首页|喹啉酮类BRD4抑制剂的3D-QSAR研究

喹啉酮类BRD4抑制剂的3D-QSAR研究

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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(q2=0.926,r2=0.997,r2pred=0.744)和CoMSIA(q2=0.939,r2=0.991,r2pred=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.
3D-QSAR Study of Quinolinone BRD4 Inhibitors
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(q2 = 0.926,r2 = 0.997,r2pred = 0.744)and CoMSIA(q2 = 0.939,r2 = 0.991,r2pred = 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.

quinolinoneBRD4 inhibitor3D-QSARCoMFACoMSIAADMETdrug-like properties

刘亚平、程平、张淑平

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上海理工大学 材料与化学学院,上海 200093

喹啉酮 BRD4 抑制剂 3D-QSAR CoMFA CoMSIA ADMET 类药性

2024

广州化学
中国科学院广州化学研究所

广州化学

影响因子:0.291
ISSN:1009-220X
年,卷(期):2024.49(1)
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