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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:
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
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author Tapkir, Amit S.
Chitlange, Sohan S.
Bhole, Ritesh P.
author_facet Tapkir, Amit S.
Chitlange, Sohan S.
Bhole, Ritesh P.
author_sort Tapkir, Amit S.
collection PubMed
description 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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spelling pubmed-55549892017-08-22 Dataset of 2-(2-(4-aryloxybenzylidene) hydrazinyl) benzothiazole derivatives for GQSAR of antitubercular agents Tapkir, Amit S. Chitlange, Sohan S. Bhole, Ritesh P. Data Brief Pharmacology, Toxicology and Pharmaceutical Science 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. Elsevier 2017-08-09 /pmc/articles/PMC5554989/ /pubmed/28831410 http://dx.doi.org/10.1016/j.dib.2017.08.006 Text en © 2017 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Pharmacology, Toxicology and Pharmaceutical Science
Tapkir, Amit S.
Chitlange, Sohan S.
Bhole, Ritesh P.
Dataset of 2-(2-(4-aryloxybenzylidene) hydrazinyl) benzothiazole derivatives for GQSAR of antitubercular agents
title Dataset of 2-(2-(4-aryloxybenzylidene) hydrazinyl) benzothiazole derivatives for GQSAR of antitubercular agents
title_full Dataset of 2-(2-(4-aryloxybenzylidene) hydrazinyl) benzothiazole derivatives for GQSAR of antitubercular agents
title_fullStr Dataset of 2-(2-(4-aryloxybenzylidene) hydrazinyl) benzothiazole derivatives for GQSAR of antitubercular agents
title_full_unstemmed Dataset of 2-(2-(4-aryloxybenzylidene) hydrazinyl) benzothiazole derivatives for GQSAR of antitubercular agents
title_short Dataset of 2-(2-(4-aryloxybenzylidene) hydrazinyl) benzothiazole derivatives for GQSAR of antitubercular agents
title_sort dataset of 2-(2-(4-aryloxybenzylidene) hydrazinyl) benzothiazole derivatives for gqsar of antitubercular agents
topic Pharmacology, Toxicology and Pharmaceutical Science
url 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
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