First report on exploration of structural features of natural compounds (NPACT database) for anti-breast cancer activity (MCF-7): QSAR-based virtual screening, molecular docking, ADMET, MD simulation, and DFT studies.

Abstract

Due to the high toxicity, poor efficacy and resistance associated with current anti-breast cancer drugs, there's growing interest in natural products (NPs) for their potential anti-cancer properties. Computational modelling of NPs to identify key structural features can aid in developing novel natural inhibitors. In this study, we developed statistically significant QSAR models based on NPs from the NPACT database, which have shown potential anticancer activity against the MCF-7 cancer cell lines. All the developed QSAR models were statistically robust, meeting both internal (R ²  = 0.666-0.669, R ² _adj  = 0.657-0.660, Q ² _Loo  = 0.636-0.638) and external (Q ² F _n  = 0.686-0.714, CCC _ext = 0.830-0.847) validation criteria. Consequently, they were utilized to virtually screen a series of NPs from the COCONUT database in the search for novel natural inhibitors. Molecular docking studies were conducted on the identified compounds against the human HER2 protein (PDB ID: 3PP0), which is a crucial target in breast cancer. Molecular docking analysis demonstrated that compounds 4608 and 2710 achieved the highest docking scores, with CDOCKER interaction energies of -72.67 kcal/mol and - 72.63 kcal/mol respectively. Compounds 4608 and 2710 were identified as the most promising candidates upon performing triplicate 100 ns MD simulation study using the CHARMM36 force field. DFT studies was performed to evaluate their stability and reactivity as potential drug molecules. This research contributes to the development of new natural inhibitors for breast cancer.

Supplementary information: The online version contains supplementary material available at 10.1007/s40203-024-00266-5.