ArticleProceedings of the National Academy of Sciences of the United States of America2010
Experimental library screening demonstrates the successful application of computational protein design to large structural ensembles.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
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Who cites it
31 citing papers in PubMed.
- Generative AI for controllable protein sequence design: A survey.npj drug discovery · 2026Review
- Customizing the structure of minimal TIM barrels to craft efficient de novo enzymes.Nature chemical biology · 2026Article
- Mapping functional dynamics hotspots for protein engineering with NMR peak intensity analysis.Protein engineering, design & selection : PEDS · 2026Article
- Engineering of T7 DNA-dependent RNA polymerase with activity at elevated temperature.PloS one · 2026Article
- Robust genome and cell engineering via in vitro and in situ circularized RNAs.Nature biomedical engineering · 2025Article
- Design of efficient artificial enzymes using crystallographically-enhanced conformational sampling.bioRxiv : the preprint server for biology · 2023Article
- Computational remodeling of an enzyme conformational landscape for altered substrate selectivity.Nature communications · 2023Article
- Recent advances in user-friendly computational tools to engineer protein function.Briefings in bioinformatics · 2021Review
- Protein stability engineering insights revealed by domain-wide comprehensive mutagenesis.Proceedings of the National Academy of Sciences of the United States of America · 2019Article
- Integrating linear optimization with structural modeling to increase HIV neutralization breadth.PLoS computational biology · 2018Article
- Rational design of proteins that exchange on functional timescales.Nature chemical biology · 2017Article
- Rosetta:MSF: a modular framework for multi-state computational protein design.PLoS computational biology · 2017Article
- Enriching Peptide Libraries for Binding Affinity and Specificity Through Computationally Directed Library Design.Methods in molecular biology (Clifton, N.J.) · 2017Article
- Computationally Designed Bispecific Antibodies using Negative State Repertoires.Structure (London, England : 1993) · 2016Article
- Design of Protein Multi-specificity Using an Independent Sequence Search Reduces the Barrier to Low Energy Sequences.PLoS computational biology · 2015Article
- Optimization of rotamers prior to template minimization improves stability predictions made by computational protein design.Protein science : a publication of the Protein Society · 2015Article
- SwiftLib: rapid degenerate-codon-library optimization through dynamic programming.Nucleic acids research · 2015Article
- Computational Design of the β-Sheet Surface of a Red Fluorescent Protein Allows Control of Protein Oligomerization.PloS one · 2015Article
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3 authors.
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Abstract
The stability, activity, and solubility of a protein sequence are determined by a delicate balance of molecular interactions in a variety of conformational states. Even so, most computational protein design methods model sequences in the context of a single native conformation. Simulations that model the native state as an ensemble have been mostly neglected due to the lack of sufficiently powerful optimization algorithms for multistate design. Here, we have applied our multistate design algorithm to study the potential utility of various forms of input structural data for design. To facilitate a more thorough analysis, we developed new methods for the design and high-throughput stability determination of combinatorial mutation libraries based on protein design calculations. The application of these methods to the core design of a small model system produced many variants with improved thermodynamic stability and showed that multistate design methods can be readily applied to large structural ensembles. We found that exhaustive screening of our designed libraries helped to clarify several sources of simulation error that would have otherwise been difficult to ascertain. Interestingly, the lack of correlation between our simulated and experimentally measured stability values shows clearly that a design procedure need not reproduce experimental data exactly to achieve success. This surprising result suggests potentially fruitful directions for the improvement of computational protein design technology.
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