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Alizadehdakhel, Asghar, sayyadikordabadi, robabeh, Ghasemi, Ghasem, Motahary, Babak. (1400). Application of Monte Carlo Method and a novel modelling-optimization approach on QSAR Study of Etoposide drugs. , 18(2), 75-90. doi: 10.30495/jptc.2022.62210.1224
Asghar Alizadehdakhel; robabeh sayyadikordabadi; Ghasem Ghasemi; Babak Motahary. "Application of Monte Carlo Method and a novel modelling-optimization approach on QSAR Study of Etoposide drugs". , 18, 2, 1400, 75-90. doi: 10.30495/jptc.2022.62210.1224
Alizadehdakhel, Asghar, sayyadikordabadi, robabeh, Ghasemi, Ghasem, Motahary, Babak. (1400). 'Application of Monte Carlo Method and a novel modelling-optimization approach on QSAR Study of Etoposide drugs', , 18(2), pp. 75-90. doi: 10.30495/jptc.2022.62210.1224
Alizadehdakhel, Asghar, sayyadikordabadi, robabeh, Ghasemi, Ghasem, Motahary, Babak. Application of Monte Carlo Method and a novel modelling-optimization approach on QSAR Study of Etoposide drugs. , 1400; 18(2): 75-90. doi: 10.30495/jptc.2022.62210.1224

Application of Monte Carlo Method and a novel modelling-optimization approach on QSAR Study of Etoposide drugs

Journal of Physical & Theoretical Chemistry
دوره 18، شماره 2 - شماره پیاپی 3، بهمن 2021، صفحه 75-90  XML اصل مقاله (949.79 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.30495/jptc.2022.62210.1224
نویسندگان
Asghar Alizadehdakhel1؛ robabeh sayyadikordabadi email 2؛ Ghasem Ghasemi2؛ Babak Motahary3
1Department of Chemistry and Chemical Engineering, Rasht Branch, Islamic Azad University, Rasht, Iran
2Department of Chemistry and Chemical Engineering, Rasht Branch, Islamic Azad University, Rasht, Iran.
3Department of Computer Engineering, Rasht Branch, Islamic Azad University, Rasht, Iran
چکیده
Monte Carlo and Multiple Linear Regression (MLR) and Imperialist Competitive Algorithm (ICA) were used to select the most appropriate descriptors. Examining the quality of the model by comparing the mean squared error (MSE) and correlation coefficient (R2), indicated that 140 is the most appropriate number of empires for the gas phase . In the Monte Carlo method, CORAL software was used and the data were randomly divided into training, calibration, and test subsets in three splits. The correlation coefficient (R2), cross-validated correlation coefficient (Q2) and standard error of the model were calculated to be respectively 0.9301, 0.7377, and 0.595 for the test set with an optimum threshold of 4. It was concluded that simultaneous utilization of MLR-ICA and Monte Carlo method can lead to a more comprehensive understanding of the relation between physico-chemical, structural or theoretical molecular descriptors of drugs to their biological activities and facilitate designing of new drugs.
کلیدواژه‌ها
Etoposides؛ QSAR؛ ICA Algorithm؛ Monte Carlo method
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