Virtual Screening Kandungan Senyawa Kipas Laut (Gorgonia mariae) sebagai Anti-Asma

Faruk Jayanto Kelutur, Resmi Mustarichie, Abdul Kakhar Umar

Abstract

Kipas laut (Gorgonia mariae) telah digunakan masyarakat Maluku secara turun temurun sebagai obat asma. Kandungan metabolit sekunder yang paling dominan dalam kipas laut adalah sterol, dimana memiliki aktivitas terapi melalui efek sinergisme antara senyawa metabolit dengan polivalent activity. Pengujian kipas laut sebagai anti-asma belum pernah dilaporkan sebelumnya. Oleh karena itu, perlu dilakukan virtual screening menggunakan metode in silico pada komponen sterol kipas laut sebagai tahap awal dalam menentukan efektivitas terapi anti-asma dengan memprediksi nilai ikatan energi bebas (ΔG), konstanta inhibisi (Ki), dan interaksi residu asam amino menggunakan Autodock Tools 4.2 dan Discovery Studio 2016 Client®. Keamanan dan efektivitas kandidat obat dievaluasi menggunakan parameter dari Lipinski Rule of Five dan pre-ADMET. Hasil penelitian menunjukkan bahwa konstanta inhibisi dan ikatan energi bebas (Ki; ΔG) dari komponen senyawa kipas laut dapat diurutkan secara potensial yaitu 4,24-dimetil kolestanol  (0,809; -12,40) > 24-metil-22-dehidrokolesterol (0,864; -12,36) > 23-demetil gorgosterol (1,74; -11,95) > 4,24-dimetil-22-dehidrokolestanol (1,89; -11,90). Residu asam amino yang berperan penting dalam aktivitas inhibisi hCHIT1 adalah 213-ASP. Semua komponen senyawa uji memiliki nilai log P lebih dari 5 yang menunjukkan bahwa kelarutan dan toksisitas perlu diperhatikan. Evaluasi distribusi pre-ADMET berdasarkan nilai dari pengikatan protein plasma menunjukan bahwa senyawa uji dapat berdifusi menembus membran plasma dan berinteraksi sesuai target farmakologi. Selain itu, hasil parameter uji toksisitas menunjukkan bahwa senyawa 23-demetil gorgosterol dan 4,24-dimetil-22-dehidrokolestanol memiliki potensi sebagai anti-asma.

Virtual Screening of the Compounds in Gorgonians (Gorgonia mariae) as anti-asthma. The people of Maluku have used Kipas laut (G. mariae) for generations as an asthma medicine. The secondary metabolite that is most dominant in kipas laut is sterols, which have therapeutic activity through the synergistic effect between metabolite compounds and polyvalent activity. Anti-asthma activity of kipas laut has never been reported. Therefore, it is necessary to do virtual screening using the in silico method on the sterol component of kipas laut as a first step in determining the effectiveness of anti-asthma therapy by predicting the value of free energy bonds (ΔG), constant inhibition (Ki), and interactions of amino acid residues using Autodock Tools 4.2 and Discovery Studio 2016 Client®. The effectiveness and safety of prospective drugs are evaluated using the Lipinski Rule of Five and pre-ADMET. The results showed that the value of inhibition constants and free energy bonds (Ki; ΔG) on the compound of kipas laut that was potentially sorted was 4.24-dimethyl cholestanol (0.809; -12.40) > 24-methyl-22-dehydrocholesterol (0.864; -12.36) > 23-demethyl gorgosterol (1.74; -11.95) > 4.24-dimethyl-22-dehidrokolestanol (1.89; -11.90). The crucial residues of amino acids is 213-ASP, which play a significant role in hCHIT1 inhibitory activity. All components of the test compound have a log P value of more than five, which indicates that solubility and toxicity need to be considered. Evaluation of the pre-ADMET based on the value of plasma protein binding shows that the test compound can diffuse through the plasma membrane and interact according to pharmacological targets. In addition, the results of the toxicity test showed that 23-demethyl gorgosterol and 4.24-dimethyl-22-dehidrokolestanol compounds have potential as anti-asthma.

