PTP1B抑制剂的结合模式与虚拟筛选
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摘要
蛋白酪氨酸磷酸酶1B(Protein tyrosine phosphatase 1B,PTP1B)抑制剂是治疗Ⅱ型糖尿病以及肥胖症的潜在药物。药物设计包含多个环节,而普通方案通常缺少一些具体环节的细致处理。本文加入新的细节处理以完善计算过程,并用于设计新型PTP1B抑制剂:1)使用分子动力学模拟、结合自由能计算,研究实验上有较高抑制性的三缩酚酸和非抑制性的二缩酚酸在结合模式与抑制性能上的差异;2)基于三缩酚酸结构,对ZINC数据库Clean Drug-Like子集1300万个分子进行BIT_MACCS指纹相似性搜索,相似性大于75%的分子用LeDock进行分子对接,按照打分和药物基本特性描述符,选出8个分子进行分子动力学模拟,最终推选出5个与PTP1B具有较好结合模式的分子;3)为扩大分子结构多样性,对ZINC数据库中Leads Now子集360万个分子进行分子对接,利用重打分因子、pose校正因子以及聚类分析,最终筛选出10个候选化合物(Hits)以供实验验证。
Protein tyrosine phosphatase 1B(PTP1B) inhibitors are potential therapeutic agents for treating Type Ⅱ diabetes and obesity.In this study,we added detailed treatments to conventional computational approach for designing novel PTP1 B inhibitors.1) Molecular dynamics simulations and binding free energy calculations were used to study the binding modes and the inhibition differences between Trivaric Acid with higher inhibition and Nordivaricatic Acid with no inhibition.2) Similarity searchings based on the structure of Trivaric Acid were performed over 13 million molecules in the ZINC Clean Drug-Like database,leading to a 70%similar subset which was consequent to a LeDock docking combined with drug like descriptors and molecular dynamics simulations for hit selection.Five molecules were suggested to our experimental collaborators.3) Over 3.6 million compounds in the ZINC Leads Now database were screened using a sophisticated process containing rescoring,pose scaling and clustering,resulting at 10 hits for experimental validation.
引文
[1]Zhang,X.L.;Li,X.;Wang,R.X.J.Chem.Inf.Model.2009,49:1033.
    [2]Combs,A.P.J.Med.Chem.2010,53:2333.
    [3]Zhong,S.;Zhang,Y.;Xiu,Z.Curr Opin Drug Discov Devel 2010,13:326.
    [4]Irwin,J.J.;Sterling,T.;Mysinger,M.M.;Bolstad,E.S.;Coleman,R.G.J.Chem.Inf.Model.2012,52:1757.
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