The triglyceride lipase gene subfamily (TLGS) is comprised of three evolutionarily related lipases: lipoprotein lipase (LPL), hepatic lipase (HL), and endothelial lipase (EL), and plays a central role in the regulation of plasma lipid and lipoprotein metabolism. The existing evidences indicate that genetic abnormality of EL can increase plasma levels of high-density-lipoproteins (HDL) by which further influences the pathological process of various diseases including inflammation and atherosclerosis. However, specific EL inhibitors have not been reported until now. We previously homology modeled and systematically analyzed the 3D-models of all the triglyceride lipase gene subfamily members including LPL, HL and EL, and demonstrated for the first time that the binding poses of known dual inhibitor for EL/LPL including sulfonylfuran urea-type andboronic acid-type compounds achieved from docking studies and molecular dynamics simulation showed a good explanation for the difference with the known experimental biological activities and selectivity data. Furthermore, we have determined the potential key residues involved in the molecular interaction, especially for specifically binding to EL. In the current study, we will focus on designing and developing the EL-specific inhibitors based on the known chemical scaffolds and the spatial characteristics of TLGS binding sites. The combinatorial chemistry strategy will be applied to design a focused virtual EL potential inhibitor library, and then virtual screening strategy based on pharmacophore models and molecular docking will be used to identify those compounds with potential both high activity and specificity for EL. The molecular interaction fingerprint analysis for the selected compounds will help to determine 2-3 different chemical scaffolds from the designed library for further synthesis. In a total, 30-50 candidate inhibitors will be synthesized for evaluation of their biological activity based on both substrate catalyzed assay and cell assay. The development of specific-EL inhibitors will not only provide novel efficient tools for investigating EL roles in regulating lipoprotein metabolism, but also pave a potential path for the development of a novel therapeutic strategy for the regulation of plasma lipid related diseases.
甘油三酯脂酶是脂质和脂蛋白代谢中一类重要的调控酶,主要包括脂蛋白脂酶(LPL)、肝脂酶(HL)和内皮脂肪酶(EL).研究表明特异性抑制EL可以提高血浆高密度脂蛋白(HDL)浓度,进而影响包括炎症和动脉粥样硬化在内多种疾病的病理过程.课题组前期建立了多个甘油三酯脂酶的同源结构模型,针对呋喃磺酰脲与硼酸类化合物与EL/LPL的结合模式分析和计算模拟较好的解释了已知生物活性差异,确定了化合物可能特异性作用于EL的关键改造位点.本课题在上述骨架的基础上,基于脂肪酶的结构差异,采用虚拟组合策略设计化合物库,通过特异性筛选策略确定2-3类预测同时具备高活性和高特异性的EL抑制剂骨架,衍生设计、合成30-50个候选化合物,并进行基于酶底物催化和细胞水平的生物活性评价.本课题将为研究血浆HDL调控及相关病理过程中的EL生物功能提供高效的工具分子,为发现以EL为靶点的血浆脂蛋白调控药物奠定基础.
甘油三酯脂酶是脂质和脂蛋白代谢中一类重要的调控酶,主要包括脂蛋白脂酶(LPL)、肝脂酶(HL)和内皮脂肪酶(EL)。研究表明特异性抑制EL可以提高血浆高密度脂蛋白(HDL)浓度,进而影响包括炎症和动脉粥样硬化在内多种疾病的病理过程。在本课题研究过程中,基于EL底物和抑制剂诱导的动力学模型,提出了具有更高区分度的选择性抑制剂虚拟筛选模型,通过对新骨架化合物的第一轮筛选,得到了4个活性分子。选择其中三类骨架——喹啉、苯磺酰胺、苯并咪唑作为第二轮筛选的起点,丰富了骨架的衍生物,提高了新骨架系列化合物的活性和选择性,对三类骨架的结合模式和构效关系进行了总结,提升了对于新骨架EL抑制剂与EL结合所需关键药效团和关键残基作用的知识;并通过构效关系的总结,为EL抑制剂的合理设计或改造修饰提供了指导。最终我们发现了3个新骨架的数个活性突出、或是选择性突出的先导分子,可用于EL功能的研究或进一步改造优化。其中活性最好的化合物35-4 EL IC50达到0.4μM,对于LPL有700多倍的选择性。。本课题将为研究血浆HDL调控及相关病理过程中的EL生物功能提供高效的工具分子,为发现以EL为靶点的血浆脂蛋白调控药物奠定基础。
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数据更新时间:2023-05-31
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