Keywords

Anti-asthma; in silico; kipas laut (G. marie); sterol

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References

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Cooper, E. L., Hirabayashi, K., Strychar, K. B., and Sammarco, P. W., 2014. Corals and Their Potential Applications to Integrative Medicine. Evidence-Based Complementary and Alternative Medicine 2014, 1–9. doi: 10.1155/2014/184959.

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Deghrigue, M., Festa, C., Ghribi, L., Auria, M. V. D., De, S., Jannet, H. B., and Bouraoui, A., 2015. Anti-Inflammatory and Analgesic Activities with Gastroprotective Effect of Semi-Purified Fractions and Isolation of Pure Compounds from Mediterranean Gorgonian Eunicella Singularis. Asian Pacific Journal of Tropical Medicine 8(8), 606-611. doi: 10.1016/j.apjtm.2015.07.019.

Depkes RI, 2015. Profil Kesehatan Provinsi Maluku. Departemen Kesehatan Republik Indonesia.

Gao, Y., Gesenberg, C., and Zheng, W., 2017. Developing Solid Oral Dosage Forms Pharmaceutical Theory and Practice, second ed. Academic Press. Cambridge (Chapter 17). doi: 10.1016/B978-0-12-802447-8.00017-0.

Godfrey, S., 1985. What Is Asthma? Archives of Disease in Childhood 60(11): 997–1000. doi: 10.1136/adc.60.11.997.

Grolmusz, V. 2014. Evaluating Genetic Algorithms in Protein-Ligand Evaluating Genetic Algorithms in Protein-Ligand Docking. Journal of Medicinal Chemistry 51(12), 3499-3506. doi: 10.1007/978-3-540-79450-9.

Hongmao, S., 2016. A Practical Guide to Rational Drug Design. Elsevier. Cambridge (Chapter 6). doi: 10.1016/B978-0-08-100098-4.00006-5.

Kim, R., and Skolnick, J., 2008. Assessment of Programs for Ligand Binding Affinity Prediction. Journal of Computational Chemistry 29(8), 1316-1331. doi: 10.1002/jcc.20893.

Kokke, W. C. M. C., Bohlin, L., Fenical, W., and Djerassi, C., 1982. Novel Dinoflagellate 4α-Methylated Sterols from Four Caribbean Gorgonians. Journal of Phytochemistry 21(4), 881–887. doi: 10.1016/0031-9422(82)80085-X.

Kontoyianni, M., Mcclellan, L. M., and Sokol, G. S., 2004. Evaluation of Docking Performance : Comparative Data on Docking Algorithms. Journal of Medicinal Chemistry 47(3), 558-565. doi: 10.1021/jm0302997.

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Rachmania, R. A., Supandi, S., and Larasati, O. A., 2015. Analisis In Silico Senyawa Diterpenoid Lakton Herba Sambiloto (Andrographis paniculata Nees) pada Reseptor Alpha-Glukosidase sebagai Antidiabetes Tipe II. PHARMACY: Jurnal Farmasi Indonesia (Pharmaceutical Journal of Indonesia) 12(2), 210–222.

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Cho, S. J., Weiden, M. D., and Lee, C. G., 2015. Chitotriosidase in the Pathogenesis of Inflammation, Interstitial Lung Diseases and COPD. Allergy, Asthma & Immunology Research 7(1), 14. doi: 10.4168/aair.2015.7.1.14.

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Czyrski, A., and Kupczyk, B., 2013. The Determination of Partition Coefficient of 6-Mercaptopurine Derivatives by Thin Layer Chromatography. Journal of Chemistry, 2013, 1-4. doi: 10.1155/2013/419194.

