• Yunita Eka Puspitasari Department of Fish Product Technology, Faculty of Fisheries and Marine Sciences, Universitas Brawijaya
  • Jeny Ernawati Tambunan Department of Fish Product Technology, Faculty of Fisheries and Marine Sciences, Universitas Brawijaya
  • Hardoko Hardoko Department of Fish Product Technology, Faculty of Fisheries and Marine Sciences, Universitas Brawijaya
Keywords: α-amilase, triterpenoid, Ceriops decandra


α-amylase has a pivotal role in catalyzing the cleavage of α-1,4-glycosidic bonds of polysaccharides to produce oligosaccharides. The inhibition of α-amylase delays the breakdown of carbohydrates, causing a reduction of blood glucose level absorption in diabetes patients. The exploration of α-amylase inhibitors has attracted because society assumed that utilizing herbal medicine reduced the side effect of prescribed drugs. Mangrove from genus Ceriops have been used as antidiabetic, but the mechanism as α-amylase inhibitors has not been reported. Consumption of leaves extract of C.decandra reduced blood glucose levels in diabetic rats, and triterpenoids have been identified from the leaves. With this in mind, this study aims to predict the molecular interactions between α-amylase (PDB ID: 4GQR) and the inhibitors, triterpenoid identified in C.decandra leaves, and to evaluate the potency of triterpenoid as α-amylase inhibitor. There are five triterpenoids identified in C.decandra leaves used as ligand tests, including lupenone, betulin, betulonic acid, betulinic acid, and lupeol. The descriptive method was applied in this investigation. This study was carried out from June to September 2022. Based on the molecular interactions, the binding affinity of triterpenoids was lower than the native ligand and control ligand. Lupenone, lupeol, betalonic acid, and betulinic acid inhibited α-amylase activity by non-competitive inhibition. It was predicted that betulin inhibited α-amylase activity through competitive inhibition


Download data is not yet available.


Ruang-Areerate, P. et al. (2022). Comparative Analysis and Phylogenetic Relationships of Ceriops Species (Rhizophoraceae) and Avicennia lanata (Acanthaceae): Insight into the Chloroplast Genome Evolution between Middle and Seaward Zones of Mangrove Forests. Biology, 11(3),

Wiradana, P.A., Sundra, I.K., Kurniawan, S.B., Abdullah, S.R.S., Alamsjah, M.A., Fauzulimron, M. (2021). Monitoring of Diversity, Characteristic, Threatening Rate and Potency of Mangrove Vegetation in Denpasar, Bali, Indonesia. Plant Archives, 21(1): 592–599.

Revathi, P., Jeyaseelan, T.S., Thirumalaikolundusubramanian, P., Prabhu, N. (2014). An overview of antidiabetic profile of mangrove plants. International Journal of Pharmacy and Pharmaceutical Sciences, 6(3): 1–5

Wang, H., Li, M.-Y., Wu, J. (2012). Chemical Constituents and Some Biological Activities of Plants from the Genus Ceriops. Chemistry & Biodiversity, 9:1–11.

Ramadhan, R., Phuwapraisirisan, P., Kusuma, I.W., Amirta, R. (2020). Ethnopharmacological Evaluation of Selected East Kalimantan Flora for Diabetes Therapy: The Isolation of Lupane Triterpenoids as α-glucosidase Inhibitors from Ceriops tagal (PERR) C.B.ROBB. Rasayan Journal of Chemistry, 13(3): 1727–1734.

Ranjana., Jadhav, B.L. (2019). Phytochemical Composition, in vitro Studies on α-Amylase and α-Glucosidase Inhibitory Activity of Selected Mangrove Plants. International Journal of Pharmaceutical Sciences and Drug Research, 11(5): 181–186.

Canusa, B.S. et al. (2021). α-Glucosidase Inhibitors from the Bark Extract of Ethno-Antidiabetic Ceriops tagal (Perr.) C.B. Rob. Philippine Journal of Science, 151(S1): 25–60

Nabeel, M.A., Kathiresan, K. Manivannan, S. (2010). Antidiabetic activity of the mangrove species Ceriops decandra in alloxan-induced diabetic rats. Journal of Diabetes, 2(2): 97–103.

Oboh, G., Ademosun, A.O., Ayeni, P.O., Omojokun, O.S., Bello, F. (2015). Comparative effect of quercetin and rutin on α-amylase. Comp Clin Pathol, 24: 1103–1110.

