Computer-aided peptide-based drug design for inositol-requiring enzyme 1

Abstract

Inositol-requiring enzyme 1 (IRE1), an endoplasmic reticulum (ER) transmembrane protein with both kinase and endoribonuclease activities, plays an essential role during ER stress and its subsequent unfolded protein response (UPR). Recent evidence shows IRE1 signaling contributes to tumorigenesis and cancer progression, pointing to the therapeutic importance of this conserved arm of the UPR. Here, we employed different computational tools to design and predict short peptides with the capability of disrupting IRE1 dimerization/oligomerization, as a strategy for inhibiting its Kinase and RNase activities. A mutation-based peptide library was constructed using mCSM-PPI2 and OSPREY 3.0. The molecular interaction analyses between the designed peptides and IRE1 protein were conducted using the HADDOCK 2.2 online server, followed with molecular dynamics analysis by the GROMACS 2020 package. We then selected short peptide candidates that exhibited high affinity and best predicted physicochemical properties in complex with IRE1. Finally, online servers, such as ToxinPred and AllerTop, were used to identify the best peptide candidates that showed no significant allergenic or cytotoxic properties. These rational designed peptides with the capability of binding to IRE1 oligomerization domain can be considered as potential drug candidates for disrupting IRE1 activity in cancer and related diseases, pending for further validation by in silico and experimental studies.