Quantum chemical QSAR models to predict the anticancer activity of nitrosoureas

Discovery of new anticancer drugs is a daunting task confronting the scientists for a long time. Computer aided methods can provide important insights in this direction. In this work we have investigated the anticancer activity of aliphatic nitrosoureas using quantum chemical quantitative structure...

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Main Authors:	Ibrahim Ali , Noorbatcha, Mohd Salleh, Hamzah, Syed Osman Idid, Syed Zahir Idid
Format:	Conference or Workshop Item
Language:	English English English
Published:	2010
Subjects:	TP248.13 Biotechnology
Online Access:	http://irep.iium.edu.my/4083/ http://irep.iium.edu.my/4083/4/MSTC2010_IBRAHIM_acceptance_letter.pdf http://irep.iium.edu.my/4083/6/MSTC_2010_PARALLEL_TECHNICAL_SESSION__PROG_Book.pdf http://irep.iium.edu.my/4083/1/MSTC2010_nitrosourea_QSAR.pdf

id	iium-4083
recordtype	eprints
spelling	iium-40832014-01-15T03:19:06Z http://irep.iium.edu.my/4083/ Quantum chemical QSAR models to predict the anticancer activity of nitrosoureas Ibrahim Ali , Noorbatcha Mohd Salleh, Hamzah Syed Osman Idid, Syed Zahir Idid TP248.13 Biotechnology Discovery of new anticancer drugs is a daunting task confronting the scientists for a long time. Computer aided methods can provide important insights in this direction. In this work we have investigated the anticancer activity of aliphatic nitrosoureas using quantum chemical quantitative structure activity relationship (qcQSAR) approach. In this method the structures of the active compounds are optimized using quantum chemical methods and several quantum chemical properties are calculated in the process. These properties are subjected to detailed statistical analysis and the selected descriptors are used in the construction of the quantitative structure activity relationship. Semi empirical quantum chemical RM1 (Recife Model 1) method was used for structure optimization, while Heuristic and Multi-Linear Regression (MLR) methods were applied to get the best QSAR correlation. Quantum chemical descriptors such as partially charged surface area, resonance energy between carbon and hydrogen in C-H bonds and topological descriptors such as Kier-Hall index have been found to influence the anticancer activity of the selected compounds. The QSAR correlation obtained in this work can be used to predict the anticancer activity of new drugs, without resorting to experimental studies. Keywords: anticancer activity, Recife Model 1 (RM1), quantum chemical quantitative structure activity relationship (qcQSAR); Multi-Linear Regression (MLR); 2010-11-09 Conference or Workshop Item NonPeerReviewed application/pdf en http://irep.iium.edu.my/4083/4/MSTC2010_IBRAHIM_acceptance_letter.pdf application/pdf en http://irep.iium.edu.my/4083/6/MSTC_2010_PARALLEL_TECHNICAL_SESSION__PROG_Book.pdf application/pdf en http://irep.iium.edu.my/4083/1/MSTC2010_nitrosourea_QSAR.pdf Ibrahim Ali , Noorbatcha and Mohd Salleh, Hamzah and Syed Osman Idid, Syed Zahir Idid (2010) Quantum chemical QSAR models to predict the anticancer activity of nitrosoureas. In: Malaysian Science and Technology Congress (MSTC2010), 9-11 November 2010, Petaling Jaya, Selangor. (Unpublished)
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English English
topic	TP248.13 Biotechnology
spellingShingle	TP248.13 Biotechnology Ibrahim Ali , Noorbatcha Mohd Salleh, Hamzah Syed Osman Idid, Syed Zahir Idid Quantum chemical QSAR models to predict the anticancer activity of nitrosoureas
description	Discovery of new anticancer drugs is a daunting task confronting the scientists for a long time. Computer aided methods can provide important insights in this direction. In this work we have investigated the anticancer activity of aliphatic nitrosoureas using quantum chemical quantitative structure activity relationship (qcQSAR) approach. In this method the structures of the active compounds are optimized using quantum chemical methods and several quantum chemical properties are calculated in the process. These properties are subjected to detailed statistical analysis and the selected descriptors are used in the construction of the quantitative structure activity relationship. Semi empirical quantum chemical RM1 (Recife Model 1) method was used for structure optimization, while Heuristic and Multi-Linear Regression (MLR) methods were applied to get the best QSAR correlation. Quantum chemical descriptors such as partially charged surface area, resonance energy between carbon and hydrogen in C-H bonds and topological descriptors such as Kier-Hall index have been found to influence the anticancer activity of the selected compounds. The QSAR correlation obtained in this work can be used to predict the anticancer activity of new drugs, without resorting to experimental studies. Keywords: anticancer activity, Recife Model 1 (RM1), quantum chemical quantitative structure activity relationship (qcQSAR); Multi-Linear Regression (MLR);
format	Conference or Workshop Item
author	Ibrahim Ali , Noorbatcha Mohd Salleh, Hamzah Syed Osman Idid, Syed Zahir Idid
author_facet	Ibrahim Ali , Noorbatcha Mohd Salleh, Hamzah Syed Osman Idid, Syed Zahir Idid
author_sort	Ibrahim Ali , Noorbatcha
title	Quantum chemical QSAR models to predict the anticancer activity of nitrosoureas
title_short	Quantum chemical QSAR models to predict the anticancer activity of nitrosoureas
title_full	Quantum chemical QSAR models to predict the anticancer activity of nitrosoureas
title_fullStr	Quantum chemical QSAR models to predict the anticancer activity of nitrosoureas
title_full_unstemmed	Quantum chemical QSAR models to predict the anticancer activity of nitrosoureas
title_sort	quantum chemical qsar models to predict the anticancer activity of nitrosoureas
publishDate	2010
url	http://irep.iium.edu.my/4083/ http://irep.iium.edu.my/4083/4/MSTC2010_IBRAHIM_acceptance_letter.pdf http://irep.iium.edu.my/4083/6/MSTC_2010_PARALLEL_TECHNICAL_SESSION__PROG_Book.pdf http://irep.iium.edu.my/4083/1/MSTC2010_nitrosourea_QSAR.pdf
first_indexed	2023-09-18T20:12:10Z
last_indexed	2023-09-18T20:12:10Z
_version_	1777407550161944576

Quantum chemical QSAR models to predict the anticancer activity of nitrosoureas

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