CYP1A2抑制剂预测模型的建立及评价

Establishment and evaluation of prediction models for the discovery of CYP1A2 inhibitors

CYP1A2酶在药物代谢中起着重要作用,抑制CYP1A2会引起被CYP1A2代谢的其他药物代谢率降低,从而导致这些药物的血浆浓度增加,进而使药物的生物效应增强,可能产生药物毒性。因此识别区分CYP1A2抑制剂成为新药早期评选及药物安全性评估的研究重点。本研究利用674个已知CYP1A2抑制活性的化合物构建CYP1A2抑制剂配体库,从基于受体和基于配体的角度,采用分子对接和药效团的方法,利用Pipeline Pilot软件建立自动化筛选预测流程,简单全面地从蛋白-配体结合角度快速准确预测出CYP1A2的抑制剂分子。最终从配体库中共预测出16个目标化合物,其中14个化合物具有CYP1A2抑制活性。研究最后对美国成药数据库进行综合预测,共发现4个药物是已报道的CYP1A2抑制剂。说明本模型对CYP1A2抑制剂具有很好的预测能力,可以应用于CYP1A2抑制剂的预测。

CYP1A2 enzyme plays a crucial role in drug metabolism, and its inhibition may cause low metabolic rates and increased plasma concentrations of the drugs metabolized by CYP1A2, thus leading to drug toxicity. Therefore, distinction between CYP1A2 inhibitors and non-inhibitors becomes important topic on the early selection of new drug candidates and drug safety assessment. In this study, a CYP1A2 inhibitor-ligand library was built with 674 compounds known to possess CYP1A2 inhibitory activity. From the point of receptor-based and ligand-based view, we have built an automatic screening protocol with Pipeline Pilot, using molecular docking and pharmacophore modeling methods, so as to predict inhibitors from CYP1A2 inhibitor library quickly and accurately. The final model predicted 16 target compounds from the library, and 14 of which were CYP1A2 inhibitors. At last, we used the final model to screen the American Medicine Database, and four drugs were found to possess CYP1A2 inhibitory activity. The combination of prediction models can improve the efficiency of CYP1A2 inhibitor discovery significantly.