Dataset of 2-(2-(4-aryloxybenzylidene) hydrazinyl) benzothiazole derivatives for GQSAR of antitubercular agents

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...

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Detalles Bibliográficos
Autores principales: Tapkir, Amit S., Chitlange, Sohan S., Bhole, Ritesh P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2017
Materias:
Pharmacology, Toxicology and Pharmaceutical Science
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5554989/
https://www.ncbi.nlm.nih.gov/pubmed/28831410
http://dx.doi.org/10.1016/j.dib.2017.08.006
Descripción
Sumario: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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