In silico design and identification of new peptides for mitigating hIAPP aggregation in type 2 diabetes

Abstract

The aberrant misfolding and self-aggregation of human islet amyloid polypeptide (hIAPP or amylin) into cytotoxic aggregates are implicated in the pathogenesis of type 2 diabetes (T2D). Among various inhibitors, short peptides derived from the amyloidogenic regions of hIAPP have been employed as hIAPP aggregation inhibitors due to their low immunogenicity, biocompatibility, and high chemical diversity. Recently, hIAPP fragment HSSNN18-22 was identified as an amyloidogenic sequence and displayed higher antiproliferative activity to RIN-5F cells. Various hIAPP aggregation inhibitors have been designed by chemical modifications of the highly amyloidogenic sequence (NFGAIL) of hIAPP. In this work, a library of pentapeptides based on fragment HSSNN18-22 was designed and assessed for their efficacy in blocking hIAPP aggregation using an integrated computational screening approach. The binding free energy calculations by molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method identified HSSQN and HSSNQ that bind to hIAPP monomer with a binding affinity of −21.25 ± 4.90 and −19.73 ± 3.10 kcal/mol, respectively, which is notably higher as compared to HSSNN (–11.90 ± 4.12 kcal/mol). The sampling of the non aggregation-prone helical conformation was notably increased from 23.5 ± 3.0 in the hIAPP monomer to 38.1 ± 3.6, and 33.8 ± 3.0% on the incorporation of HSSQN, and HSSNQ, respectively, which indicate reduced aggregation propensity of hIAPP monomer. The pentapeptides, HSSQN and HSSNQ, identified as hIAPP aggregation inhibitors in this work can be further conjugated with various metal chelating peptides to yield more efficacious and clinically relevant multifunctional modulators for targeting various pathological hallmarks of T2D.