Abstract:

Endothelial lipase (EL) has been implicated in high-density lipoprotein (HDL) metabolism and the pathogenetic progress of atherosclerosis, so its specific inhibitors are expected to be useful for the treatment of cardiovascular disease. In addition to the high homology of EL with other lipases such as lipoprotein lipase (LPL), the scoring bias of current docking programs toward large molecules and large protein-binding pockets also makes it difficult to find specific EL inhibitors by docking-based virtual screening. Herein, we conducted docking-based virtual screening of the Specs database for EL and LPL firstly, and we found the scoring bias phenomenon. From the docking results of the Specs database, we established standard curves for the binding energies of EL and LPL based on heavy atom number and contact area to correct the dock energy score statistically. We then validated the correctional effects of these curves in the screening of a validation set. Furthermore, the traditional Chinese medicine database (TCMD) was screened by docking using the score correction strategy. The dock ranks before and after correction were compared to confirm the screening effectiveness. Moreover, some compounds exhibiting better affinity for EL than LPL after correction as well as some compounds with antihyperlipidemic activity that may be specific EL inhibitors were analyzed to study their interaction mechanisms. The developed score correction strategy should be helpful to improve the hit rate in docking-based virtual screening. The molecules we identified should be useful for experimental scientists to prioritize drug candidates and provide groundwork for potential therapies of hyperlipidemia and atherosclerosis.

Key words: Endothelial lipase, Lipoprotein lipase, Specific inhibitor, Molecular docking, Score correction, Standard curve