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

Abstract

This research proposes a 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 the weighted parameter; the distribution is tending to symmetry  thus making the W-HND accurate in modelling both heavily tailed and lightly tailed data.  The W-HND is fitted to the data obtained via molecular dynamics simulation, in which two drug candidates (Ligands) called Streptomycin and Abacavir were subjected to molecular docking (in-silico study); their binding effect on HIV protein receptors was studied, and the mean binding affinity for Streptomycin (6.61708 kcal/mol) shows a great binding effect as compared to Abacavir (6.246396 kcal/mol). 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