Deghrigue, M., Festa, C., Ghribi, L., Auria, M. V. D., De, S., Jannet, H. B., and Bouraoui, A., 2015. Anti-Inflammatory and Analgesic Activities with Gastroprotective Effect of Semi-Purified Fractions and Isolation of Pure Compounds from Mediterranean Gorgonian Eunicella Singularis. Asian Pacific Journal of Tropical Medicine 8(8), 606-611. doi: 10.1016/j.apjtm.2015.07.019.

Depkes RI, 2015. Profil Kesehatan Provinsi Maluku. Departemen Kesehatan Republik Indonesia.

Gao, Y., Gesenberg, C., and Zheng, W., 2017. Developing Solid Oral Dosage Forms Pharmaceutical Theory and Practice, second ed. Academic Press. Cambridge (Chapter 17). doi: 10.1016/B978-0-12-802447-8.00017-0.

Godfrey, S., 1985. What Is Asthma? Archives of Disease in Childhood 60(11): 997–1000. doi: 10.1136/adc.60.11.997.

Grolmusz, V. 2014. Evaluating Genetic Algorithms in Protein-Ligand Evaluating Genetic Algorithms in Protein-Ligand Docking. Journal of Medicinal Chemistry 51(12), 3499-3506. doi: 10.1007/978-3-540-79450-9.

Hongmao, S., 2016. A Practical Guide to Rational Drug Design. Elsevier. Cambridge (Chapter 6). doi: 10.1016/B978-0-08-100098-4.00006-5.

Kim, R., and Skolnick, J., 2008. Assessment of Programs for Ligand Binding Affinity Prediction. Journal of Computational Chemistry 29(8), 1316-1331. doi: 10.1002/jcc.20893.

Kokke, W. C. M. C., Bohlin, L., Fenical, W., and Djerassi, C., 1982. Novel Dinoflagellate 4α-Methylated Sterols from Four Caribbean Gorgonians. Journal of Phytochemistry 21(4), 881–887. doi: 10.1016/0031-9422(82)80085-X.

Kontoyianni, M., Mcclellan, L. M., and Sokol, G. S., 2004. Evaluation of Docking Performance : Comparative Data on Docking Algorithms. Journal of Medicinal Chemistry 47(3), 558-565. doi: 10.1021/jm0302997.

Létuvé, S., Kozhich, A., Humbles, A., Brewah, Y., Dombret, M.-C., Grandsaigne, M., Adle, H., Kolbeck, R., Aubier, M., Coyle, A. J., and Pretolani, M., 2010. Lung Chitinolytic Activity and Chitotriosidase Are Elevated in Chronic Obstructive Pulmonary Disease and Contribute to Lung Inflammation. The American Journal of Pathology 176(2), 638–649. doi: 10.2353/ajpath.2010.090455.

Lipinski, C. A., 2004. Lead- and Drug-Like Compounds: The Rule-of-Five Revolution. Drug Discovery Today: Technologies 1(4), 337–341. doi: 10.1016/j.ddtec.2004.11.007.

Marchbank, D. H., Berrue, F., and Kerr, R. G., 2012. Eunicidiol, an Anti-inflammatory Dilophol Diterpene from Eunicea fusca. Journal of Natural Products 75(7), 1289–1293. doi: 10.1021/np300149y.

Mazur, M., Olczak, J., Olejniczak, S., Koralewski, R., Czestkowski, W., Jedrzejczak, A., Golab, J., Dzwonek, K., Dymek, B., Sklepkiewicz, P. L., Zagozdzon, A., Noonan, T., Mahboubi, K., Conway, B., Sheeler, R., Beckett, P., Hungerford, W. M., Podjarny, A., Mitschler, A., Siah, A. C., Fadel, F., and Golebiowski, A., 2018. Targeting Acidic Mammalian chitinase Is Effective in Animal Model of Asthma. Journal of Medicinal Chemistry 61(3), 695–710. doi: 10.1021/acs.jmedchem.7b01051.

Megantara, S., Levita, J., Iwo, M. I., and Ibrahim, S., 2018. Absorption, Distribution and Toxicity Prediction of Andrographolide and Its Derivatives as Anti-HIV Drugs. Research Journal of Chemistry and Environment 22(Special Issue 1), 82–85.

