QSAR model for mast cell stabilizing activity of indolecarboxamidotetrazole compounds on human basophils
Basu, Anamika ; Sarkar, Anasua LU
and Basak, Piyali
(2017)
1st International Conference on Computational Intelligence, Communications, and Business Analytics, CICBA 2017
In Communications in Computer and Information Science
776.
p.17-29
- Abstract
Indolecarboxamidotetrazole compounds are well known as potential anti allergic agents due to their mast cell stabilizing activity on human basophils. A quantitative structure activity relationship (QSAR) model has been generated using Multiple Linear regression (MLR) for the prediction of inhibition efficiency of indolecarboxamidotetrazole derivatives. Twenty-one compounds with their activities expressed as % inhibition (PI) are collected. Descriptors are generated using Chemistry Development Kit. Three models are built and the models are evaluated using multiple correlation coefficient (R) and residual standard deviation (s). Considering the quality and accuracy of the predicted models, model 1 is the best, because it predicts... (More)
Indolecarboxamidotetrazole compounds are well known as potential anti allergic agents due to their mast cell stabilizing activity on human basophils. A quantitative structure activity relationship (QSAR) model has been generated using Multiple Linear regression (MLR) for the prediction of inhibition efficiency of indolecarboxamidotetrazole derivatives. Twenty-one compounds with their activities expressed as % inhibition (PI) are collected. Descriptors are generated using Chemistry Development Kit. Three models are built and the models are evaluated using multiple correlation coefficient (R) and residual standard deviation (s). Considering the quality and accuracy of the predicted models, model 1 is the best, because it predicts biological activity which is almost closed to that of experimental value. This model is externally validated. This built model can be used to calculate inhibition efficiency of natural mast cell stabilizers containing caroxamidotetrazoles as antiallergic chemical in future.
(Less)
- author
- Basu, Anamika
; Sarkar, Anasua
LU
and Basak, Piyali
- publishing date
- 2017
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- keywords
- Carboxamidotetrazole, Multiple linear regression, Natural mast cell stabilizer, QSAR model
- host publication
- Computational Intelligence, Communications, and Business Analytics - 1st International Conference, CICBA 2017, Revised Selected Papers
- series title
- Communications in Computer and Information Science
- volume
- 776
- pages
- 13 pages
- publisher
- Springer
- conference name
- 1st International Conference on Computational Intelligence, Communications, and Business Analytics, CICBA 2017
- conference location
- Kolkata, India
- conference dates
- 2017-03-24 - 2017-03-25
- external identifiers
-
- scopus:85032504172
- ISSN
- 1865-0929
- ISBN
- 9789811064296
- DOI
- 10.1007/978-981-10-6430-2_2
- language
- English
- LU publication?
- no
- id
- 699dacda-d3d0-488e-a8ce-8de63f595902
- date added to LUP
- 2018-09-13 10:15:47
- date last changed
- 2022-03-09 20:33:27
@inproceedings{699dacda-d3d0-488e-a8ce-8de63f595902,
abstract = {{<p>Indolecarboxamidotetrazole compounds are well known as potential anti allergic agents due to their mast cell stabilizing activity on human basophils. A quantitative structure activity relationship (QSAR) model has been generated using Multiple Linear regression (MLR) for the prediction of inhibition efficiency of indolecarboxamidotetrazole derivatives. Twenty-one compounds with their activities expressed as % inhibition (PI) are collected. Descriptors are generated using Chemistry Development Kit. Three models are built and the models are evaluated using multiple correlation coefficient (R) and residual standard deviation (s). Considering the quality and accuracy of the predicted models, model 1 is the best, because it predicts biological activity which is almost closed to that of experimental value. This model is externally validated. This built model can be used to calculate inhibition efficiency of natural mast cell stabilizers containing caroxamidotetrazoles as antiallergic chemical in future.</p>}},
author = {{Basu, Anamika and Sarkar, Anasua and Basak, Piyali}},
booktitle = {{Computational Intelligence, Communications, and Business Analytics - 1st International Conference, CICBA 2017, Revised Selected Papers}},
isbn = {{9789811064296}},
issn = {{1865-0929}},
keywords = {{Carboxamidotetrazole; Multiple linear regression; Natural mast cell stabilizer; QSAR model}},
language = {{eng}},
pages = {{17--29}},
publisher = {{Springer}},
series = {{Communications in Computer and Information Science}},
title = {{QSAR model for mast cell stabilizing activity of indolecarboxamidotetrazole compounds on human basophils}},
url = {{http://dx.doi.org/10.1007/978-981-10-6430-2_2}},
doi = {{10.1007/978-981-10-6430-2_2}},
volume = {{776}},
year = {{2017}},
}