In silico Prediction of Pyrazoline Derivatives as Antimalarial agents

Abstract

Malaria is one of the toughest health and development challenges faced by tropical countries. The resistance of malarial parasite to available drugs and currently used chemotherapy made its emergence for development of new drugs. Pyrazoline derivatives have shown good antimalarial activity. In present work, our objective is to explore pyrazoline derivatives with in silico methods for their antimalarial activity. A five-point pharmacophore was developed using 80 molecules having logIC50 ranging from 10.39 to 6.72. The pharmacophore yielded a statistically significant 3D-QSAR model with a high correlation coefficient R2= 0.806772, cross validation coefficient Q2= 0.7154 at four component PLS factor. To evaluate the effectiveness of docking protocol, we have selected crystallographic bound compound to validate our docking procedure. Protein selected for our studies with PDB id is 2BMA having resolution 2.7 Å. Further similar orientations were observed between the superpositions of 80 compounds after pharmacophore and 3D-QSAR poses, pharmacophore and XP docking poses, 3D-QSAR and XP docking poses. These present studies will provide insight in designing novel molecules with better antimalarial activity. Results explained that two aromatic rings and two hydrophobic groups are important for the antimalarial activity. The docking studies of all selected inhibitors in the active site of 2BMA showed crucial hydrogen bond interactions with HIS95, SER97, GLN323, ARG93, ALA321, ALA346, ILE166, ILE102 and PRO96 amino acid residues.