ArticlePLoS computational biology2016
Evolution-Based Functional Decomposition of Proteins.
Article in PLoS computational biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 86 papers.
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Who cites it
86 citing papers in PubMed.
- The ecological context of enzymatic variation.bioRxiv : the preprint server for biology · 2026Article
- Protein Surface Site Determines the Evolutionary Accessibility of Allosteric Regulation.bioRxiv : the preprint server for biology · 2026Article
- Determinants of metal import and specificity in a bacterial transporter.bioRxiv : the preprint server for biology · 2026Article
- Functional bottlenecks can emerge from non-epistatic underlying traits.PLoS computational biology · 2026Article
- Restoration of the Y220C p53 Full-Length Mutant by PK11000: a Molecular Dynamics Study of an Intrinsically Disordered Protein.ACS omega · 2026Article
- Computational design of class II MHC binding peptide with sequence-based evolution information.Bioinformatics advances · 2026Article
- Unexplored regions of the protein sequence-structure map revealed at scale by a library of foldtuned language models.bioRxiv : the preprint server for biology · 2025Article
- Widespread epistasis shapes RNA polymerase II active site function and evolution.Nature communications · 2025Article
- Considering Metabolic Context in Enzyme Evolution and Design.Biochemistry · 2025Review
- MD Multi-Sector Selector: Recursive Extraction and Refinement of Molecular Dynamics Based Sectors Yields Two Sectors in p53 Tumor Suppressor Protein.The journal of physical chemistry. B · 2025Article
- Coevolving residues distant from the ligand binding site are involved in GAF domain function.Communications chemistry · 2025Article
- Disrupting the network of co-evolving amino terminal domain residues relieves mitochondrial calcium uptake inhibition by MCUb.Computational and structural biotechnology journal · 2025Article
- AlloViz: A tool for the calculation and visualisation of protein allosteric communication networks.Computational and structural biotechnology journal · 2024Article
- Statistical Coupling Analysis Predicts Correlated Motions in Dihydrofolate Reductase.The journal of physical chemistry. B · 2024Article
- Emergent time scales of epistasis in protein evolution.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Clustering protein functional families at large scale with hierarchical approaches.Protein science : a publication of the Protein Society · 2024Article
- Impact of phylogeny on the inference of functional sectors from protein sequence data.PLoS computational biology · 2024Article
- Deep-learning-based design of synthetic orthologs of SH3 signaling domains.Cell systems · 2024Article
- Ancestral Reconstruction and the Evolution of Protein Energy Landscapes.Annual review of biophysics · 2024Review
- Simultaneous enhancement of multiple functional properties using evolution-informed protein design.Nature communications · 2024Article
26 more citing papers are in PubMed but not listed here.
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3 authors.
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Abstract
The essential biological properties of proteins-folding, biochemical activities, and the capacity to adapt-arise from the global pattern of interactions between amino acid residues. The statistical coupling analysis (SCA) is an approach to defining this pattern that involves the study of amino acid coevolution in an ensemble of sequences comprising a protein family. This approach indicates a functional architecture within proteins in which the basic units are coupled networks of amino acids termed sectors. This evolution-based decomposition has potential for new understandings of the structural basis for protein function. To facilitate its usage, we present here the principles and practice of the SCA and introduce new methods for sector analysis in a python-based software package (pySCA). We show that the pattern of amino acid interactions within sectors is linked to the divergence of functional lineages in a multiple sequence alignment-a model for how sector properties might be differentially tuned in members of a protein family. This work provides new tools for studying proteins and for generally testing the concept of sectors as the principal units of function and adaptive variation.
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