Integrative computational and experimental approaches to Hydnocarpus wightianus phytochemicals: Targeting breast...

Breast cancer causes a huge burden on healthcare systems, and it is crucial to identify new drugs from nature sources with better efficacy and safety profile. By employing an integrated computational and experimental strategy, the current study focuses on discovering phytochemicals from Hydnocarpus wightianus as anti-breast cancer agents, with the major concern of mechanistic understanding and molecular stability. Initially, H. wightianus phytochemicals were subjected to drug-likeness screening and their possible molecular targets were predicted using SwissTargetPrediction. Breast cancer associated genes were collected from GeneCards and OMIM databases. Compound-target and protein-protein interaction networks were constructed and analyzed using Cytoscape, CytoHubba, and MCODE to find out the important hub genes and functional modules. Further, Gene Ontology and KEGG pathway enrichment analyses were performed to confirm the biological relevance. Identified potential genes were docked and top leads were analyzed using ADMET profiling, and molecular dynamics simulations. Molecular Electrostatic Potential mapping and Density Functional Theory calculations were employed to reveal the electronic distribution and chemical reactivity of the predominant H. wightianus compound. MDA-MB-231 breast cancer cells were used for experimental validation. In vitro studies showed that cell death caused by the drug increased in relation to its concentration, mitochondria lost their potential, and cells were undergoing apoptotic ones as confirmed by Rhodamine 123, Hoechst, and AO/EtBr staining. The combination of network pharmacology, molecular dynamics, and DFT-based electronic analysis, along with experimental validation, ranks H. wightianus bioactive compounds as promising therapeutic candidates for future preclinical and clinical trials in the fight against breast cancer.