中文摘要：

内皮脂肪酶（EL）是脂代谢调控甘油三酯脂酶家族的新成员，其功能主要为水解富含磷脂的高密度脂蛋白（HDL），对其进行选择性抑制而不影响其同源蛋白脂蛋白脂肪酶（LPL）能够提高血浆中HDLc的浓度水平，有利于预防及治疗动脉粥样硬化疾病。目前分子对接中的打分函数对大分子及大蛋白口袋具有偏向性，使得基于分子对接的虚拟筛选成功率普遍不高。本文中，我们将EL和LPL分别与Specs小分子库进行了分子对接，分析了对接打分与重原子数及接触面积的关系，发现对接打分与重原子数及接触面积之间有极高的相关性，即存在重原子数的叠加效应（重原子数越大，打分越好的趋势）。我们建立了基于重原子数和接触面积的EL、LPL对接打分标准曲线，利用此标准曲线进行对接打分的修正，并用已知抑制剂和生成的decoy分子作为验证集进行了验证。随后，我们应用此打分修正策略对传统中药库（TCMD）进行了基于分子对接的虚拟筛选，发现经过打分修正后的分子排名与重原子数之间的分布更为均衡，同时我们对EL打分较高、LPL打分较低且类药性较好的分子进行了结合模式的分析，为高活性高选择性EL抑制剂的发现奠定了基础。

英文摘要：

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.