ArticleJournal of the American Chemical Society2024
Improving Protein Expression, Stability, and Function with ProteinMPNN.
Article in Journal of the American Chemical Society, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 142 papers.
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Who cites it
142 citing papers in PubMed.
- Deep Learning-driven synergistic engineering of PET hydrolase for post-consumer PET depolymerization.Synthetic and systems biotechnology · 2027Article
- Review
- Aligning protein-generative models to experimental fitness with ProteinDPO.Nature methods · 2026Article
- Article
- Integrative machine learning approaches for enzyme kinetic parameter prediction.Briefings in bioinformatics · 2026Review
- Towards routine accurate electron-density studies of biological macromolecules.Acta crystallographica. Section D, Structural biology · 2026Article
- Toward Rational Design of Precision-Fermented Milk Proteins: Integrating Cross-Species Selection, Post-Translational Modification, and AI Optimization.Comprehensive reviews in food science and food safety · 2026Review
- Soluble protein analog selection engine (SPASE): An automated AI-powered server to improve protein engineering workflows.Protein science : a publication of the Protein Society · 2026Article
- Enhancing Enzyme Activity With Mutation Combinations Guided by Few-Shot Learning and Causal Inference.Angewandte Chemie (International ed. in English) · 2026Article
- Accelerating protein design by scaling experimental characterization.Nature communications · 2026Article
- Automated synthetic cell-based screening for designed proteins with emergent functions.Nature communications · 2026Article
- Improving expression of Photobacterium sp. JT-ISH-224 α2,6-sialyltransferase using ProteinMPNN and machine learning guided combinatory mutagenesis.Biotechnology letters · 2026Article
- Structure and evolution-guided design of minimal RNA-guided nucleases.Science (New York, N.Y.) · 2026Article
- Towards Cost-Effective and Sustainable Media Formulations for Terrestrial and Aquatic Cellular Agriculture.Foods (Basel, Switzerland) · 2026Review
- Beyond native sequence recovery: Improved modeling of the sequence-energy landscape of protein structures.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- PolyProline Predictor: A web server for empirical sequence-based prediction of polyproline II helices.Protein science : a publication of the Protein Society · 2026Article
- Reclone: a global research community building equitable access to reagents.Nature methods · 2026Article
- Targeting the Undruggable: Deep Learning-Driven Design of Peptide Therapeutics in Cancer.Pharmaceuticals (Basel, Switzerland) · 2026Review
- Benchmarking Generative AI Protein Models Reveals Differences Between Structural and Sequence-based Approaches.Genomics, proteomics & bioinformatics · 2026Article
- Overestimating zero-shot fitness prediction: Broad benchmarks mask local failures and practical limitations.bioRxiv : the preprint server for biology · 2026Article
82 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
16 authors.
Funding
Abstract
Natural proteins are highly optimized for function but are often difficult to produce at a scale suitable for biotechnological applications due to poor expression in heterologous systems, limited solubility, and sensitivity to temperature. Thus, a general method that improves the physical properties of native proteins while maintaining function could have wide utility for protein-based technologies. Here, we show that the deep neural network ProteinMPNN, together with evolutionary and structural information, provides a route to increasing protein expression, stability, and function. For both myoglobin and tobacco etch virus (TEV) protease, we generated designs with improved expression, elevated melting temperatures, and improved function. For TEV protease, we identified multiple designs with improved catalytic activity as compared to the parent sequence and previously reported TEV variants. Our approach should be broadly useful for improving the expression, stability, and function of biotechnologically important proteins.
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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.