目的 采用計(jì)算機(jī)輔助藥物設(shè)計(jì)的方法發(fā)現(xiàn)潛在的PTP1B抑制劑。方法 應(yīng)用3D-QSAR藥效團(tuán)模型中的Hypogen模塊構(gòu)建藥效團(tuán)模型，成本分析、測(cè)試集預(yù)測(cè)和Fisher檢驗(yàn)3種方法來(lái)驗(yàn)證該模型可用于預(yù)測(cè)化合物的生物活性的能力。運(yùn)用該藥效團(tuán)模型對(duì)ZINC數(shù)據(jù)庫(kù)進(jìn)行虛擬篩選，得到Fit value值較高的先導(dǎo)化合物ZINC35671983。根據(jù)藥效團(tuán)的特征對(duì)ZINC35671983進(jìn)行結(jié)構(gòu)改造得到相應(yīng)化合物。將化合物用ADMET進(jìn)行成藥預(yù)測(cè)。結(jié)果 ZINC35671983進(jìn)行結(jié)構(gòu)改造篩選獲得92個(gè)化合物，篩出對(duì)接得分高于ZINC3567198的8個(gè)化合物。結(jié)論 發(fā)現(xiàn)8個(gè)潛在的PTP1B抑制劑，這有助于發(fā)現(xiàn)新的PTP1B先導(dǎo)化合物。

Objective To identify Potential PTP1B inhibitors by computer-aided drug design. Methods The Hypogen module of 3D-QSAR pharmacophore model was used to construct the pharmacophore model, cost analysis, test set prediction and Fisher test to verify the ability of the model to predict the biological activity of the compound. The lead compound ZINC35671983 with high Fit value was obtained by virtual screening of ZINC database with the pharmacophore model. The corresponding compounds were obtained by structural modification of ZINC35671983 according to the characteristics of pharmacophore. The compounds were predicted by ADMET. Results ZINC35671983 obtained 92 compounds through structural modification screening, and screened out 8 compounds with higher docking scores than ZINC3567198. Conclusion A total of 8 potential PTP1B inhibitors were found which is helpful to find new PTP1B lead compounds.

R96

天津市醫(yī)學(xué)重點(diǎn)學(xué)科（專(zhuān)科）建設(shè)資助項(xiàng)目（TJYXZDXK-032A）