ABSTRACT
The present study used in vitro and in silico techniques, as well as the metabolomics approach to characterise α-glucosidase inhibitors from different fractions of Clinacanthus nutans. C. nutans is a medicinal plant belonging to the Acanthaceae family, and is traditionally used to treat diabetes in Malaysia. n-Hexane, n-hexane: ethyl acetate (1:1, v/v), ethyl acetate, ethyl acetate: methanol (1:1, v/v), and methanol fractions were obtained via partitioning of the 80% methanolic crude extract. The in vitro α-glucosidase inhibitory activity was analyzed using all the fractions collected, followed by profiling of the metabolites using liquid chromatography combined with mass spectrometry. The partial least square (PLS) statistical model was developed using the SIMCA P+14.0 software and the following four inhibitors were obtained: (1) 4,6,8-Megastigmatrien-3-one; (2) N-Isobutyl-2-nonen-6,8-diynamide; (3) 1',2'-bis(acetyloxy)-3',4'-didehydro-2'-hydro-ß, ψ-carotene; and (4) 22-acetate-3-hydroxy-21-(6-methyl-2,4-octadienoate)-olean-12-en-28-oic acid. The in silico study performed via molecular docking with the crystal structure of yeast isomaltase (PDB code: 3A4A) involved a hydrogen bond and some hydrophobic interactions between the inhibitors and protein. The residues that interacted include ASN259, HID295, LYS156, ARG335, and GLY209 with a hydrogen bond, while TRP15, TYR158, VAL232, HIE280, ALA292, PRO312, LEU313, VAL313, PHE314, ARG315, TYR316, VAL319, and TRP343 with other forms of bonding.
ABSTRACT
BACKGROUND: Clinacanthus nutans (C. nutans) is an Acanthaceae herbal shrub traditionally consumed to treat various diseases including diabetes in Malaysia. This study was designed to evaluate the α-glucosidase inhibitory activity of C. nutans leaves extracts, and to identify the metabolites responsible for the bioactivity. METHODS: Crude extract obtained from the dried leaves using 80% methanolic solution was further partitioned using different polarity solvents. The resultant extracts were investigated for their α-glucosidase inhibitory potential followed by metabolites profiling using the gas chromatography tandem with mass spectrometry (GC-MS). RESULTS: Multivariate data analysis was developed by correlating the bioactivity, and GC-MS data generated a suitable partial least square (PLS) model resulting in 11 bioactive compounds, namely, palmitic acid, phytol, hexadecanoic acid (methyl ester), 1-monopalmitin, stigmast-5-ene, pentadecanoic acid, heptadecanoic acid, 1-linolenoylglycerol, glycerol monostearate, alpha-tocospiro B, and stigmasterol. In-silico study via molecular docking was carried out using the crystal structure Saccharomyces cerevisiae isomaltase (PDB code: 3A4A). Interactions between the inhibitors and the protein were predicted involving residues, namely LYS156, THR310, PRO312, LEU313, GLU411, and ASN415 with hydrogen bond, while PHE314 and ARG315 with hydrophobic bonding. CONCLUSION: The study provides informative data on the potential α-glucosidase inhibitors identified in C. nutans leaves, indicating the plant's therapeutic effect to manage hyperglycemia.
