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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2017
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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. |
format | Online Article Text |
id | pubmed-5554989 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
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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