Cluster Analysis and QSAR Study of Some Anti‐hepatitis B Virus Agents Comprising 4‐Aryl‐6‐chloro‐quinolin‐2‐ones and 5‐Aryl‐7‐chloro‐1,4‐benzodiazepines

Abstract

Chronic hepatitis B virus (HBV) infection has caused a global health crisis by infecting more than 400 million people, constituting the ninth leading cause of death in the world. There is an urgent demand for antiviral agents to effectively inhibit HBV infection based on the development of drug resistance and increasing infected numbers. Quantitative structure-activity relationship (QSAR) models were developed for a series of potent anti-hepatitis B virus agents comprising 4-aryl-6-chloro-quinolin-2-ones and 5-aryl-7-chloro-1,4-benzodiazepines using Cerius r ＝0.989) constructed by the genetic function approximation (GFA) methodology indicates that the activity was mainly governed by E-State-keys (S_sssN and S_sCl), electronic descriptor (LUMO), thermodynamic descriptor (Foct) and conformational descriptor (Energy). 3D-QSAR models were developed based on steric and electrostatic interactions by molecular field analysis (MFA) to investigate the substitutional requirements for the favorable receptor-drug interaction, showing that electrostatic interactions is crucial for the activity. The models derived can provide a preliminary valuable guidance for continuing search for novel potent anti-hepatitis B virus agents prior to synthesis.

Computational Studies and Molecular Dynamic Simulation to Design Lead Compounds for Hepatitis B Virus

“…[4][5][6] Cluster Analysis and QSAR Study of Some Anti-hepatitis B Virus Agents Comprising 4-Aryl-6-chloro-quinolin-2-ones and 5-Aryl-7-chloro-1, 4-benzodiazepines. 7 Sheng Liu et al created the docking and synthesis design of phenylpropanoid derivatives for anti -HBV. 8 Recently, a computational study is the best choice to reduce a cost and time for searching a lead compound.…”