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目的选取33个噻吩并[3,2-d]嘧啶-6-甲酰胺类SIRT1~3抑制剂,进行三维定量构效关系(3D-QSAR)研究,为筛选高活性SIRT1~3抑制剂的研究奠定基础。方法通过2种经典的比较分子力场分析(Co MFA)法和比较分子相似性指数分析(Co MSIA)法,针对SIRT1~3抑制剂依次建立3组3D-QSAR模型,进行构效关系研究。结果 Co MFA模型交叉验证系数q2分别为0.814、0.833、0.726,相关系数r2分别为0.999、1.000、0.981;Co MSIA模型q2分别为0.716、0.785、0.608,r2分别为0.924、0.990、0.962。结论 3组3D-QSAR模型均具有较好预测能力和较强稳定性,可为SIRT1~3抑制剂的设计和筛选提供可靠的理论依据。
Objective To select 33 thieno [3,2-d] pyrimidine-6-carboxamides as inhibitors of SIRT1 ~ 3 for 3D-QSAR study and to screen highly active SIRT1 ~ 3 inhibitors Lay the foundation. Methods Three sets of 3D-QSAR models were established for SIRT1 ~ 3 inhibitors in order to study the structure-activity relationship by two classical methods of comparative molecular force field analysis (Co MFA) and comparative molecular similarity index (Co MSIA). Results The cross-validation coefficients of Co MFA models were 0.814, 0.833 and 0.726 respectively, and the correlation coefficients r2 were 0.999, 1.000 and 0.981 respectively. The Co MSIA models q2 were 0.716, 0.785 and 0.608 respectively, and r2 was 0.924, 0.990 and 0.962 respectively. Conclusion All three groups of 3D-QSAR models have good predictive ability and strong stability, which can provide a reliable theoretical basis for the design and screening of SIRT1 ~ 3 inhibitors.