In silico Studies of some potential anti-cancer agents on M19-MEL cell line

IF 2.4 Q3 CHEMISTRY, MULTIDISCIPLINARY Moroccan Journal of Chemistry Pub Date : 2021-02-14 DOI:10.48317/IMIST.PRSM/MORJCHEM-V9I2.20575
A. B. Umar
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引用次数: 2

Abstract

The resistance of melanoma cancer cells to the known treatments has become a barrier to the success of chemotherapy.  In this research, a quantitative evaluation of the structure-activity relationship (QSAR) was carried out on 57 anti-cancer compounds and some selected potent compounds were screened through Lipinski’s rule and docked. Genetic function algorithm (GFA) was adopted in variables selection and Multiple linear regression (MLR) was used to generate the model. The built QSAR model showed good statistical parameters (( (0.904), (0.885), Q 2 cv (0.873) and (0.779)). The cR⁠ 2 ⁠ P for Y-randomization is 0.749 and the applicability domain was also determined. The predictive ability of the model was found to be satisfactory and could be used to predict the anti-cancer activity of compounds on M19 MEL cell line. 4 most potent compounds were selected among the data set and screened through Lipinski's rule of five filters for oral bioavailability, ADMET risk filter for a drug like features. Later, V600E-BRAF, a known melanoma cancer target was used for docking. Based on the interaction energy and types of interactions involved, the selected compounds were identified as the best hits against V600E-BRAF. This research would help in the lead identification and design of novel drugs.
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一些潜在抗癌药物在M19-MEL细胞系上的硅片研究
黑色素瘤癌细胞对已知治疗方法的耐药性已经成为化疗成功的障碍。本研究对57种抗癌化合物的构效关系(QSAR)进行了定量评价,并通过Lipinski规则筛选筛选出部分有效化合物并进行了对接。变量选择采用遗传函数算法(GFA),模型生成采用多元线性回归(MLR)。建立的QSAR模型具有良好的统计参数((0.904),(0.885),q2 cv(0.873)和(0.779))。y随机化的cR (2) P为0.749,并确定了该方法的适用范围。该模型的预测能力令人满意,可用于预测化合物对M19 MEL细胞株的抗癌活性。从数据集中选择了4种最有效的化合物,并通过Lipinski的口服生物利用度五过滤器规则进行筛选,ADMET风险过滤器用于药物特征。随后,利用已知的黑色素瘤肿瘤靶点V600E-BRAF进行对接。根据所涉及的相互作用能和相互作用类型,确定了所选化合物对V600E-BRAF的最佳打击。这项研究将有助于新药物的先导鉴定和设计。
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来源期刊
Moroccan Journal of Chemistry
Moroccan Journal of Chemistry CHEMISTRY, MULTIDISCIPLINARY-
CiteScore
3.40
自引率
9.10%
发文量
0
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