INTERACTIONS OF XANTHONE COMPOUNDS FROM THE MANGOSTEEN (GARCINIA MANGOSTANA L) PERICARPS AGAINST INOS, COX-1, AND COX-2 ENZYME RECEPTORS AS ANTI-INFLAMMATORY

Authors

  • DWINTHA LESTARI Department of Pharmacy, Universitas Muhammadiyah Bandung, Indonesia
  • RISKA PERMATA SARI Department of Pharmacy, Universitas Muhammadiyah Bandung, Indonesia https://orcid.org/0000-0001-6047-4927
  • IDA MUSFIROH Department of Pharmaceutical Analysis Pharmacy and Medicinal Chemistry, Faculty of Pharmacy, Universitas Padjadjaran, Indonesia
  • SANDRA MEGANTARA Department of Pharmaceutical Analysis Pharmacy and Medicinal Chemistry, Faculty of Pharmacy, Universitas Padjadjaran, Indonesia https://orcid.org/0000-0003-4951-7740
  • MEILINDA SETYA PRACEKA Department of Pharmacy, Universitas Halim Sanusi, Bandung, Indonesia https://orcid.org/0000-0002-2632-8958
  • NUR KUSAIRA KHAIRUL IKRAM Institute of Biological Sciences, Faculty of Science, University of Malaya, Kuala Lumpur, Malaysia
  • MUCHTARIDI Department of Pharmaceutical Analysis Pharmacy and Medicinal Chemistry, Faculty of Pharmacy, Universitas Padjadjaran, Indonesia https://orcid.org/0000-0002-6156-8025

DOI:

https://doi.org/10.22159/ijap.2023v15i1.45861

Keywords:

Inflammatory, iNOS, COX-1, COX-2, Pharmacophore, molecular docking, α-mangostin, γ-mangostin

Abstract

Objective: Mangosteen is a plant that is very effective for inflammation. Besides that, the skin of the mangosteen plant in Indonesia continues to be developed because it is an antioxidant and suppresses the production of cytokines.

Methods: Screening pharmacophores and molecular docking simulations by molecular modeling computation to predict the activity of the Mangosteen plant in silico and to determine potential drug candidates from mangosteen for inflammation to the iNOS, COX-1, and COX-2.

Results: Pharmacophore Screening, γ-mangosteen has the highest pharmacophore fit score of 33.32 and 33.64 on COX-1 and COX-2 and is selective to iNOS target. Molecular docking of α-mangosteen and γ-mangosteen test compounds to the active site of used, COX-1, and COX-2 enzymes showed free energy binding (ΔGo) values of, -5.09, -5.00, -6.15; and -6.76, -5.30, -7.81 Kcal/mol respectively. Meanwhile, hydrogen bonds and good ΔGo values ​​were formed between γ-mangosteen and COX-2, where the Hydroxyl group on γ-mangosteen interacted with the amino acids His75, Ser339, and Ala513 with ΔGo of -7.81 Kcal/mol.

Conclusion: It can be said that α-mangosteen and γ-mangosteen have molecular interactions with COX-1 and COX-2 active sites with the highest affinity for COX-2 compared to COX-1, and iNOS.

Downloads

Download data is not yet available.

References

Muchtaridi M, Suryani D, Qosim WA, Saptarini NM. Quantitative analysis of A-mangostin in mangosteen (Garcinia mangostana L.) pericarp extract from four district of West Java by HPLC method. Int J Pharm Pharm Sci. 2016;8:232–6.

Marzaimi IN, Aizat WM. Current Review on Mangosteen Usages in Antiinflammation and Other Related Disorders. 2nd edition. Elsevier Inc.; 2019.

Muchtaridi M, Wijaya CA. Anticancer potential of α-mangostin. Asian J Pharm Clin Res. 2017;10:440–5.

Yatman E. Mangosteen rind contains high nutritious xanthones. Univ Borobudur. 2012;29:2–9.

Putri IP. Effectivity of Xanthone of Mangosteen (Garcinia mangostana L.) Rind as Anticancer. J Major. 2015;4:33.

Dinata, Deden I., Hardi Suryanto. IM. Simulasi Docking Molekuler Senyawa Xanthorrhizol sebagai Antiinflamasi terhadap Enzim COX-1 dan COX-2 Molecular Docking Simulation of Xanthorrhizol Compounds Derived from Temulawak as Antiinflammatory on Enzymes COX-1 and COX-2. Ijpst. 2014;1:7–13.

Liu SH, Lee LT, Hu NY, Huange KK, Shih YC, Munekazu I, et al. Effects of alpha-mangostin on the expression of anti-inflammatory genes in U937 cells. Chinese Med (United Kingdom). 2012;7:1–11.

Sukma M, Tohda M, Suksamran S, Tantisira B. γ-Mangostin increases serotonin 2A/2C, muscarinic, histamine and bradykinin receptor mRNA expression. J Ethnopharmacol. 2011;135:450–4.

Musfiroh I, Megawati G, Herawati DMD, Rusdin A. 3D-Pharmacophore Modelling of Omega-3 Derivatives With Peroxisome Proliferator-Activated Receptor Gamma As an Anti-Obesity Agent. Int J Appl Pharm. 2021;13 special issue 4:167–70.

