QSAR study of ACK1 inhibitors by genetic algorithm–multiple linear regression (GA–MLR)
Joint Authors
Pourbasheer, Islam
Aalizadah, Rida
Ganjali, Muhammad Rida
Norouzi, Parviz
Shadmanesh, Javad
Source
Journal of Saudi Chemical Society
Issue
Vol. 18, Issue 5 (31 Dec. 2014), pp.681-688, 8 p.
Publisher
Publication Date
2014-12-31
Country of Publication
Saudi Arabia
No. of Pages
8
Main Subjects
Topics
Abstract EN
In this work, a quantitative structure–activity relationship (QSAR) model was used to predict the ACK1 inhibitory activities.
A data set of 37 compounds with known ACK1 inhibitory activities was used.
The data set was divided into two subsets of training and test sets, based on hierarchical clustering technique.
Genetic algorithm was applied to select the respective variables to build the model in the next step.
Multiple linear regressions (MLR) were employed to give the QSAR model.
The squared cross-validated correlation coefficient for leave-one-out ðQ2 LOOÞ of 0.712 and squared correlation coefficient ðR2 trainÞ of 0.806 were obtained for the training set compounds by GA–MLR model.
The given model performed a good stability and predictability when it was verified by internal and external validation.
The predicted results from this study can lead to design of better and potent ACK1 inhibitors.
American Psychological Association (APA)
Pourbasheer, Islam& Aalizadah, Rida& Ganjali, Muhammad Rida& Norouzi, Parviz& Shadmanesh, Javad. 2014. QSAR study of ACK1 inhibitors by genetic algorithm–multiple linear regression (GA–MLR). Journal of Saudi Chemical Society،Vol. 18, no. 5, pp.681-688.
https://search.emarefa.net/detail/BIM-414094
Modern Language Association (MLA)
Pourbasheer, Islam…[et al.]. QSAR study of ACK1 inhibitors by genetic algorithm–multiple linear regression (GA–MLR). Journal of Saudi Chemical Society Vol. 18, no. 5 (2014), pp.681-688.
https://search.emarefa.net/detail/BIM-414094
American Medical Association (AMA)
Pourbasheer, Islam& Aalizadah, Rida& Ganjali, Muhammad Rida& Norouzi, Parviz& Shadmanesh, Javad. QSAR study of ACK1 inhibitors by genetic algorithm–multiple linear regression (GA–MLR). Journal of Saudi Chemical Society. 2014. Vol. 18, no. 5, pp.681-688.
https://search.emarefa.net/detail/BIM-414094
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 687-688
Record ID
BIM-414094