Identifying a novel class of lead compounds for monoacylglycerol lipase inhibition: an integrated computational study.

Monoacylglycerol lipase (MAGL) is a serine hydrolase that degrades the endocannabinoid 2-arachidonoylglycerol and other monoacylglycerols in the brain and peripheral tissues. Elevated MAGL levels in invasive malignancies promote tumor growth by releasing free fatty acids, making MAGL inhibition a potential strategy for treating cancer. In this study, a virtual screening workflow began with Pharmit web server, where a pharmacophore was generated based on the X-ray crystal structure of MAGL complexed with its inhibitor, (2-cyclohexyl-1,3-benzoxazol-6-yl){3-[4-(pyrimidin-2-yl)piperazin-1-yl]azetidin-1-yl}methanone. A total of 5.241 million molecules from the MolPort database were screened, utilizing its diverse and purchasable chemical space to enhance the likelihood of identifying novel MAGL inhibitors and facilitating experimental validation. After applying filters based on Lipinski's and Veber's rules, a maximum energy cutoff of -7.0 kcal/mol, and an RMSD of 2Å, 4027 hits were obtained. The compounds were then docked using Vina-GPU, and the top five hits, along with the co-crystal inhibitor, were further analyzed through DFT computations and molecular dynamics simulations. MMGBSA computations identified MolPort-007-806-063 as the most potent compound, with a binding energy of -59.9±0.23 kcal/mol. In comparison, the co-crystal inhibitor exhibited a binding energy of -56.26±0.22 kcal/mol, while the other compounds showed energies of -54.57±0.26 kcal/mol, -53.57±0.24 kcal/mol, -41.13±0.33 kcal/mol, and -36.23±0.36 kcal/mol. These compounds are promising MAGL inhibitor candidates for experimental validation through enzyme inhibition assays, cell-based activity assays, and crystallographic studies to confirm their predicted binding modes and potency.