喹啉酮类BRD4抑制剂的3D-QSAR研究  

3D-QSAR Study of Quinolinone BRD4 Inhibitors

作　　者：刘亚平 程平 张淑平[1] LIU Yaping;CHENG Ping;ZHANG Shuping(School of Materials and Chemistry,University of Shanghai for Science and Technology,Shanghai 200093,China)

机构地区：[1]上海理工大学材料与化学学院,上海200093

出　　处：《广州化学》2024年第1期56-61,I0003,共7页Guangzhou Chemistry

摘　　要：使用比较分子力场分析法(CoMFA)和比较分子相似性指数法(CoMSIA)对33个已报道的喹啉酮类BRD4抑制剂进行3D-QSAR模型建立,研究了其化学结构和生物活性间的关系,并用计算机辅助药物设计(computer-aided drug design,CADD)设计出7个喹啉酮类抑制剂。结果表明,建立的CoMFA(q^(2)=0.926,r^(2)=0.997,r^(2)_(pred)=0.744)和CoMSIA(q^(2)=0.939,r^(2)=0.991,r^(2)_(pred)=0.786)模型具有较好的预测能力,基于这些模型设计的7个新喹啉酮类BRD4抑制剂具有高活性,并对其进行ADMET性质评价和类药性分析。以上研究结果有助于改造和开发更加有效的喹啉酮类BRD4抑制剂。Comparative molecular field analysis(CoMFA)and comparative molecular similarity index analysis(CoMSIA)were used to establish 3D-QSAR models of 33 reported quinolinone BRD4 inhibitors,and the relationship between their chemical structure and biological activity was studied.Seven quinolinone BRD4 inhibitors were designed by computer-aided drug design(CADD).The results showed that the established CoMFA(q^(2)=0.926,r^(2)=0.997,r^(2)_(pred)=0.744)and CoMSIA(q^(2)=0.939,r^(2)=0.991,r^(2)_(pred)=0.786)models had good predictive ability.Seven new quinolone BRD4 inhibitors designed based on these models had high activity,and their ADMET properties and drug-likeness were evaluated.The above results are helpful for the modification and development of more effective quinolone BRD4 inhibitors.

关 键 词：喹啉酮 BRD4抑制剂 3D-QSAR COMFA COMSIA ADMET 类药性 

分 类 号：R914.2[医药卫生—药物化学]