Noor Zafirah Ismail, Melati Khairuddean, Sadiq Abubakar, Hasni Arsad
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引用次数: 0
Abstract
Compounds with a chalcone scaffold-based structure have demonstrated promising anticancer biological activity. However, the molecular interactions between chalcone scaffold-based compounds and breast cancer-associated proteins remain unclear. Through network pharmacology, molecular docking, and molecular dynamics (MD) simulation analyses, compounds with a chalcone scaffold-based structure were evaluated for their interaction with potential breast cancer targets. The compounds were retrieved from the ASINEX database, resulting in 575,302 compounds. A total of 342 compounds with chalcone scaffold-based structures were discovered. From the 342 compounds that was analysed, ten were chosen due to their adherence to Lipinski's rule, having an appropriate range of lipophilicity (LOGP), and topological polar surface area (TPSA), and absence of any toxicity. Based on target intersection, 50 target genes were found and subjected to protein-protein interaction (PPI), gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Four target genes were found to be involved in the breast cancer pathway. Consequently, molecular docking was utilised to analyse the molecular interactions between the compounds and four target protein receptors. Compound 211 exhibited the highest binding affinities for the epidermal growth factor receptor (EGFR), fibroblast growth factor receptor 1 (FGFR1), oestrogen receptor (ESR1), and cyclin dependent kinase 6 (CDK6) with values of -8.95 kcal/mol, -8.60 kcal/mol, -10.33 kcal/mol, and -9.90 kcal/mol, respectively. During MD simulation, compound 211 and its respective proteins were stable, compact, and had minimal flexibility. The findings provide foundations for future studies into the interaction underlying the anti-breast cancer potential of compounds with chalcone-based scaffold structures.
期刊介绍:
The Journal of Biomolecular Structure and Dynamics welcomes manuscripts on biological structure, dynamics, interactions and expression. The Journal is one of the leading publications in high end computational science, atomic structural biology, bioinformatics, virtual drug design, genomics and biological networks.