ArticleNature communications2024
Simultaneous enhancement of multiple functional properties using evolution-informed protein design.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Evolutionary Adaptability Coupled with Computation-Driven Engineering for Thermostability Enhancement of a Deoxynivalenol-Detoxifying Fusion Enzyme.International journal of molecular sciences · 2026Article
- Enhancing Enzyme Activity With Mutation Combinations Guided by Few-Shot Learning and Causal Inference.Angewandte Chemie (International ed. in English) · 2026Article
- FireProtASR 2.0: evolution-guided Design of Protein Ancestors and Successors with phylogenetics and machine learning.Briefings in bioinformatics · 2026Article
- Engineering and Application of a Thermostable MHETase for PET Depolymerization.ACS sustainable chemistry & engineering · 2026Article
- PyTEA-O: a Python implementation of Two-Entropies Analysis for protein sequence variation analysis.Bioinformatics (Oxford, England) · 2026Article
- Machine learning enables efficient and effective affinity maturation of nanobodies.bioRxiv : the preprint server for biology · 2026Article
- Computational Methods to Engineer Cas Proteins for Efficient Genome Editing.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Structural comparison of substrate-binding pockets of serine β-lactamases in classes A, C, and D.Journal of enzyme inhibition and medicinal chemistry · 2025Review
- Enhancing functional proteins through multimodal inverse folding with ABACUS-T.Nature communications · 2025Article
- A protein dynamics-based deep learning model enhances predictions of fitness and epistasis.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Directed evolution of hydrocarbon-producing enzymes.Biotechnology for biofuels and bioproducts · 2025Review
- Hydrogel particle-based protein display enabled by particle-templated emulsification.RSC advances · 2025Article
- Simultaneous enhancement of multiple functional properties using evolution-informed protein design.Nature communications · 2024Article
- Rheostats, toggles, and neutrals, Oh my! A new framework for understanding how amino acid changes modulate protein function.The Journal of biological chemistry · 2024Review
- Machine learning for functional protein design.Nature biotechnology · 2024Review
- Is Novelty Predictable?Cold Spring Harbor perspectives in biology · 2024Review
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17 authors.
Funding
Abstract
A major challenge in protein design is to augment existing functional proteins with multiple property enhancements. Altering several properties likely necessitates numerous primary sequence changes, and novel methods are needed to accurately predict combinations of mutations that maintain or enhance function. Models of sequence co-variation (e.g., EVcouplings), which leverage extensive information about various protein properties and activities from homologous protein sequences, have proven effective for many applications including structure determination and mutation effect prediction. We apply EVcouplings to computationally design variants of the model protein TEM-1 β-lactamase. Nearly all the 14 experimentally characterized designs were functional, including one with 84 mutations from the nearest natural homolog. The designs also had large increases in thermostability, increased activity on multiple substrates, and nearly identical structure to the wild type enzyme. This study highlights the efficacy of evolutionary models in guiding large sequence alterations to generate functional diversity for protein design applications.
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