Derosa, G., Maffioli, P. (2012). α-Glucosidase inhibitors and their use in clinical practice. Archives of Medical Science, 8(5): 899–906.

Claereboudt, E.J.S. et al. (2019). Triterpenoids in echinoderms: Fundamental differences in diversity and biosynthetic pathways. Marine Drugs, 17(6). 10.3390/md17060352.

Moses, T., Papadopoulou, K.K., Osbourn, A. (2014). Metabolic and functional diversity of saponins, biosynthetic intermediates and semi-synthetic derivatives. Critical Reviews in Biochemistry and Molecular Biology, 49(6): 439–462.

Perez, J., Chien-Shen, C., Ragasa, C.Y. (2017). Triterpenes from Ceriops Decandra (Griff.) W. Theob. Asian Journal of Pharmaceutical and Clinical Research, 10(11):244–246.

Ponglimanont, C., Thongdeeying, P. (2005). Lupane-triterpene esters from the leaves of Ceriops decandra (griff.) Ding Hou. Australian Journal of Chemistry, 58(8): 615–618, 2005.

Yin, Z., Zhang, W., Feng, F., Zhang, Y., Kang, W. (2014). α-Glucosidase inhibitors isolated from medicinal plants. Food Science and Human Wellness, 3:136–174.

Puspitasari, Y.E., Hardoko, H., Sulistiyati, T.D., Fajrin, N.A., Tampubolon, H.O. (2022). Phytochemical Compound Identification of Mangrove Leaves Sonneratia alba and in Silico Analysis as Antidiabetic. Jurnal Perikanan dan Kelautan, 27(2):241–248.

Lipinski, C.A., Lombardo, F., Dominy, B.W., Feeney, P.J. (1997). Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Advanced Drug Delivery Reviews, 23: 3–25.

Tian, S., Wang, J., Li, Y., Li, D., Xu, L., Hou, T. (2015). The application of in silico drug-likeness predictions in pharmaceutical research. Advanced Drug Delivery Reviews, 86: 2–10.

Ntie-Kang, F. (2013). An in silico evaluation of the ADMET profile of the StreptomeDB database. SpringerPlus, 2(1): 1–11.

Drwal, M.N., Banerjee, P., Dunkel, M., Wettig, M.R., Preissner, R. (2014). ProTox: A web server for the in silico prediction of rodent oral toxicity. Nucleic Acids Research, 42(W1): 53–58.

Banerjee, P., Eckert, A.O., Schrey, A.K., Preissner, R. (2018). ProTox-II: A webserver for the prediction of toxicity of chemicals. Nucleic Acids Research, 46(W1):W257–W263.

Banerjee, P., Dehnbostel, F.O., Preissner, R. (2018). Prediction is a balancing act: Importance of sampling methods to balance sensitivity and specificity of predictive models based on imbalanced chemical data sets. Frontiers in Chemistry, 6:1–11.

Trott, O., Olson, A.J. (2009). AutoDock Vina: Improving the Speed and Accuracy of Docking with a New Scoring Function, Efficient Optimization, and Multithreading. Journal of computational chemistry, 31(455): 455–461.

Rafey, A., et al. (2021). Analysis of plant origin antibiotics against oral bacterial infections using in vitro and in silico techniques and characterization of active constituents. Antibiotics, 10(12).

Brayer, G.D., et al. (2000). Subsite mapping of the human pancreatic α-amylase active site through structural, kinetic, and mutagenesis techniques. Biochemistry, 39(16): 4778–4791.

Casacchia, T., et al. (2019). A pilot study on the nutraceutical properties of the Citrus hybrid Tacle® as a dietary source of polyphenols for supplementation in metabolic disorders. Journal of Functional Foods, 52: 370–381.

Gaspersz, N., Sohilait, M.R. (2019). Penambatan Molekuler α, β, and γ-Mangostin Sebagai Inhibitor α -Amilase Pankreas Manusia. Indo. J. Chem. Res, 6(2): 59–66.

How to Cite
Puspitasari, Y. E., Tambunan, J. E., & Hardoko, H. (2022). IN SILICO STUDY OF TRITERPENOID IDENTIFIED FROM Ceriops decandra LEAVES AS INHIBITORS OF α-AMYLASE. Asian Journal of Aquatic Sciences, 5(3), 429-439.