Fingerprint-based QSAR Model Generation to Identify Structural Determinants of HCV NS5B Inhibition

• DOI: 10.29228/jrp.429
• Publication Date: 2023-07-14T09:33:00Z
• Authors: Berin KARAMAN MAYACK; Muhammed Moyasar ...; Mikail Hakan GEZG...
• Keywords: NS5B

RNA-dependent RNA polymerase, non-structural protein 5B (NS5B), is an essential enzyme of HCV for viral transcription and genome replication.Its initial validation as a promising target the treatment chronic hepatitis hepatocellular carcinoma has consequently prompted different research institutes pharmaceutical industry to find potential inhibitors human therapies.Among those, anthranilic acid derivatives received increasing attention because their drug-like properties.In order design drug candidates, structural determinants NS5B were determined by robust fingerprint-based quantitative structure-activity relationship (QSAR) model which was depicted on atomic effect contribution maps provide visual aids medicinal chemists.In present work, we used combination computational chemistry methods including ensemble docking, binding free energy calculations, QSAR model.We built in silico protocol accelerate structure-based inhibitors.The model, kpls_linear_3, constructed KPLS fitting with linear fingerprints produced best predictive performance (a correlation coefficient training set R2 = 0.8900, Q² 0.9234 RMSE 0.3032 test compounds).The map that generated based this showed good agreement between predictions experimental data.To our knowledge, illustrated first time use aid assessing strategy represented herein can assist chemists rapid identification important features novel other targets well.