In-Silico Studies and Property Model to Investigate The Binding Effect of Selected Ligands on HIV Integrase

Abstract

This research proposes new Weighted Halfnormal Distributuion (W-HND); the model is built by using the weighting function to add the weighted parameter to the classical Halfnormal distribution. The W-HND has been characterized with heavily tail and leptokurtic, with increasing value of weighted parameter; distribution is tending to symmetry thus making the W-HND accurate in modeling both heavily tailed and lightly tailed data. The W-HND is fitted to the data obtained via molecular dynamics simulation in which two drug candidate (Ligands) called Streptomycin and Abacavir were subjected to molecular docking (in-silico study); their binding effect on HIV protein receptor was studied and the mean binding affinity for Streptomycin (6.61708 kcal/mol) shows great binding effect as compared to Abacavir (6.246396 kcal/mol). The performance criteria such as Akaike information (AIC) and Bayesian information criteria (BIC) were used as established standard for selecting best performing model; in this case, WHND performs efficiently as compared to Lognormal and Weibull Model