Fragment based Quantitative structure activity relationship (QSAR) analysis on reported 25 2-(2-(4-aryloxybenzylidene) hydrazinyl) benzothiazole dataset as antitubercular agents were carried out. Molecules in the current dataset were fragmented into six fragments (R1, R2, R3, R4, R5, R6).Group based QSAR Models were derived using Multiple linear regression (MLR) analysis and selected on the basis of various statistical parameters. Dataset of benzothiazole reveled importance of presence of halogen atoms on is essential requirement. The generated models will provide structural requirements of benzothiazole derivatives which can be used to design and develop potent antitubercular derivatives.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5554989PMC
http://dx.doi.org/10.1016/j.dib.2017.08.006DOI Listing

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Fragment based Quantitative structure activity relationship (QSAR) analysis on reported 25 2-(2-(4-aryloxybenzylidene) hydrazinyl) benzothiazole dataset as antitubercular agents were carried out. Molecules in the current dataset were fragmented into six fragments (R1, R2, R3, R4, R5, R6).Group based QSAR Models were derived using Multiple linear regression (MLR) analysis and selected on the basis of various statistical parameters.

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Novel 2-(2-(4-aryloxybenzylidene) hydrazinyl)benzothiazole derivatives as anti-tubercular agents.

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Institute of Chemical Technology, Department of Pharmaceutical Sciences and Technology, Nathalal Parekh Marg, Matunga, Mumbai 400019, India.

A series of structurally novel, substituted 2-(2-(4-aryloxybenzylidene) hydrazinyl)benzothiazole derivatives incorporating 2-hydrazinyl benzothiazole and 4-(aryloxy)benzaldehyde were designed and synthesized using molecular hybridization approach. All the synthesized compounds exhibited promising activity (MIC 1.5-29.

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