Exploring a Computational Method for Evaluating the Epinecidin‑1 and Its Variants Binding Efficacy with Breast Cancer Receptor (HER‑2)

Abstract

Host defense peptides are short oligopeptides, which function as the first line of defense mechanism in the host organisms against various microbial infections. Despite their antimicrobial and anti-inflammatory activity, they also exhibit anticancer activity. Harnessing this property and using in silico tools, we iterated alanine, cysteine and lysine residues of a host defense peptide Epinecidin-1(Epi-1). Strong binding to the breast cancer receptor, HER-2 was set as the bait criteria and the affinities were compared to the FDA recommended commercial drugs such as Abemaciclib, Alpelisib, Everolimus, Exemestane and Paclitaxel. Doing so, we found that some of the iterated variants had obtained binding affinity values higher or equivalent to the commercial drugs. In the present study, out of the 60 created Epi-1 variants, 3 variants have strong affinity to the HER2 receptor. The variants alanine 9, cysteine 16 and lysine 1 have 10, 8 and 10 interactions respectively with the HER2 receptor. Moreover, alanine 9 has the closest binding distance (2.05872 Å) with the HER2 receptor among all other counterparts. The present finding is unequivocal evidence that these variants of Epi-1 peptides have a high binding affinity near to commercial chemotherapeutics. Thus, short peptides engineered for therapeutic application using the knowledge of computational biology is one of the best ways to find an alternative for anticancer chemotherapeutics. Designing molecules via this computational methodology will save time and resources for the new drug development in the pharmaceutical industry.