NDLI: QSAR study of antiproliferative drug against A549 by GA-MLR and SW-MLR methods

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QSAR study of antiproliferative drug against A549 by GA-MLR and SW-MLR methods

Content Provider	Directory of Open Access Journals (DOAJ)
Author	Somayeh Alimohammadi Aliasghar Hamidi Parinaz Pargolghasemi Nasim Nourani Mir Saleh Hoseininezhad-Namin
Abstract	Quantitative structure-activity relationship (QSAR) is the most extensively used computational methodology for analogue-based design. In this research, QSAR model was used to predict antiproliferative properties of 4-(2-fluorophenoxy) quinoline derivatives against A549(human lung adenocarcinoma). For this purpose, we used the multiple linear regressions (MLR) for the construction of a model to predict drug activity and Stepwise (SW) and genetic algorithm (GA) methods used to build the model. The data were selected from 31 molecules with specific pharmacological activity. They were divided into two sets train and test data. The resulting model was tested using statistical methods such as external test set and cross-validation to ensure its authenticity. The results showed that GA-MLR approach had good predictive power and higher data rates compared with SW-MLR (Q2LOO = 0.877, R2Train =0.933). The results obtained in this study can be used to design drugs with higher performance and pharmacological activity to treat lung cancer.
Related Links	http://www.chemrevlett.com/article_103559_c1335f2635a9e2498ca321bd5e7b0e99.pdf
ISSN	26767279
DOI	10.22034/crl.2020.220465.1037
Journal	Chemical Review and Letters
Issue Number	4
Volume Number	2
e-ISSN	26454947
Language	English
Publisher	Iranian Chemical Science and Technologies Association
Publisher Date	2019-01-01
Publisher Place	Iran
Access Restriction	Open
Subject Keyword	Chemistry Lung Cancer Quinoline Derivative Multiple Linear Regressions Genetic Algorithm
Content Type	Text
Resource Type	Article
Subject	Chemistry Organic Chemistry Physical and Theoretical Chemistry Inorganic Chemistry

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