RCSB Protein Data Bank. Protein Data Bank. 2020. http://www.rcsb.org/pdb. Accessed 30 Mar 2020.

Pubchem. PubChem. 2020. https://pubchem.ncbi.nlm.nih.gov/. Accessed 1 Apr 2020.

Mysinger MM, Carchia M, Irwin JJ, Shoichet BK. Directory of useful decoys, enhanced (DUD-E): Better ligands and decoys for better benchmarking. J Med Chem. 2012;55:6582–94.

Nurhidayah M, Fadilah F, Arsianti A, Bahtiar A. Identification of Fgfr Inhibitor As St2 Receptor/Interleukin-1 Receptor-Like 1 Inhibitor in Chronic Obstructive Pulmonary Disease Due To Exposure To E-Cigarettes By Network Pharmacology and Molecular Docking Prediction. Int J Appl Pharm. 2022;14:256–66.

Praceka MS, Megantara S, Mustarichie R. Journal of Global Pharma Technology Molecular Modeling of Anti-Alopecia Journal of Global Pharma Technology Molecular Modeling of Sauropus Androgynus Compounds. 2020; May.

Shaikh SI, Zaheer Z, Mokale SN, Lokwani DK. Development of New Pyrazole Hybrids As Antitubercular Agents: Synthesis, Biological Evaluation and Molecular Docking Study. Int J Pharm Pharm Sci. 2017;9:50.

Holik HA, Ibrahim FM, Wianatalie E, Achmad A, Faried A, Kartamihardja AHS. the Molecular Interaction and Admet Prediction of Modified Jph203 As a Potential Radiopharmaceutical Kit for Molecular Imaging of Cancer: an in Silico Research. Int J Appl Pharm. 2021;13 special issue 4:205–9.

Wolber G, Langer T. LigandScout: 3-D pharmacophores derived from protein-bound ligands and their use as virtual screening filters. J Chem Inf Model. 2005;45:160–9.

Hariyanti H, Kurmardi K, Yanuar A, Hayun H. Ligand Based Pharmacophore Modeling, Virtual Screening, and Molecular Docking Studies of Asymmetrical Hexahydro-2H-Indazole Analogs of Curcumin (AIACs) to Discover Novel Estrogen Receptors Alpha (ERα) Inhibitor. Indones J Chem. 2020;21:137.

Mubarak A. Alamri* 1 & Mohammed A. Alamri 2. Pharmacophore and docking-based sequential virtual screening for the identification of novel Sigma 1 receptor ligands. Bioinformation. 2019;15:579–85.

Temml V, Kaserer T, Kutil Z, Landa P, Vanek T, Schuster D. Pharmacophore modeling for COX-1 and-2 inhibitors with LigandScout in comparison to Discovery Studio. Future Med Chem. 2014;6:1869–81.

Levita J, Patala R, Kolina J, Milanda T, Mutakin M, Puspitasari IM, et al. Pharmacophore modeling and molecular docking of phytoconstituents in Morus sp. and Arcangelisia flava against nitric oxide synthase for antiinflammatory discovery. J Appl Pharm Sci. 2018;8:53–9.

Nugraha G, Istyastono EP. Virtual target construction for structure-based screening in the discovery of histamine h2 receptor ligands. Int J Appl Pharm. 2021;13:239–41.

Candra GNH, Wijaya IMAP. Molecular Docking Kaempferol as Anti-Inflammatory in Atherosclerosis In Silico. J Ilm Medicam. 2021;7:13–8.

Bhowmik R, Roy S, Sengupta S, Sharma S. Biocomputational and pharmacological analysis of phytochemicals from zingiber officinale (Ginger), allium sativum (garlic), and murrayakoenigii (curry leaf) in contrast to type 2-diabetes. Int J Appl Pharm. 2021;13:280–6.

Silalahi M. Benefits And Bioactivity of Mangist (Garcinia mangostana L.). Bioeducation. 2021;VOL 12:30–7.

Mohan S, Syam S, Abdelwahab SI, Thangavel N. An anti-inflammatory molecular mechanism of action of α-mangostin, the major xanthone from the pericarp of Garcinia mangostana: an in silico, in vitro and in vivo approach. 2018.

Kurniawan. Isolation, Identification, Validation Of Determination Of Alfa Mangostin And Gamma Mangostin Levels Of Mangostine Fruit (Garcinia mangostana L.). Univ Muhammadiyah Surakarta. 2020;:4–5.

Published

21-10-2022

How to Cite

LESTARI, D., SARI, R. P., MUSFIROH, I., MEGANTARA, S., PRACEKA, M. S., KHAIRUL IKRAM, N. K., & MUCHTARIDI. (2022). INTERACTIONS OF XANTHONE COMPOUNDS FROM THE MANGOSTEEN (GARCINIA MANGOSTANA L) PERICARPS AGAINST INOS, COX-1, AND COX-2 ENZYME RECEPTORS AS ANTI-INFLAMMATORY. International Journal of Applied Pharmaceutics, 15(1). https://doi.org/10.22159/ijap.2023v15i1.45861

Issue

Section

Original Article(s)

Most read articles by the same author(s)

1 2 > >>