Synthesis, anti-tuberculosis activity, and 3D-QSAR study of 4-(adamantan-1-yl)-2-substituted quinolines

Structural optimization of the previously identified 4-(adamantan-1-yl)-2-quinolinecarbohydrazide (AQCH, MIC = 6.25 μg/mL, 99% inhibition, Mycobacterium tuberculosis H37Rv) has led to two series of 4-(adamantan-1-yl)-2-substituted quinolines (Series 1–2). All new derivatives were evaluated in vitro...

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Published inBioorganic & medicinal chemistry Vol. 15; no. 2; pp. 626 - 640
Main Authors Nayyar, Amit, Monga, Vikramdeep, Malde, Alpeshkumar, Coutinho, Evans, Jain, Rahul
Format Journal Article
LanguageEnglish
Published England Elsevier Ltd 15.01.2007
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Summary:Structural optimization of the previously identified 4-(adamantan-1-yl)-2-quinolinecarbohydrazide (AQCH, MIC = 6.25 μg/mL, 99% inhibition, Mycobacterium tuberculosis H37Rv) has led to two series of 4-(adamantan-1-yl)-2-substituted quinolines (Series 1–2). All new derivatives were evaluated in vitro for antimycobacterial activities against drug-sensitive M. tuberculosis H37Rv strain. Several 4-adamantan-1-yl-quinoline-2-carboxylic acid N′-alkylhydrazides (Series 1) described herein showed promising inhibitory activity. In particular, analogs 7, 9, 20, and 21 displayed MIC of 3.125 μg/mL. Further investigation of AQCH by its reaction with various aliphatic, aromatic, and heteroaromatic aldehydes led to the synthesis of 4-adamantan-1-yl-quinoline-2-carboxylic acid alkylidene hydrazides (Series 2). Analogs 42– 44 and 48 have produced promising antimycobacterial activities (99% inhibition) at 3.125 μg/mL against drug-sensitive M. tuberculosis H37Rv strain. The most potent analog 35 of the series produced 99% inhibition at 1.00 μg/mL against drug-sensitive strain, and MIC of 3.125 μg/mL against isoniazid-resistant TB strain. To understand the relationship between structure and activity, a 3D-QSAR analysis has been carried out by three methods—comparative molecular field analysis (CoMFA), CoMFA with inclusion of a hydropathy field (HINT), and comparative molecular similarity indices analysis (CoMSIA). Several statistically significant CoMFA, CoMFA with HINT, and CoMSIA models were generated. Prediction of the activity of a test set of molecules was the best for the CoMFA model generated with database alignment. Based on the CoMFA contours, we have tried to explain the structure–activity relationships of the compounds reported herein.
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ISSN:0968-0896
1464-3391
DOI:10.1016/j.bmc.2006.10.064