ArticleProceedings of the National Academy of Sciences of the United States of America2017
Computationally optimized deimmunization libraries yield highly mutated enzymes with low immunogenicity and enhanced activity.
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 18 papers.
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Who cites it
18 citing papers in PubMed.
- Rational Immunogenicity Modulation of Virus-Like Particles by VLPIM.Computational and structural biotechnology journal · 2026Article
- Machine learning for functional protein design.Nature biotechnology · 2024Review
- Functional Deimmunization of Botulinum Neurotoxin Protease Domain via Computationally Driven Library Design and Ultrahigh-Throughput Screening.ACS synthetic biology · 2023Article
- Complementation Dependent Enzyme Prodrug Therapy Enables Targeted Activation of Prodrug on HER2-Positive Cancer Cells.ACS medicinal chemistry letters · 2022Article
- Resistor: An algorithm for predicting resistance mutations via Pareto optimization over multistate protein design and mutational signatures.Cell systems · 2022Article
- Co-optimization of therapeutic antibody affinity and specificity using machine learning models that generalize to novel mutational space.Nature communications · 2022Article
- MHCEpitopeEnergy, a Flexible Rosetta-Based Biotherapeutic Deimmunization Platform.Journal of chemical information and modeling · 2021Article
- Deimmunization of protein therapeutics - Recent advances in experimental and computational epitope prediction and deletion.Computational and structural biotechnology journal · 2021Review
- Globally deimmunized lysostaphin evades human immune surveillance and enables highly efficacious repeat dosing.Science advances · 2020Article
- A High-Throughput Single-Clone Phage Fluorescence Microwell Immunoassay and Laser-Driven Clonal Retrieval System.Biomolecules · 2020Article
- Advances in protein structure prediction and design.Nature reviews. Molecular cell biology · 2019Review
- Mitigation of T-cell dependent immunogenicity by reengineering factor VIIa analogue.Blood advances · 2019Article
- Balancing sensitivity and specificity in distinguishing TCR groups by CDR sequence similarity.BMC bioinformatics · 2019Article
- Multifunctional CRISPR-Cas9 with engineered immunosilenced human T cell epitopes.Nature communications · 2019Article
- ImmunomeBrowser: a tool to aggregate and visualize complex and heterogeneous epitopes in reference proteins.Bioinformatics (Oxford, England) · 2018Article
- Peptide design by optimization on a data-parameterized protein interaction landscape.Proceedings of the National Academy of Sciences of the United States of America · 2018Article
- Review
- Pareto Optimization of Combinatorial Mutagenesis Libraries.IEEE/ACM transactions on computational biology and bioinformaticsArticle
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Authors and funding
7 authors.
Funding
Abstract
Therapeutic proteins of wide-ranging function hold great promise for treating disease, but immune surveillance of these macromolecules can drive an antidrug immune response that compromises efficacy and even undermines safety. To eliminate widespread T-cell epitopes in any biotherapeutic and thereby mitigate this key source of detrimental immune recognition, we developed a Pareto optimal deimmunization library design algorithm that optimizes protein libraries to account for the simultaneous effects of combinations of mutations on both molecular function and epitope content. Active variants identified by high-throughput screening are thus inherently likely to be deimmunized. Functional screening of an optimized 10-site library (1,536 variants) of P99 β-lactamase (P99βL), a component of ADEPT cancer therapies, revealed that the population possessed high overall fitness, and comprehensive analysis of peptide-MHC II immunoreactivity showed the population possessed lower average immunogenic potential than the wild-type enzyme. Although similar functional screening of an optimized 30-site library (2.15 × 10
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