• 中文
    • English
  • English 
    • 中文
    • English
  • Login
View Item 
  •   DSpace Home
  • 化学化工学院
  • 化学化工-已发表论文
  • View Item
  •   DSpace Home
  • 化学化工学院
  • 化学化工-已发表论文
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Structure-based rational quest for potential novel inhibitors of human HMG-CoA reductase by combining CoMFA 3D QSAR modeling and virtual screening

Thumbnail
Full Text
Structure-based rational quest for potential novel inhibitors of human HMG-CoA reductase by combining CoMFA 3D QSAR modeling and virtual screening.htm (392bytes)
Date
2006-11
Author
Zhang, Qing Y.
Wan, Jian
Xu, Xin
徐昕
Yang, Guang F.
Ren, Yan L.
Liu, Jun J.
Wang, Hui
Guo, Yu
Collections
  • 化学化工-已发表论文 [14469]
Show full item record
Abstract
3-Hydroxy-3-methylglutaryl-coenzyme A reductase (HMGR) catalyzes the formation of mevalonate. In many classes of organisms, this is the committed step leading to the synthesis of essential compounds, such as cholesterol. However, a high level of cholesterol is an important risk factor for coronary heart disease, for which an effective clinical treatment is to block HMGR using inhibitors like statins. Recently the structures of catalytic portion of human HMGR complexed with six different statins have been determined by a delicate crystallography study (Istvan and Deisenhofer Science 2001, 292, 1160-1164), which established a solid basis of structure and mechanism for the rational design, optimization, and development of even better HMGR inhibitors. In this study, three-dimensional quantitative structure-activity relationship (3D QSAR) with comparative molecular field analysis (CoMFA) was performed on a training set of up to 35 statins and statin-like compounds. Predictive models were established by using two different ways: (1) Models-fit, obtained by SYBYL conventional fit-atom molecular alignment rule, has cross-validated coefficients (q(2)) up to 0.652 and regression coefficients (r(2)) up to 0.977. (2) Models-dock, obtained by FlexE by docking compounds into the HMGR active site, has cross-validated coefficients (q(2)) up to 0.731 and regression coefficients (r(2)) up to 0.947. These models were further validated by an external testing set of 12 statins and statin-like compounds. Integrated with CoMFA 3D QSAR predictive models, molecular surface property (electrostatic and steric) mapping and structure-based (both ligand and receptor) virtual screening have been employed to explore potential novel hits for the HMGR inhibitors. A representative set of eight new compounds of non-statin-like structures but with high pIC(50) values were sorted out in the present study.
Citation
J. Comb. Chem., 2007, 9 (1): 131–138
URI
http://dx.doi.org/doi:10.1021/cc060101e
https://dspace.xmu.edu.cn/handle/2288/9677

copyright © 2002-2016  Duraspace  Theme by @mire  厦门大学图书馆  
About | Policies
 

 

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

LoginRegister

copyright © 2002-2016  Duraspace  Theme by @mire  厦门大学图书馆  
About | Policies