3D-QSAR studies on Maslinic acid analogs for Anticancer activity against Breast Cancer cell line MCF-7

Abstract

Abstract Global prevalence of breast cancer and its rising frequency makes it a key area of research in drug discovery programs. The research article describes the development of field based 3D-QSAR model based on human breast cancer cell line MCF7 in vitro anticancer activity, which defines the molecular level understanding and regions of structure-activity relationship for triterpene maslinic acid and its analogs. The key features such as average shape, hydrophobic regions and electrostatic patterns of active compounds were mined and mapped to virtually screen potential analogs. Then, field points based descriptors were used to develop a 3D-QSAR model by aligning known active compounds onto identified pharmacophore template. The derived LOO validated PLS regression QSAR model showed acceptable r2 0.92 and q2 0.75. After screening through Lipinski’s rule of five filter for oral bioavailability, ADMET risk filter for drug like features, and synthetic accessibility for chemical synthesis, out of 593 hits, 39 were left top hits. Docking screening was performed through identified potential targets namely, AKR1B10, NR3C1, PTGS2, and HER2. Finally, compound P-902 was identified as best hit. This study, would be of great help in lead identification and optimization for early drug discovery.