ArticleJournal of the American Chemical Society2023
High-Accuracy Prediction of Stabilizing Surface Mutations to the Three-Helix Bundle, UBA(1), with EmCAST.
Article in Journal of the American Chemical Society, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed, 2 citations in OpenAlex.
- Novel Prion Protein Gene (bioRxiv : the preprint server for biology · 2026Article
- Identification and initial characterization of novel prion protein gene (Frontiers in veterinary science · 2026Article
- Computational Enzyme Redesign Enhances Tolerance to Denaturants for Peptide C-Terminal Amidation.JACS Au · 2024Article
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6 authors at 1 institution in 1 country.
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Abstract
The accurate modeling of energetic contributions to protein structure is a fundamental challenge in computational approaches to protein analysis and design. We describe a general computational method, EmCAST (empirical Cα stabilization), to score and optimize the sequence to the structure in proteins. The method relies on an empirical potential derived from the database of the Cα dihedral angle preferences for all possible four-residue sequences, using the data available in the Protein Data Bank. Our method produces stability predictions that naturally correlate one-to-one with the experimental results for solvent-exposed mutation sites. EmCAST predicted four mutations that increased the stability of a three-helix bundle, UBA(1), from 2.4 to 4.8 kcal/mol by optimizing residues in both helices and turns. For a set of eight variants, the predicted and experimental stabilizations correlate very well (
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