Circuit topology predicts pathogenicity of missense mutations

Abstract

The contact topology of a protein determines important aspects of the folding process. The topological measure of contact order has been shown to be predictive of the rate of folding. Circuit topology is emerging as another fundamental descriptor of biomolecular structure, with predicted effects on the folding rate. We analyze the residue-based circuit topological environments of 21 K mutations labeled as pathogenic or benign. Multiple statistical lines of reasoning support the conclusion that the number of contacts in two specific circuit topological arrangements, namely inverse parallel and cross relations, with contacts involving the mutated residue have discriminatory value in determining the pathogenicity of human variants. We investigate how results vary with residue type and according to whether the gene is essential.We further explore the relationship to a number of structural features and find that circuit topology provides nonredundant information on protein structures and pathogenicity of mutations. Results may have implications for the polymer physics of protein folding and suggest that "local" topological information, including residue-based circuit topology and residue contact order, could be useful in improving state-of-theart machine learning algorithms for pathogenicity prediction.

ProteinCT: An implementation of the protein circuit topology framework

“…One can quickly notice the significant number of cross contacts related to only 1 residue site within the protein, a significant chunk of all contacts within the protein system can be seen as cross contacts related to the ones stemming from residue 36. A large number of contacts in cross was seen to be indicative on average of pathogenicity upon mutation [17] .

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“…Local circuit topology can be used to seek out any differences between mutated variants of certain residues and their respective contacts within proteins. It is speculated that differences in local topology of various mutants of the same protein can reflect the nature of polymer folding in the biological environment [17] . To demonstrate this functionality within the ProteinCT tool, an example analysis was done using the bovine phospotransferase (PDB code: 1PNJ).…”

“…CT thus confers an inherent advantage in estimating folding rates and number of unfolding paths of a folded linear macromolecule [12] , [15] , [16] . Finally, recent evidence shows that circuit topology can predict pathogenicity of missense mutations, which often alter the folding stability of a protein, in addition to other properties such as aggregation propensity, binding affinity to other proteins and/or ligands, catalysis, and dynamic aspects relevant to protein function [17] .

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Intelligent Protein Design and Molecular Characterization Techniques: A Comprehensive Review

“…Circuit topology is a newly proposed descriptor that theoretically assesses the relationship between contact pairs on the protein backbone and provides information about the protein structure (such as the order of residues and residue contacts). The use of circuit topology to predict the folding rate of proteins has improved pathogenicity prediction of missense mutations [184].…”

Circuit Topology Approach for the Comparative Analysis of Intrinsically Disordered Proteins

“…Recently, topology of unknotted protein chains has been defined based on the arrangement of loops or the associated intrachain contacts. This approach, called circuit topology (CT), − has been applied to stable folded proteins for various applications, , and has proven to be effective for modeling polymer folding reactions . CT is a very simple yet effective framework for the characterization of the arrangement of interchain (residue–residue) contacts in a folded molecule.…”