ArticleNature chemical biology2026
Protein stability is determined by single-site bias rather than pairwise covariance.
Article in Nature chemical biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Protein engineering: status report.Protein engineering, design & selection : PEDS · 2026Review
- Residue conservation and solvent accessibility are (almost) all you need for predicting mutational effects in proteins.Bioinformatics (Oxford, England) · 2025Article
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5 authors.
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Abstract
The biases revealed in protein sequence alignments have been shown to provide information related to protein structure, stability and function. Recent studies using Potts models show that single-site biases and pair correlations can improve predictions of protein fitness, activity and stability compared to simpler models. Here we use a Potts model to design groups of protein sequences with different amounts of single-site biases and pair correlations and determine the stabilities of sequences from each group. Surprisingly, sequences excluding pair correlations maximize stability compared to sequences that maximize pair correlations, suggesting that pair correlations contribute to other aspects of protein fitness. Consistent with this interpretation, we find that for three enzyme families, activity is greatly increased by maximizing pair correlations. The finding that elimination of covariant residue pairs increases protein stability suggests a route to enhance stability of designed proteins, although this stability may be offset by reduced enzyme activity.
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