integrating multi-analysis of an in silico approach to investigate cinnamaldehyde as a drugs candidate

Cinnamaldehyde is a natural compound that garnered significant interest as a potential drug candidate. this study aims to investigate the potential of cinnamaldehyde as a candidate for drugs through multi-analysis of in silico methods, such as pharmacokinetics analysis, pharmacology networking, molecular docking, and simulation of molecular dynamics. through pharmacological networking, a total of 156 proteins were identified as targets for cinnamaldehyde. a careful selection of protein-protein interactions (ppi) and topographical networking led to 10 proteins: stat3, egfr, esr1, src, ptgs2, nfkb1, mmp9, erbb2, ccnd1, and tlr4. further analysis revealed that these proteins are mainly associated with cancer pathways, antiviral responses, and lipid metabolism. docking score in binding energy value (kcal/mol) showed that cinnamaldehyde outperformed doxycycline as a reference drug, specifically in mmp9. the dynamic simulation analysis indicated that the ligand-protein complexes formed by cinnamaldehyde and doxycycline have similar patterns. the simulation result exhibited some fluctuations in rmsd and radius of gyration during the initial 10 ns. overall, the ligand-protein complexes displayed stable interaction over a 50 ns simulation. although limited in an in-silico study, this study concludes that cinnamaldehyde shows potential as an anticancer agent targeting the mmp9 protein.