A comprehensive in silico exploration of the impacts of missense variants on two different conformations of human pirin protein

Abstract

A total of 153 missense variants of pirin were identified (Additional file 1: Table S1). The pathogenicity of these variants was predicted using five different tools (SIFT, PolyPhen2, PMut, Meta-SNP and Rhapsody). Each tool follows a different algorithm to predict pathogenicity. SIFT uses sequence homology-based approach for classifying a missense variant as either deleterious or tolerated (Sim et al. 2012). PolyPhen-2 classifies an amino acid substitution into probably damaging, possibly damaging, and benign on the basis of sequence, phylogenetic and structural characteristics of the substitution(Adzhubei et al. 2010, 2013). PMut uses neural networks to predict structure and evolutionary properties resulting from change in amino acid sequence (López-Ferrando et al. 2017). Rhapsody utilizes sequence coevolution data along with structure- and dynamics-based methods to predict pathogenicity of target variants (Ponzoni et al. 2020).