Fragment-based and classical quantitative structure-activity relationships for a series of hydrazides as antituberculosis agents

被引：27

作者：

Andrade, Carolina H. ^{[2
]}

Salum, Livia de B. ^{[1
]}

Castilho, Marcelo S. ^{[3
]}

Pasqualoto, Kerly F. M. ^{[4
]}

Ferreira, Elizabeth I. ^{[2
]}

Andricopulo, Adriano D. ^{[1
]}

机构：

[1] Univ Sao Paulo, Inst Fis, Ctr Biotecnol Mol Estrutural, Lab Quim Med & Computac, BR-13560970 Sao Carlos, SP, Brazil

[2] Univ Sao Paulo, Fac Ciencias Farmaceut, Lab Planejamento & Sintese Quimioterapicos Potenc, BR-05508900 Sao Paulo, Brazil

[3] Univ Fed Bahia, Fac Farm, Lab Bioinformat & Modelagem Mol, BR-40170290 Salvador, BA, Brazil

[4] Univ Estadual Campinas, Inst Quim, Lab Quimiometria Teor & Aplicada, BR-13084971 Campinas, SP, Brazil

来源：

MOLECULAR DIVERSITY | 2008年 / 12卷 / 01期

基金：

巴西圣保罗研究基金会;

关键词：

tuberculosis; infectious diseases; hydrazides; drug design; QSAR;

D O I：

10.1007/s11030-008-9074-z

中图分类号：

Q5 [生物化学]; Q7 [分子生物学];

学科分类号：

071010 ; 081704 ;

摘要：

Worldwide, tuberculosis (TB) is the leading cause of death among curable infectious diseases. Multidrug-resistant Mycobacterium tuberculosis is an emerging problem of great importance to public health, and there is an urgent need for new anti-TB drugs. In the present work, classical 2D quantitative structure-activity relationships (QSAR) and hologram QSAR (HQSAR) studies were performed on a training set of 91 isoniazid derivatives. Significant statistical models (classical QSAR, q(2) = 0.68 and r(2) = 0.72; HQSAR, q(2) = 0.63 and r(2) = 0.86) were obtained, indicating their consistency for untested compounds. The models were then used to evaluate an external test set containing 24 compounds which were not included in the training set, and the predicted values were in good agreement with the experimental results (HQSAR, r(pred)(2) = 0.87; classical QSAR, r(pred)(2) = 0.75).

引用

页码：47 / 59

页数：13

共 33 条

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