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Prediction of anticancer activity of aliphatic nitrosoureas using quantum chemical quantitative structure activity relation (QSAR) methods

Design and development of new anticancer drugs with low toxicity is a very challenging task and computer aided methods are being increasingly used to solve this problem. In this study, we investigated the anticancer activity of aliphatic nitrosoureas using quantum chemical quantitative structure...

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Main Authors: Noorbatcha, Ibrahim Ali, Hamzah, F., Mohd. Salleh, Hamzah, Syed Osman Idid, Syed Zahir Idid
Format: Article
Language:English
Published: Academic Journals 2011
Subjects:
TP Chemical technology
Online Access:http://irep.iium.edu.my/14650/1/QSAR_AJB_2011_published.pdf
http://irep.iium.edu.my/14650/
http://www.academicjournals.org/ajb/PDF/pdf2011/16DecConf/Noorbatcha%20et%20al.pdf
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spelling my.iium.irep.146502021-07-06T02:19:58Z http://irep.iium.edu.my/14650/ Prediction of anticancer activity of aliphatic nitrosoureas using quantum chemical quantitative structure activity relation (QSAR) methods Noorbatcha, Ibrahim Ali Hamzah, F. Mohd. Salleh, Hamzah Syed Osman Idid, Syed Zahir Idid TP Chemical technology Design and development of new anticancer drugs with low toxicity is a very challenging task and computer aided methods are being increasingly used to solve this problem. In this study, we investigated the anticancer activity of aliphatic nitrosoureas using quantum chemical quantitative structure activity relation (QSAR) approach. In this method, the physic-chemical properties, known as descriptors, necessary for predicting quantitative structure activity relations was obtained from semi empirical quantum chemical methods. We used Recife Model 1 to optimize the structure of the molecules and to calculate the quantum chemical descriptors, while heuristic and best multilinear regression methods were applied to obtain the best correlation. Two data sets containing aliphatic nitrosoureas and chloroethyl substituted nitrosoureas were used in the present calculations. The QSAR equations obtained here can be used to design new anticancer drugs prior to resorting to experimental activity studies. Key words: Quantitative structure activity relationship (QSAR), best multi linear regression (BMLR), quantum chemical method, Recife Model 1 (RM1). Academic Journals 2011-12-16 Article PeerReviewed application/pdf en http://irep.iium.edu.my/14650/1/QSAR_AJB_2011_published.pdf Noorbatcha, Ibrahim Ali and Hamzah, F. and Mohd. Salleh, Hamzah and Syed Osman Idid, Syed Zahir Idid (2011) Prediction of anticancer activity of aliphatic nitrosoureas using quantum chemical quantitative structure activity relation (QSAR) methods. African Journal of Biotechnology, 10 (81). pp. 18863-18868. ISSN 1684–5315 http://www.academicjournals.org/ajb/PDF/pdf2011/16DecConf/Noorbatcha%20et%20al.pdf DOI: 10.5897/AJB11.2766
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
topic TP Chemical technology
spellingShingle TP Chemical technology
Noorbatcha, Ibrahim Ali
Hamzah, F.
Mohd. Salleh, Hamzah
Syed Osman Idid, Syed Zahir Idid
Prediction of anticancer activity of aliphatic nitrosoureas using quantum chemical quantitative structure activity relation (QSAR) methods
description Design and development of new anticancer drugs with low toxicity is a very challenging task and computer aided methods are being increasingly used to solve this problem. In this study, we investigated the anticancer activity of aliphatic nitrosoureas using quantum chemical quantitative structure activity relation (QSAR) approach. In this method, the physic-chemical properties, known as descriptors, necessary for predicting quantitative structure activity relations was obtained from semi empirical quantum chemical methods. We used Recife Model 1 to optimize the structure of the molecules and to calculate the quantum chemical descriptors, while heuristic and best multilinear regression methods were applied to obtain the best correlation. Two data sets containing aliphatic nitrosoureas and chloroethyl substituted nitrosoureas were used in the present calculations. The QSAR equations obtained here can be used to design new anticancer drugs prior to resorting to experimental activity studies. Key words: Quantitative structure activity relationship (QSAR), best multi linear regression (BMLR), quantum chemical method, Recife Model 1 (RM1).
format Article
author Noorbatcha, Ibrahim Ali
Hamzah, F.
Mohd. Salleh, Hamzah
Syed Osman Idid, Syed Zahir Idid
author_facet Noorbatcha, Ibrahim Ali
Hamzah, F.
Mohd. Salleh, Hamzah
Syed Osman Idid, Syed Zahir Idid
author_sort Noorbatcha, Ibrahim Ali
title Prediction of anticancer activity of aliphatic nitrosoureas using quantum chemical quantitative structure activity relation (QSAR) methods
title_short Prediction of anticancer activity of aliphatic nitrosoureas using quantum chemical quantitative structure activity relation (QSAR) methods
title_full Prediction of anticancer activity of aliphatic nitrosoureas using quantum chemical quantitative structure activity relation (QSAR) methods
title_fullStr Prediction of anticancer activity of aliphatic nitrosoureas using quantum chemical quantitative structure activity relation (QSAR) methods
title_full_unstemmed Prediction of anticancer activity of aliphatic nitrosoureas using quantum chemical quantitative structure activity relation (QSAR) methods
title_sort prediction of anticancer activity of aliphatic nitrosoureas using quantum chemical quantitative structure activity relation (qsar) methods
publisher Academic Journals
publishDate 2011
url http://irep.iium.edu.my/14650/1/QSAR_AJB_2011_published.pdf
http://irep.iium.edu.my/14650/
http://www.academicjournals.org/ajb/PDF/pdf2011/16DecConf/Noorbatcha%20et%20al.pdf
_version_ 1705056438596927488
score 13.211869

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