摘要
目的 构建蛋白酪氨酸磷酸酶1B(protein tyrosine phosphatase 1B,PTP1B)抑制剂的药效团筛选模型.方法 通过收集文献中已报道的PTP1B小分子抑制剂,选择其中活性较强的化合物作为训练集,利用Discovery Studio中的HypoGen算法构建PTP1B抑制剂的三维药效团模型.结果 最优药效团模型具有2个氢键受体和3个疏水中心,综合参数分析药效团模型03(q2=0.643,RMS Error=0.587,Weights=1.91)、07(q2=0.678,RMS Error=0.473,Weights=1.80)较好,两模型可用于PTP1B天然抑制剂的虚拟筛选,并应用药效团模型03对半枝莲中2种生物碱类成分进行药效的预测,与实测值接近.结论 构建PTP1B抑制剂的药效团模型有较好的预测能力,有助于发现新型的PTP1B抑制剂.
Abstract
Objective:Constructing a pharmacophore screening model for protein tyrosine phosphatase 1B(PTP1B)inhibitors.Methods:The"HypoGen"algorithm in Discovery Studio was used to construct a three-dimensional pharmacophore model of PTP1B inhibitors.The training set of the simulation consisted of reported protein tyrosine phosphatase 1B inhibitors with high inhibitory activity.Results:Pharmacophore model 03(q2=0.643,RMS Error=0.587,Weights=1.91)and 07(q2=0.678,RMS Error=0.473,Weights=1.80)are better with 2 hydrogen-bond receptors and 3 hydrophobic cores and can be applied for Virtual Screening of PTP1B Inhibitors based on Natural Products.Inhibitionin of two alkaloids was predicted by pharmacophore Model 03,which was close to the measured value.Conclusion:The establishment of pharmacophore model of PTP1B inhibitors has better predictive ability,which is helpful to the discovery of novel PTP1B inhibitors.
基金项目
泰安市科技创新发展项目(政策引导类)(2022NS330)
维普
万方数据