Profiling Metabolites through Chemometric Analysis in Orthosiphon aristatus Extracts as α-Glucosidase Inhibitory Activity and In Silico Molecular Docking

https://doi.org/10.22146/ijc.71334

Faizal Maulana(1), Alfari Andiqa Muhammad(2), Ali Umar(3), Fachrur Rizal Mahendra(4), Muhammad Musthofa(5), Waras Nurcholis(6*)

(1) Department of Chemistry, Faculty of Mathematics and Natural Sciences, IPB University, Jl. Tanjung Kampus IPB Dramaga, Bogor 16680, Indonesia
(2) Department of Biochemistry, Faculty of Mathematics and Natural Sciences, IPB University, Jl. Tanjung Kampus IPB Dramaga, Bogor 16680, Indonesia
(3) Department of Chemistry, Faculty of Mathematics and Natural Sciences, IPB University, Jl. Tanjung Kampus IPB Dramaga, Bogor 16680, Indonesia
(4) Department of Biochemistry, Faculty of Mathematics and Natural Sciences, IPB University, Jl. Tanjung Kampus IPB Dramaga, Bogor 16680, Indonesia
(5) Department of Biochemistry, Faculty of Mathematics and Natural Sciences, IPB University, Jl. Tanjung Kampus IPB Dramaga, Bogor 16680, Indonesia
(6) Department of Biochemistry, Faculty of Mathematics and Natural Sciences, IPB University, Jl. Tanjung Kampus IPB Dramaga, Bogor 16680, Indonesia Tropical Biopharmaca Research Center, IPB University, Jl. Taman Kencana Kampus IPB Taman Kencana, Bogor 16128, Indonesia
(*) Corresponding Author

Abstract


Orthosiphon aristatus (called kumis kucing in Indonesia) is a valuable herb for diabetes mellitus treatment. In this study, LC-MS/MS and PCA analyses were used to investigate the metabolite profile, classify O. aristatus extracts, and assess the inhibitory activity of a-glucosidase and the probable bioactive compounds through in silico study. Results showed that the methanol and ethanol extracts of O. aristatus were active in α-glucosidase inhibitory activity. Both extracts contained 86 compounds as known from the LC-MS/MS analysis. PCA analysis identified 10 metabolites that correlated with α-glucosidase inhibitory activity. Results of in silico analysis obtained rosmarinic acid compound potentially act as anti-diabetic activity, which can be developed for further research.


Keywords


diabetic; in silico; Orthosiphon aristatus; metabolomics; PCA

Full Text:

Full Text PDF


References

[1] International Diabetes Federation, 2019, IDF Diabetes Atlas, 9th Ed., International Diabetes Federation, Belgium.

[2] Aquarista, N.C., 2016, Differences characteristics patients diabetes mellitus type 2 with and without coronary heart disease, JBE, 5 (1), 37–47.

[3] Beagley, J., Guariguata, L., Weil, C., and Motala, A.A., 2014, Global estimates of undiagnosed diabetes in adults, Diabetes Res. Clin. Pract., 103 (2), 150–160.

[4] Miranda-Díaz, A.G., Pazarín-Villaseñor, L., Yanowsky-Escatell, F.G., and Andrade-Sierra, J., 2016, Oxidative stress in diabetic nephropathy with early chronic kidney disease, J. Diabetes Res., 2016, 7047238.

[5] Lathifah, N.L., 2017, Hubungan durasi penyakit dan kadar gula darah dengan keluhan subyektif penderita diabetes melitus, JBE, 5 (2), 231–239.

[6] Ullah, F., Afridi, A.K., Rahim, F., Ashfaq, M., Khan, S., Shabbier, G., and Ur Rahman, S., 2015, Knowledge of diabetic complication in patients with diabetes mellitus, J. Ayub Med. Coll. Abbottabad, 27 (2), 360–363.

[7] Arman, M.S.I., Al Mahmud, A., Mahmud, H.R., and Reza, A.S.M.A., 2019, Free radical, oxidative stress and diabetes mellitus: A mini review, Discovery Phytomed., 6 (3), 99–101.

[8] Tiwari, B.K., Pandey, K.B., Abidi, A.B., and Rizvi, S.I., 2013, Markers of oxidative stress during diabetes mellitus, J. Biomarkers, 2013, 378790.

[9] Chatsumpun, N., Sritularak, B., and Likhitwitayawuid, K., 2017, New bioflavonoids with α-glucosidase and pancreatic lipase inhibitory activities from Boesenbergia rotunda, Molecules, 22 (11), 1862.

