Research Center for Drug Discovery, School of Pharmaceutical Sciences, Sun Yat-Sen University, Guangzhou, China.
J Chem Inf Model. 2011 Sep 26;51(9):2147-55. doi: 10.1021/ci100511v. Epub 2011 Mar 24.
High cholesterol levels contribute to hyperlipidemia. Liver X receptors (LXRs) are the drug targets. LXRs regulate the cholesterol absorption, biosynthesis, transportation, and metabolism. Novel agonists of LXR, especially LXRβ, are attractive solutions for treating hyperlipidemia. In order to discover novel LXRβ agonists, a three-dimensional pharmacophore model was built based upon known LXRβ agonists. The model was validated with a test set, a virtual screening experiment, and the FlexX docking approach. Results show that the model is capable of predicting a LXRβ agonist activity. Ligand-based virtual screening results can be refined by cross-linking by structure-based approaches. This is because two ligands that are mapped in the same way to the same pharmacophore model may have significantly different binding behaviors in the receptor's binding pocket. This paper reports our approach to identify reliable pharmacophore models through combining both ligand- and structure-based approaches.
胆固醇水平升高会导致高脂血症。肝 X 受体（LXRs）是药物靶点。LXRs 调节胆固醇的吸收、生物合成、运输和代谢。LXR 的新型激动剂，特别是 LXRβ，是治疗高脂血症的有吸引力的解决方案。为了发现新型 LXRβ 激动剂，基于已知的 LXRβ 激动剂构建了一个三维药效团模型。该模型通过测试集、虚拟筛选实验和 FlexX 对接方法进行了验证。结果表明，该模型能够预测 LXRβ 激动剂的活性。基于配体的虚拟筛选结果可以通过基于结构的方法进行交联来进一步优化。这是因为映射到相同药效团模型的两种配体在受体结合口袋中可能具有明显不同的结合行为。本文报告了我们通过结合基于配体和基于结构的方法来识别可靠药效团模型的方法。
