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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

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journal contribution
posted on 2020-05-18, 11:23 authored by Pujan N. Pandya, Sivakumar Prasanth Kumar, Kinjal Bhadresha, Chirag N. Patel, Saumya K. Patel, Rakesh M. Rawal, Archana U. Mankad

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.

Funding

This work was financially supported by the Financial Assistance Programme – Gujarat State Biotechnology Mission, Gujarat, India [grant number GSBTM/FAP/1443] and Department of Science and Technology [grant number GSBTM/MD/JDR/1409/2017-18].

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