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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Academic Journals
2011
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/14650/ http://irep.iium.edu.my/14650/ http://irep.iium.edu.my/14650/ http://irep.iium.edu.my/14650/1/QSAR_AJB_2011_published.pdf |
| Summary: | 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). |
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