ArticleMethods in enzymology2013
Flexible backbone sampling methods to model and design protein alternative conformations.
Article in Methods in enzymology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Protein Catalysis Through Structural Dynamics: A Comprehensive Analysis of Energy Conversion in Enzymatic Systems and Its Computational Limitations.Pharmaceuticals (Basel, Switzerland) · 2025Review
- De novo design of four-helix bundle proteins to bind metalloporphyrin cofactors.Methods in enzymology · 2025Article
- Review
- Sampling alternative conformational states of transporters and receptors with AlphaFold2.eLife · 2022Article
- IsAb: a computational protocol for antibody design.Briefings in bioinformatics · 2021Article
- A Minireview on Temperature Dependent Protein Conformational Sampling.The protein journal · 2021Review
- Structural Characterization of Receptor-Receptor Interactions in the Allosteric Modulation of G Protein-Coupled Receptor (GPCR) Dimers.International journal of molecular sciences · 2021Review
- New computational protein design methods for de novo small molecule binding sites.PLoS computational biology · 2020Article
- Expanding the space of protein geometries by computational design of de novo fold families.Science (New York, N.Y.) · 2020Article
- FASPR: an open-source tool for fast and accurate protein side-chain packing.Bioinformatics (Oxford, England) · 2020Article
- Comparison of Rosetta flexible-backbone computational protein design methods on binding interactions.Proteins · 2020Article
- Incorporating an allosteric regulatory site in an antibody through backbone design.Protein science : a publication of the Protein Society · 2017Article
- An Evolution-Based Approach to De Novo Protein Design.Methods in molecular biology (Clifton, N.J.) · 2017Article
- Synthetic beta-solenoid proteins with the fragment-free computational design of a beta-hairpin extension.Proceedings of the National Academy of Sciences of the United States of America · 2016Article
- Why reinvent the wheel? Building new proteins based on ready-made parts.Protein science : a publication of the Protein Society · 2016Review
- Mapping the conformational landscape of a dynamic enzyme by multitemperature and XFEL crystallography.eLife · 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
- A Web Resource for Standardized Benchmark Datasets, Metrics, and Rosetta Protocols for Macromolecular Modeling and Design.PloS one · 2015Article
- Coupling Protein Side-Chain and Backbone Flexibility Improves the Re-design of Protein-Ligand Specificity.PLoS computational biology · 2015Article
- Achievements and challenges in structural bioinformatics and computational biophysics.Bioinformatics (Oxford, England) · 2015Article
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4 authors.
Funding
Abstract
Sampling alternative conformations is key to understanding how proteins work and engineering them for new functions. However, accurately characterizing and modeling protein conformational ensembles remain experimentally and computationally challenging. These challenges must be met before protein conformational heterogeneity can be exploited in protein engineering and design. Here, as a stepping stone, we describe methods to detect alternative conformations in proteins and strategies to model these near-native conformational changes based on backrub-type Monte Carlo moves in Rosetta. We illustrate how Rosetta simulations that apply backrub moves improve modeling of point mutant side-chain conformations, native side-chain conformational heterogeneity, functional conformational changes, tolerated sequence space, protein interaction specificity, and amino acid covariation across protein-protein interfaces. We include relevant Rosetta command lines and RosettaScripts to encourage the application of these types of simulations to other systems. Our work highlights that critical scoring and sampling improvements will be necessary to approximate conformational landscapes. Challenges for the future development of these methods include modeling conformational changes that propagate away from designed mutation sites and modulating backbone flexibility to predictively design functionally important conformational heterogeneity.
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