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Identification of promising compounds from curry tree with cyclooxygenase inhibitory potential using a combination of machine learning, molecular docking, dynamics simulations and binding free energy calculations
Molecular Simulation ( IF 2.1 ) Pub Date : 2020-05-18 , DOI: 10.1080/08927022.2020.1764552
Pujan N. Pandya 1 , Sivakumar Prasanth Kumar 2 , Kinjal Bhadresha 2 , Chirag N. Patel 1 , Saumya K. Patel 1 , Rakesh M. Rawal 2 , Archana U. Mankad 1
Affiliation  

ABSTRACT Murraya koenigii (Linn.) Spreng, commonly known as curry leaf tree, is popular as a condiment and spice among Asian countries. Ethnobotanical studies suggest that certain phytochemicals in different parts of the plant are involved in anti-inflammatory, anti-oxidant and anti-cancer activities. There is a knowledge gap in connecting the ethnobotanical applications of M. koenigii, identification of chief phytochemicals through computational approaches and and evaluation of phytochemical’s effect on cancer cell lines. We present here a comprehensive study to identify the phytochemicals responsible for anti-inflammation using random forest (RF) models, the interactions with COX-1 and COX-2 enzymes using molecular docking, dynamics simulation and free energy calculations. The RF models prioritised four phytochemicals viz. girinimbine, murrayanine, murrastinine-B and mukolidine with COX-1 and COX-2 binding potential. These phytochemicals developed key contacts with COX targets which were largely retained in the trajectories of the dynamics simulations. Phytochemicals ranking based on the binding free energy suggested that girinimbine (a carbazole alkaloid) is selective towards COX-2 supported by the experimental studies on COX anti-inflammation. Cytotoxicity assessment on the breast cancer cell line MDA-MB-231 illustrated that the presence of this phytochemical in root, stem and leaf (IC50 value: 0.006 µg/ml) parts highlight its role as a COX-2 inhibitor.

中文翻译:

结合机器学习、分子对接、动力学模拟和结合自由能计算,从具有环氧合酶抑制潜力的咖喱树中鉴定出有前景的化合物

摘要 Murraya koenigii (Linn.) Spreng,俗称咖喱叶树,作为调味品和香料在亚洲国家很受欢迎。民族植物学研究表明,植物不同部位的某些植物化学物质参与抗炎、抗氧化和抗癌活动。在连接 M. koenigii 的民族植物学应用、通过计算方法识别主要植物化学物质以及评估植物化学物质对癌细胞系的影响方面存在知识差距。我们在这里提出了一项综合研究,以使用随机森林 (RF) 模型确定负责抗炎的植物化学物质,使用分子对接、动力学模拟和自由能计算与 COX-1 和 COX-2 酶的相互作用。RF 模型优先考虑四种植物化学物质,即。吉林宾,murrayanine、murrastinine-B 和 mukolidine 具有 COX-1 和 COX-2 结合潜力。这些植物化学物质与 COX 目标形成了关键联系,这些目标在很大程度上保留在动力学模拟的轨迹中。基于结合自由能的植物化学物质排名表明,吉林宾(一种咔唑生物碱)对 COX-2 具有选择性,这得到了 COX 抗炎实验研究的支持。对乳腺癌细胞系 MDA-MB-231 的细胞毒性评估表明,这种植物化学物质在根、茎和叶(IC50 值:0.006 µg/ml)部分的存在突出了其作为 COX-2 抑制剂的作用。基于结合自由能的植物化学物质排名表明,吉林宾(一种咔唑生物碱)对 COX-2 具有选择性,这得到了 COX 抗炎实验研究的支持。对乳腺癌细胞系 MDA-MB-231 的细胞毒性评估表明,这种植物化学物质在根、茎和叶(IC50 值:0.006 µg/ml)部分的存在突出了其作为 COX-2 抑制剂的作用。基于结合自由能的植物化学物质排名表明,吉林宾(一种咔唑生物碱)对 COX-2 具有选择性,这得到了 COX 抗炎实验研究的支持。对乳腺癌细胞系 MDA-MB-231 的细胞毒性评估表明,这种植物化学物质在根、茎和叶(IC50 值:0.006 µg/ml)部分的存在突出了其作为 COX-2 抑制剂的作用。
更新日期:2020-05-18
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