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In a number of human cancers, both cycloxygenase-2 (COX-2) and 5-lipoxygenase (5-LOX) are up-regulated and co-expressed, promoting cancer cell proliferation and angiogenesis. Resveratrol (3,4′,5-trihydroxy-trans-stilbene) is a natural polyphenolic phytoalexin found in a variety of plants that influences various signal-transduction pathways which control apoptosis, cell growth and cell division, metastasis, angiogenesis and inflammation, and has an impact on cancer stages ranging from initiation to progression. In this work, molecular docking and molecular dynamics simulation method are employed to design resveratrol derivatives for COX-2 and 5-LOX enzymes. By attaching several functional groups on four different places of the resveratrol scaffold, the R group enumeration approach was employed to build four libraries of resveratrol derivatives. Thus, R group enumeration is done to focus on the enhancement of potency of compounds and other chemical characteristics like solubility. Drug-like filters such as REOS 1, 2, 3 and PAINS were applied to the libraries, generating a total of 5557 compounds. Drug-like filters such as REOS and PAINS-1, 2 and 3 were applied to the libraries, generating a total of 5557 compounds. All of these compounds were docked with both enzymes using the Glide SP and XP docking methods. Enrichment calculations were performed using 40 compounds from XP docking along with resveratrol, and 1000 decoy compounds from the DUD-E database to validate the docking protocol. The stability of the complexes was further studied using molecular dynamics simulation, radius of gyration, MM/GBSA, H bond monitoring and electrostatic potential surface (EPS). ADMET properties of compounds were studied using SwissADME and pkCSM server. Communicated by Ramaswamy H. Sarma

Dual inhibition of cyclooxygenase-2 (COX-2) and 5-lipoxygenase (5-LOX) by resveratrol derivatives in cancer therapy: in silico approach