Mapping the Structural Topology of IRS Family Cascades Through Computational Biology

Abstract

Structural topologies of proteins play significant roles in analyzing their biological functions. Converting the amino acid data in a protein sequence into structural information to outline the function of a protein is a major challenge in post-genome research which can add an extra room in understanding the protein sequence-structure-function relationships. In this study, we performed a comprehensive bioinformatics analysis of structural topology of the IRS family members such as IRS-1, IRS-2, IRS-3, IRS-4, IRS-5 and IRS-6. Based on this assessment, we found that IRS-2 encloses the highest number of α helices, β sheets and β turns in the secondary structure topology compared to IRS-1 and IRS-6. IRS family members are rich in serine or leucine residues. Among the IRS family members, the highest percentage of serine and leucine was observed in IRS-1 (15%) and IRS-5 (10%), respectively. Notably, the highest number of disulphide bonds was observed in IRS-1 (10) which is responsible for structural stability of the protein. Hydrogen bond pattern in α helices and β sheet was recorded in IRS-1, IRS-2 and IRS-6. By conservation analysis, the longest protein IRS-3 was found to be highly conserved among the IRS family members. The cluster of sequence logo present in the N terminus of these cascades was noted, and highly conserved residues in N-terminal region help in the formation of the two highly conserved domains such as PH domain and PTB domain. Results generated from this analysis will be more beneficial to researchers in understanding more about insulin signalling mechanism(s) as well as insulin resistance pathway. We discuss here that bioinformatics tools utilized in this study can play a vital role in addressing the complexity of structural topology to understand structure-function relationships in insulin signalling cascades.