Mapping Pharmacological Network to Identify Common Molecular Targets of Epigallocatechin-3-gallate (EGCG) in Inflammation and Cancer

Cancer development and inflammation are closely interconnected. In this study, an integrated computational strategy was employed to identify the potential common therapeutic targets of Epigallocatechin-3-gallate (EGCG) in both inflammation and cancer. Through a network pharmacology approach, EGCG targets shared between the two conditions were predicted, followed by pathway enrichment analysis using the Kyoto Encyclopaedia of Genes and Genomes (KEGG) and gene ontology (GO) databases. These analyses were effective in identifying the major targets of EGCG in fighting inflammation and cancer. Molecular docking studies demonstrated that EGCG showed the highest binding affinity with HSP90AA1 among the identified targets, with a binding score of −10.06 kcal/mol. Further, molecular dynamics (MD) simulations were performed to investigate the stability of the EGCG complexed with HSP90AA1 in comparison with the co-crystal ligand 50Q. Both molecules show comparable stability and remain intact within the binding site for 100 ns of simulations. Moreover, free energy binding of EGCG and co-crystal ligand 50Q was found to be −218.407 ± 0.921 and −146.775 ± 1.512 kJ/mol calculated by MM-PBSA method. The EGCG showed more negative binding energy than co-crystal ligand, thus emerging as a potent molecule from this study. Further in vitro and in vivo studies are essential to validate the therapeutic efficacy of EGCG. These findings provide valuable theoretical insights that could facilitate the development of EGCG as an effective HSP90AA1 inhibitor in modulating inflammation and cancer.