ArticleJournal of molecular evolution2026
Comparative Analysis of AlphaFold2 Models and Intrinsic Disorder Illuminates Structural Divergence as a Symptom of Functional Divergence Across the Calmodulin Superfamily.
Article in Journal of molecular evolution, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- An Ancestral Mechanism of Calmodulin Binding to Cds1 Kinase Inhibits Catalytic Activity.IUBMB life · 2026Article
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2 authors.
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Abstract
Protein structure enables function. Eukaryotic genomes contain paralogous genes often encoding functionally diverse proteins forming superfamilies. As protein sequences evolve, their function may change but identifying functional divergence from sequence alone is difficult. With AlphaFold2, large-scale evolutionary analyses of protein 3D structures to identify structural divergence as a symptom of functional divergence may be possible. We investigated the structural features of 448 proteins in the calmodulin superfamily that includes many functionally divergent paralogs with conformational heterogeneity. Phylogenetic reconstruction yielded 18 main clades. Across the phylogeny, most residues in the AlphaFold2 models were predicted with high model confidence. Further, conformationally flexible clades were more disordered based on IUPred2A prediction. Clustering based on pairwise similarity of structural properties including 3D structure, and secondary structure and disorder mapped to the alignment context revealed a similar agreement with the sequence-based phylogeny except for the clades with numerous recent gene duplications. Clustering based on model confidence was less similar to the sequence-based phylogeny. Notably, AlphaFold2 frequently modeled functionally similar proteins from the same main clade into highly similar structures while the models differ more between functionally divergent main clades and within clades with extensive gene duplications, which may yield rapidly diverging sequences with unexpected co-evolutionary patterns. These results suggest that by comparing the evolutionary signals from sequence, AlphaFold2 models, and disorder across protein families, we can expand our perspective on protein structure evolution including identifying functional divergence.
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