[10] Dhabi, A.S., Bhatt, N.R., and Shah, M., 2013, Voglibose: An alpha glucosidase inhibitor, J. Clin. Diagn. Res., 7 (12), 3023–3027.

[11] Hasimun, P., Adnyana, I.K., Valentina, R., and Lisnasari, E., 2016, Potential alpha glucosidase inhibitor from selected zingiberaceae family, Asian J. Pharm. Clin. Res., 9 (1), 164–167.

[12] Yuan, H., Ma, Q., Ye, L., Piao, G., 2016, The traditional medicine and modern from natural products. Molecules, 21 (559), 1–18.

[13] Mohamed, E.A.H., Siddqui, M.J.A., Ang, L.F., Sadikun, A., Chan, S.H., Tan, S.C., Asmawi, M.Z., and Yam, M.F., 2012, Potent α-glucosidase and α-amylase inhibitory activities of standardized 50% ethanolic extracts and sinensetin from Orthosiphon stamineus Benth as anti-diabetic mechanism, BMC Complementary Altern. Med., 12 (1), 176.

[14] Ashraf, K., Sultan, S., and Adam, A., 2018, Orthosiphon stamineus Benth. is an outstanding food medicine: Review of phytochemical and pharmacological activities, J. Pharm. BioAllied Sci., 10 (3), 109–118.

[15] Murugesu, S., Ibrahim, Z., Ahmed, Q.U., Nik Yusoff, N.I., Uzir, B.F., Perumal, V., Abas, F., Saari, K., El-Seedi, H., and Khatib, A., 2018, Characterization of α-glucosidase inhibitors from Clinacanthus nutans Lindau leaves by gas chromatography-mass spectrometry-based metabolomics and molecular docking simulation, Molecules, 23 (9), 2402.

[16] Guedes, J.A.C., Filho, E.G.A., Silva, M.F.S, Rodrigues, T.H.S., Ramires, C.M.C., Lima, M.A.C., Silva, G.S., Pessoa, C.O., Canuto, K.M., Brito, E.S., Alves, R.E., Nascimento, R.F., and Zocolo, G.J., 2020, GC-MS-based metabolomic profiles combined with chemometric tools and cytotoxic activities of non-polar leaf extract of Spondias mombin L. and Spondias tuberosa Arr. Cam, J. Braz. Chem. Soc., 31 (2), 331–340.

[17] Mishra, S., Sarkar, U., Taraphder, S., Datta, S., Swain, D.P., Saikhom, R., Panda, S., and Laishram, M., 2017, Multivariate statistical data analysis- Principal component analysis, Int. J. Livest. Res., 7 (5), 60–78.

[18] Aziz, Z., Yuliana, D.N., Simanjuntak, P., Rafi, M., Mulatsari, E., and Abdilah, S., 2021, Investigation of yacon leaves (Smallanthus sonchifolius) for α-glucosidase inhibitors using metabolomics and in silico approach, Plant Foods Hum. Nutr., 76 (4), 487–493.

[19] Elhawary, S.S., Younis, Y.I., Bishbishy, E.H.M., and Khattab, R.A., 2018, LC-MS/MS-based chemometric analysis of phytochemical diversity in 13 Ficus spp. (Moraceae): Correlation to their in vitro antimicrobial and in silico quorum sensing inhibitory activities, Ind. Crops Prod., 126, 261–271.

[20] Rather, M.A., Dutta, S., Guttula, P.K., Dhandare, B.C., Yusufzai, S.I., and Zafar, M.I., 2020, Structural analysis, molecular docking and molecular dynamics simulations of G-protein-coupled receptor (kisspeptin) in fish, J. Biomol. Struct. Dyn., 38 (8), 2422–2439.

[21] Zafar, M., Khan, H., Rauf, A., Khan, A., and Lodhi, M.A., 2016, In silico study of alkaloid as α-glucosidase inhibitors: Hope for the discovery of effective lead compounds, Front. Endocrinol., 7, 153.

[22] Krieger, E., and Vriend, G., 2015, New ways to boost molecular dynamics simulations, J. Comput. Chem., 36 (13), 996–1007.

[23] Rafi, M., Purwakusumah, E.D., Ridwan, T., Barus, B., Sutandi, A., and Darusman, L.K., 2015, Geographical classification of Java tea (Orthosiphon stamineus) from Java Island by FTIR spectroscopy combined with canonical variate analysis, JSM, 23 (1), 25–31.