Morris, G. M., Huey, R., Lindstrom, W., Sanner, M. F., Belew, R. K., Goodsell, D. S., and Olson, A. J., 2009. AutoDock4 and AutoDockTools4: Automated Docking with Selective Receptor Flexibility. Journal of Computational Chemistry 30(16), 2785–2791. doi: 10.1002/jcc.21256.

Narayanaswamy, R., Wai, L. K., and Esa, N. M., 2017. Molecular Docking Analysis of Phytic Acid and 4-Hydroxyisoleucine as Cyclooxygenase-2, Microsomal Prostaglandin E Synthase-2, Tyrosinase, Human Neutrophil Elastase, Matrix Metalloproteinase-2 and-9, Xanthine Oxidase, Squalene Synthase, Nitric Oxide Synthase, Human Aldose Reductase, and Lipoxygenase Inhibitors. Pharmacognosy Magazine 13(Suppl 3), 512–518. doi: 10.4103/pm.pm_195_16.

Nursamsiar, Toding, A. T., and Awaluddin, A., 2016. Studi In Silico Senyawa Turunan Analog Kalkon dan Pirimidin sebagai Antiinflamasi: Prediksi Absorpsi, Distribusi, dan Toksisitas. PHARMACY: Jurnal Farmasi Indonesia (Pharmaceutical Journal of Indonesia) 13(1), 92–100. doi: 10.30595/pji.v13i1.891.

O’Hagan, S., and Kell, D. B., 2015. The Apparent Permeabilities of Caco-2 Cells to Marketed Drugs: Magnitude, and Independence from Both Biophysical Properties and Endogenite Similarities. PeerJ 3, e1405. doi: 10.7717/peerj.1405.

Okechukwu, P. N., and Ekeuku, S. O., 2012. In Vivo And In Vitro Anti-Asthmatic Effects of Dichloromethane Crude Extract from the Leaves of Labisia pumila. Global Journal of Pharmacology 6(2), 126–130. doi: 10.5829/idosi.gjp.2012.6.2.6590.

Pratama, M. R. F., 2015. Molecular Docking of Anticancer Agents : Artemisinin and Derivates as HER2 Inhibitor. In: Proceedings of 1st Sari Mulia International Conference on Health and Science 2015. SMICHS 2015, 18-19 Desember 2015, Banjarmasin. SSRN, Cambridge, pp. 1–12.

Puspaningtyas, A. R., 2013. Molecular Docking using Molegro Virtual Docker (MVD) on Water Extract of Guavafruit (Psidium Gajava, Linn) and Sweet Orange (Citrus Sinensis, Peels) as Inhibior on Enzyme Tyrosinase as Positive Control of Whitening Agent. Indonesian Journal of Applied Chemistry 15(1), 31–39. doi: 10.14203/jkti.v15i1.102.

Rachmania, R. A., Supandi, S., and Larasati, O. A., 2015. Analisis In Silico Senyawa Diterpenoid Lakton Herba Sambiloto (Andrographis paniculata Nees) pada Reseptor Alpha-Glukosidase sebagai Antidiabetes Tipe II. PHARMACY: Jurnal Farmasi Indonesia (Pharmaceutical Journal of Indonesia) 12(2), 210–222.

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Rizki, M.I., Chabib, L. Nabil, A. and Yusuf, B., 2015. Tanaman dengan Aktivitas Anti-Asma. Jurnal Phamasciesnce 2(1), 1–9. doi: 10.20527/jps.v2i1.5807.

Roy, D., Kumar, V., Acharya, K. K., and Thirumurugan, K., 2013. Probing the Binding of Syzygium -Derived α -Glucosidase Inhibitors with N- and C-Terminal Human Maltase Glucoamylase by Docking and Molecular Dynamics Simulation. Applied Biochemistry and Biotechnology 172(1), 102–114. doi: 10.1007/s12010-013-0497-3.

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