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PSICalc: a novel approach to identifying and ranking critical non-proximal interdependencies within the overall protein structure


AUTHORS

Townsley TDThomas D , Wilson JTJames T , Akers HHarrison , Bryant TTimothy , Cordova SSalvador , Wallace TLT L , Durston KKKirk K , Deweese JEJoseph E . Bioinformatics advances. 2022 8 18; 2(1). vbac058

ABSTRACT

MOTIVATION: AlphaFold has been a major advance in predicting protein structure, but still leaves the problem of determining which sub-molecular components of a protein are essential for it to carry out its function within the cell. Direct coupling analysis predicts two- and three-amino acid contacts, but there may be essential interdependencies that are not proximal within the 3D structure. The problem to be addressed is to design a computational method that locates and ranks essential non-proximal interdependencies within a protein involving five or more amino acids, using large, multiple sequence alignments (MSAs) for both globular and intrinsically unstructured proteins.

RESULTS: We developed PSICalc (Protein Subdomain Interdependency Calculator), a laptop-friendly, pattern-discovery, bioinformatics software tool that analyzes large MSAs for both structured and unstructured proteins, locates both proximal and non-proximal inter-dependent sites, and clusters them into pairwise (second order), third-order and higher-order clusters using a k-modes approach, and provides ranked results within minutes. To aid in visualizing these interdependencies, we developed a graphical user interface that displays these subdomain relationships as a polytree graph. To demonstrate, we provide examples of both proximal and non-proximal interdependencies documented for eukaryotic topoisomerase II including between the unstructured C-terminal domain and the N-terminal domain.

AVAILABILITY AND IMPLEMENTATION: https://github.com/jdeweeselab/psicalc-package.

SUPPLEMENTARY INFORMATION: Supplementary data are available at online.