[24] Truong, D.H., Nguyen, D.H., Ta, N.T., Bui, A.V., Do, T.H., and Nguyen, H.C., 2019, Evaluation of the use of different solvents for phytochemical constituents, antioxidants, and in vitro anti-inflammatory activities of Severinia buxifolia, J. Food Qual., 2019, 8178294.

[25] Himani, B., Seema, B., Bhole, N., Mayank, Y., Vinod, S., and Mamta, S., 2013, Misai kuching: A glimpse of maestro, Int. J. Pharm. Sci. Rev. Res., 22 (2), 55–59.

[26] Şöhretoğlu, D., and Sari, S., 2019, Flavonoids as alpha-glucosidase inhibitors: Mechanistic approaches merged with enzyme kinetics and molecular modelling, Phytochem. Rev., 19 (5), 1081–1092.

[27] Jolliffe, I.T., and Cadima, J., 2016, Principal component analysis: A review and recent developments, Philos. Trans. R. Soc., A, 374 (2065), 20150202.

[28] Zobayer, N., and Aowlad Hossain, A.B.M., 2018, In silico characterization and homology modelling of histamine receptors, J. Biol. Sci., 18 (4), 178–191.

[29] Ueno, G., Shimada, A., Yamashita, E., Hasegawa, K., Kumasaka, T., Shinzawa-Itoh, K., Yoshikawa, S., Tsukihara, T., and Yamamoto, M., 2019, Low-dose X-ray structure analysis of cytochrome c oxidase utilizing high-energy X-rays, J. Synchrotron Radiat., 26 (4), 912–921.

[30] Iman, M., Saadabadi, A., and Davood, A., 2015, Molecular docking analysis and molecular dynamics simulation study of ameltolide analogous as a sodium channel blocker, Turk. J. Chem., 39, 306–316.

[31] Chen, H., Zhou, X., Gao, Y., Chen, H., and Zhou, J., 2017, “Fragment-Based Drug Design: Strategic Advances and Lessons Learned” in Comprehensive Medicinal Chemistry III, Eds. Chackalamannil S., Rotella D., Ward S.E., Elsevier, Oxford, 212–232.

[32] Lipinski, C.A., Lombardo, F., Dominy, B.W., and Feeney, P.J., 2012, Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings, Adv. Drug Delivery Rev., 64 (Suppl.), 4–17.

[33] Bickerton, G.R., Paolini, G.V., Besnard, J., Muresan, S., and Hopkins, A.L., 2012, Quantifying the chemical beauty of drugs, Nat. Chem., 4 (2), 90–98.

[34] Doak, B.C., Over, B., Giordanetto, F., and Kihlberg, J., 2014, Oral druggable space beyond the rule of 5: Insights from drugs and clinical candidates, Chem. Biol., 21 (9), 1115–1142.

[35] Benet, L.Z., Hosey, C.M., Ursu, O., and Oprea, T.I., 2016, BDDCS, the Rule of 5 and drugability, Adv. Drug Delivery Rev., 101, 89–98.

[36] Chagas, C.M., Moss, S., and Alisaraie, L., 2018, Drug metabolites and their effects on the development of adverse reactions: Revisiting Lipinski’s Rule of Five, Int. J. Pharm., 549 (1-2), 133–149.

[37] Chua, S.L., Lau, C.H., Chew, C.Y., Ismail, N.I.M., and Sootorgun, N., 2017, Phytochemical profile of Orthosiphon aristatus extracts after storage: Rosmarinic acid and other caffeic acid derivatives, Phytomedicine, 39, 49–55.

[38] Runtuwene, J., Cheng, K.C., Asakawa, A., Amitani, H., Amitani, M., Morinaga, A., Takimoto, Y., Kairupan, B.H.R., and Inui, A, 2016, Rosmarinic acid ameliorates hyperglycemia and insulin sensitivity in diabetic rats, potentially by modulating the expression of PEPCK and GLUT4, Drug Des., Dev. Ther., 10, 2193–2202.



DOI: https://doi.org/10.22146/ijc.71334

Article Metrics

Abstract views : 3063 | views : 1318


Copyright (c) 2022 Indonesian Journal of Chemistry

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

 


Indonesian Journal of Chemistry (ISSN 1411-9420 / 2460-1578) - Chemistry Department, Universitas Gadjah Mada, Indonesia.

Web
Analytics View The Statistics of Indones. J. Chem.