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Article

Characterization of α-Glucosidase Inhibitors from Psychotria malayana Jack Leaves Extract Using LC-MS-Based Multivariate Data Analysis and In-Silico Molecular Docking

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Pharmacognosy Research Group, Department of Pharmaceutical Chemistry, Kulliyyah of Pharmacy, International Islamic University Malaysia, Kuantan 25200, Malaysia
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Department of Pharmacy, Faculty of Biological Sciences, University of Chittagong, Chittagong 4331, Bangladesh
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Faculty of Pharmacy, Airlangga University, Surabaya 60155, Indonesia
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Institute of Biological Sciences, Faculty of Science, University of Malaya, Kuala Lumpur 50603, Malaysia
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Center for Research in Biotechnology for Agriculture (CEBAR), Faculty of Science, University of Malaya, Kuala Lumpur 50603, Malaysia
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Pharmacognosy Group, Department of Pharmaceutical Biosciences, BMC, Uppsala University, SE-751 23 Uppsala, Sweden
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International Research Center for Food Nutrition and Safety, Jiangsu University, Zhenjiang 212013, China
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Authors to whom correspondence should be addressed.
Academic Editors: Young Hae Choi, Young Pyo Jang, Yuntao Dai and Luis Francisco Salomé-Abarca
Molecules 2020, 25(24), 5885; https://doi.org/10.3390/molecules25245885
Received: 6 November 2020 / Revised: 7 December 2020 / Accepted: 10 December 2020 / Published: 12 December 2020
Psychotria malayana Jack has traditionally been used to treat diabetes. Despite its potential, the scientific proof in relation to this plant is still lacking. Thus, the present study aimed to investigate the α-glucosidase inhibitors in P.malayana leaf extracts using a metabolomics approach and to elucidate the ligand–protein interactions through in silico techniques. The plant leaves were extracted with methanol and water at five various ratios (100, 75, 50, 25 and 0% v/v; water–methanol). Each extract was tested for α-glucosidase inhibition, followed by analysis using liquid chromatography tandem to mass spectrometry. The data were further subjected to multivariate data analysis by means of an orthogonal partial least square in order to correlate the chemical profile and the bioactivity. The loading plots revealed that the m/z signals correspond to the activity of α-glucosidase inhibitors, which led to the identification of three putative bioactive compounds, namely 5′-hydroxymethyl-1′-(1, 2, 3, 9-tetrahydro-pyrrolo (2, 1-b) quinazolin-1-yl)-heptan-1′-one (1), α-terpinyl-β-glucoside (2), and machaeridiol-A (3). Molecular docking of the identified inhibitors was performed using Auto Dock Vina software against the crystal structure of Saccharomyces cerevisiae isomaltase (Protein Data Bank code: 3A4A). Four hydrogen bonds were detected in the docked complex, involving several residues, namely ASP352, ARG213, ARG442, GLU277, GLN279, HIE280, and GLU411. Compound 1, 2, and 3 showed binding affinity values of −8.3, −7.6, and −10.0 kcal/mol, respectively, which indicate the good binding ability of the compounds towards the enzyme when compared to that of quercetin, a known α-glucosidase inhibitor. The three identified compounds that showed potential binding affinity towards the enzymatic protein in molecular docking interactions could be the bioactive compounds associated with the traditional use of this plant. View Full-Text
Keywords: Psychotria malayana Jack; type 2 diabetes; α-glucosidase inhibitors; LC-MS; metabolomics; molecular docking Psychotria malayana Jack; type 2 diabetes; α-glucosidase inhibitors; LC-MS; metabolomics; molecular docking
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MDPI and ACS Style

Nipun, T.S.; Khatib, A.; Ibrahim, Z.; Ahmed, Q.U.; Redzwan, I.E.; Saiman, M.Z.; Supandi, F.; Primaharinastiti, R.; El-Seedi, H.R. Characterization of α-Glucosidase Inhibitors from Psychotria malayana Jack Leaves Extract Using LC-MS-Based Multivariate Data Analysis and In-Silico Molecular Docking. Molecules 2020, 25, 5885. https://doi.org/10.3390/molecules25245885

AMA Style

Nipun TS, Khatib A, Ibrahim Z, Ahmed QU, Redzwan IE, Saiman MZ, Supandi F, Primaharinastiti R, El-Seedi HR. Characterization of α-Glucosidase Inhibitors from Psychotria malayana Jack Leaves Extract Using LC-MS-Based Multivariate Data Analysis and In-Silico Molecular Docking. Molecules. 2020; 25(24):5885. https://doi.org/10.3390/molecules25245885

Chicago/Turabian Style

Nipun, Tanzina S., Alfi Khatib, Zalikha Ibrahim, Qamar U. Ahmed, Irna E. Redzwan, Mohd Z. Saiman, Farahaniza Supandi, Riesta Primaharinastiti, and Hesham R. El-Seedi. 2020. "Characterization of α-Glucosidase Inhibitors from Psychotria malayana Jack Leaves Extract Using LC-MS-Based Multivariate Data Analysis and In-Silico Molecular Docking" Molecules 25, no. 24: 5885. https://doi.org/10.3390/molecules25245885

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