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sayyadikordabadi, robabeh, Fallah Shojaei, Abdollah, Alizadehdakhel, Asghar, mohammadinargesi, leila, Ghasemi, Ghasem. (1399). Monte Carlo and QSAR Study on Biological Activity of Several Platinum (IV) Anti Cancer Drugs. , 18(1), 1-19. doi: 10.30495/jptc.2021.20871
robabeh sayyadikordabadi; Abdollah Fallah Shojaei; Asghar Alizadehdakhel; leila mohammadinargesi; Ghasem Ghasemi. "Monte Carlo and QSAR Study on Biological Activity of Several Platinum (IV) Anti Cancer Drugs". , 18, 1, 1399, 1-19. doi: 10.30495/jptc.2021.20871
sayyadikordabadi, robabeh, Fallah Shojaei, Abdollah, Alizadehdakhel, Asghar, mohammadinargesi, leila, Ghasemi, Ghasem. (1399). 'Monte Carlo and QSAR Study on Biological Activity of Several Platinum (IV) Anti Cancer Drugs', , 18(1), pp. 1-19. doi: 10.30495/jptc.2021.20871
sayyadikordabadi, robabeh, Fallah Shojaei, Abdollah, Alizadehdakhel, Asghar, mohammadinargesi, leila, Ghasemi, Ghasem. Monte Carlo and QSAR Study on Biological Activity of Several Platinum (IV) Anti Cancer Drugs. , 1399; 18(1): 1-19. doi: 10.30495/jptc.2021.20871

Monte Carlo and QSAR Study on Biological Activity of Several Platinum (IV) Anti Cancer Drugs

Journal of Physical & Theoretical Chemistry
دوره 18، شماره 1، خرداد 2021، صفحه 1-19  XML اصل مقاله (1004.84 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.30495/jptc.2021.20871
نویسندگان
robabeh sayyadikordabadi email 1؛ Abdollah Fallah Shojaei1؛ Asghar Alizadehdakhel1؛ leila mohammadinargesi2؛ Ghasem Ghasemiorcid 1
1Depatment of Chemistry and Chemical Engineering, Rasht Branch, Islamic Azad University, Rasht, Iran
2Department of Chemistry, Faculty of Sciences, University of Guilan, P.O.BOX 1914, Rasht, Iran
چکیده
QSAR investigations of some platinum (IV) derivatives were conducted using multiple linear regression (MLR) and artificial neural network (ANN) as modelling tools, along with simulated annealing (SA) and genetic algorithm (GA) optimization algorithms. In addition, CORAL software was used to correlate the biological activity to the structural parameters of the drugs. The obtained results from different approaches were compared and GA-ANN combination showed the best performance according to its correlation coefficient (R2) and mean sum square errors (RMSE). From the GA-ANN method, it was revealed that MTAS8e, ESpm05d, BElv3, MWC09, ESpm14u, BEHe2, RDF125e, and S3K are the most important descriptors. From Monte Carlo simulations, it was found that the presence of double bond, present of Platinum, number of chlorine connected to Pt, branching in molecular skeleton and presence of N and O atoms are the most important molecular features affecting the biological activity of the drug. It was concluded that simultaneous utilization of QSAR 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.
کلیدواژه‌ها
Platinum (IV) Antitumor Drugs؛ QSAR؛ Genetic Algorithm؛ Monte Carlo method
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