QSAR modeling, docking and insilico ADMET studies of lanosterol synthase inhibitors

Abstract

Lanosterol Synthase is an attractive target for antihypercholesterolemeic drug design. A set of 26 molecules having lanosterol synthase inhibitory activity was used for pharmacophoric hypothesis and atom based QSAR analysis. Inhibitory concentrations (pIC50) of these compounds were ranged from 7.452 to 8.721. Pharmacophoric hypothesis AAHPR.174 had the best survival score of 3.560. On the basis of the best hypothesis AAHPR.174, atom based 3D-QSAR validation was carried out using PLS factor, with 20 compounds in training set and 6 compounds in test set. From the regression analysis, a highly predictive and statistically significant model was generated having the co-efficient of determination (R2 = 0.9934), cross validated co-efficient (q2 = 0.8083), Pearson correlation co-efficient = 0.9345 and variance ratio (F = 561.9). The QSAR model indicated that hydrogen bond acceptor, aromatic, hydrophobic and positively charged groups play an important role in LSS inhibitor activities. This pharmacophoric hypothesis was used to screen ligands from Asinex database. On the basis of fitness score and docking interactions, novel ligands were selected. Insilico ADME/Toxicity predictions were analyzed to understand the lanosterol synthase inhibitor activity of these compounds and that may help in the future development of drug candidate with fewer side effects.