploring the Blueprint of Life: The Innovation in Antibody and Protein Design.Combinatorial chemistry & high throughput screening · 2026Article
- Dual-module aCAR-iCAR NK cells for solid tumors: cascade resistance mechanisms, AI-driven engineering, and precision stratification.Frontiers in immunology · 2026Review
- Structure-Guided Engineering of High-Affinity Antibodies Against Zika Virus Using Deep Learning and Molecular Dynamics.Chemistry & biodiversity · 2026Article
- Fitness Landscape for Antibodies 2: Benchmarking Reveals That Protein AI Models Cannot Yet Consistently Predict Developability Properties.bioRxiv : the preprint server for biology · 2025Article
- AbAgym: a well-curated dataset for the mutational analysis of antibody-antigen complexes.mAbs · 2025Article
- Article
- 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
- Advances in Techniques for the Structure and Functional Optimization of Therapeutic Monoclonal Antibodies.Biomedicines · 2025Review
- Evolutionary paths that link orthogonal pairs of binding proteins.Cell systems · 2025Article
- Revolutionizing oncology: the role of Artificial Intelligence (AI) as an antibody design, and optimization tools.Biomarker research · 2025Review
24 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issued
Authors and funding
14 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Antibodies developed for research and clinical applications may exhibit suboptimal stability, expressibility, or affinity. Existing optimization strategies focus on surface mutations, whereas natural affinity maturation also introduces mutations in the antibody core, simultaneously improving stability and affinity. To systematically map the mutational tolerance of an antibody variable fragment (Fv), we performed yeast display and applied deep mutational scanning to an anti-lysozyme antibody and found that many of the affinity-enhancing mutations clustered at the variable light-heavy chain interface, within the antibody core. Rosetta design combined enhancing mutations, yielding a variant with tenfold higher affinity and substantially improved stability. To make this approach broadly accessible, we developed AbLIFT, an automated web server that designs multipoint core mutations to improve contacts between specific Fv light and heavy chains (http://AbLIFT.weizmann.ac.il). We applied AbLIFT to two unrelated antibodies targeting the human antigens VEGF and QSOX1. Strikingly, the designs improved stability, affinity, and expression yields. The results provide proof-of-principle for bypassing laborious cycles of antibody engineering through automated computational affinity and stability design.
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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.