IN SILICO STUDY OF SOME FLAVONOID COMPOUNDS AGAINST ACE-2 RECEPTORS AS ANTI-COVID-19

Authors

  • IDA MUSFIROH Pharmaceutical Analysis and Medicinal Chemistry, Faculty of Pharmacy, Universitas Padjadjaran, West Java, Indonesia https://orcid.org/0000-0002-2569-8914
  • OKTAVIA SABETTA SIGALINGGING Pharmaceutical Analysis and Medicinal Chemistry, Faculty of Pharmacy, Universitas Padjadjaran, West Java, Indonesia
  • CECEP SUHANDI Pharmaceutical Analysis and Medicinal Chemistry, Faculty of Pharmacy, Universitas Padjadjaran, West Java, Indonesia. Pharmaceutics and Pharmaceutical Technology, Faculty of Pharmacy, Universitas Padjadjaran, West Java, Indonesia
  • NUR KUSAIRA KHAIRUL IKRAM Institute of Biological Sciences, Faculty of Science, Universiti Malaya, 50603, Kuala Lumpur, Malaysia
  • SANDRA MEGANTARA Pharmaceutical Analysis and Medicinal Chemistry, Faculty of Pharmacy, Universitas Padjadjaran, West Java, Indonesia
  • MUCHTARIDI MUCHTARIDI Pharmaceutical Analysis and Medicinal Chemistry, Faculty of Pharmacy, Universitas Padjadjaran, West Java, Indonesia

DOI:

https://doi.org/10.22159/ijap.2023v15i4.48109

Keywords:

ACE-2, COVID-19, Flavonoid, In silico

Abstract

Objective: The coronavirus disease 2019 (COVID-19) pandemic has become a global concern today. As a receptor that plays an important role in viral entry, inhibition of angiotensin-converting enzyme-2 (ACE-2) activity could prevent severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. Quercetin is one of the flavonoid compounds reported to have activity as an ACE-2 inhibitor via interaction with the hydroxyl group at ring B positions 3' and 4'. The aims of this research to analyze the binding interaction of some flavonoid compounds into ACE-2 receptor to predict their activity as an anticovid-19.

Methods: An in silico approach via molecular docking simulations was conducted, and the selection of potential compounds was based on Lipinski's rules, prediction of absorption, distribution, metabolism, and toxicity (ADMET).

Results: The results showed that nepetin was the most potent compound, with a bond energy of-4.71 kcal/mol and an inhibition constant of 355.62 µM. The compound is bound to amino acid residues Asp30, His34, Glu35, and Thr27, which are important amino acid residues of the ACE-2 receptor.

Conclusion: The nepetin compound complies with all Lipinski rules and has a better ADMET profile compared to other compounds.

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References

Worldometer. Coronavirus: Indonesia. Available from: https://www.worldometers.info/coronavirus/country/indonesia/.2021.

Han Y, Yang H. The transmission and diagnosis of 2019 novel coronavirus infection disease (COVID-19): A Chinese perspective. J Med Virol. 2020;92(6):639-44. doi: 10.1002/jmv.25749, PMID 32141619.

Biscayart C, Angeleri P, Lloveras S, do Chaves TSS, Schlagenhauf P, Rodríguez-Morales AJ. The next big threat to global health? 2019 novel coronavirus. What advice can we give to travellers? Travel Med Infect Dis. 2020;33:1-4:2020.

Sanders JM, Monogue ML, Jodlowski TZ, Cutrell JB. Pharmacologic treatments for coronavirus disease 2019 (COVID-19): a review. JAMA. 2020;323(18):1824-36. doi: 10.1001/jama.2020.6019, PMID 32282022.

Muchtaridi M, Fauzi M, Khairul Ikram NK, Mohd Gazzali A, Wahab HA. Natural flavonoids as potential angiotensin-converting enzyme 2 inhibitors for anti-SARS-CoV-2. Molecules. 2020;25(17):1-20. doi: 10.3390/molecules25173980, PMID 32882868.

Panche AN, Diwan AD, Chandra SR. Flavonoids: an overview. J Nutr Sci. 2016;5:(e47). doi: 10.1017/jns.2016.41, PMID 28620474.

Gheblawi M, Wang K, Viveiros A, Nguyen Q, Zhong JC, Turner AJ. Angiotensin-converting enzyme 2: SARS-CoV-2 receptor and regulator of the renin-angiotensin system: celebrating the 20th anniversary of the discovery of ACE2. Circ Res. 2020;126(10):1456-74. doi: 10.1161/CIRCRESAHA.120.317015, PMID 32264791.

Bahbah EI, Negida A, Nabet MS. Purposing saikosaponins for the treatment of COVID-19. Med Hypotheses. 2020;140:109782. doi: 10.1016/j.mehy.2020.109782, PMID 32353743.

Liu X, Raghuvanshi R, Ceylan FD, Bolling BW. Quercetin and its metabolites inhibit recombinant human angiotensin-converting enzyme 2 (ACE2) activity. J Agric Food Chem. 2020;68(47):13982-9. doi: 10.1021/acs.jafc.0c05064, PMID 33179911.

Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS. AutoDock4 and AutoDockTools4: automated docking with selective receptor flexibility. J Comput Chem. 2009;30(16):2785-91. doi: 10.1002/jcc.21256, PMID 19399780.

Lipinski CA. Lead- and drug-like compounds: the rule-of-five revolution. Drug Discov Today Technol. 2004;1(4):337-41. doi: 10.1016/j.ddtec.2004.11.007, PMID 24981612.

Holik HA, Ibrahim FM, Fatah AL, Achmad A, Kartamihardja AHS. In silico studies of (S)-2-amino-4-(3,5-dichlorophenyl) butanoic acid against lat1 as a radio theranostic agent of cancer. Int J App Pharm. 2021;13Special Issue 4:239-43. doi: 10.22159/ijap.2021.v13s4.43868.

Sethi A, Sanam S, Munagalasetty S, Jayanthi S, Alvala M. Understanding the role of galectin inhibitors as potential candidates for SARS-CoV-2 spike protein: in silico studies. RSC Adv. 2020;10(50):29873-84. doi: 10.1039/d0ra04795c, PMID 35518264.

Du X, Li Y, Xia YL, Ai SM, Liang J, Sang P. Insights intoprotein–ligand interactions: mechanisms, models, and methods. Int J Mol Sci. 2016;17(2):1-34. doi: 10.3390/ijms17020144, PMID 26821017.

Shityakov S, Förster C. In silico structure-based screening of versatile P-glycoprotein inhibitors using polynomial empirical scoring functions. Adv Appl Bioinform Chem. 2014;7:1-9. doi: 10.2147/AABC.S56046, PMID 24711707.

Brooks BR, Brooks CL, Mackerell AD, Nilsson L, Petrella RJ, Roux B. Charmm: The biomolecular simulation program. J Comput Chem. 2009;30(10):1545-614.

Jia CS, Wang YT, Wei LS, Wang CW, Peng XL, Zhang LH. Predictions of entropy and Gibbs energy for carbonyl sulfide. ACS Omega. 2019;4(22):20000-4. doi: 10.1021/acsomega.9b02950, PMID 31788634.

Han DP, Penn Nicholson A, Cho MW. Identification of critical determinants on ACE2 for SARS-CoV entry and development of a potent entry inhibitor. Virology. 2006;350(1):15-25. doi: 10.1016/j.virol.2006.01.029, PMID 16510163.

Giordano D, De Masi L, Argenio MA, Facchiano A. Structural dissection of viral spike‐protein binding of sars‐cov‐2 and sars‐cov‐1 to the human angiotensin‐converting enzyme 2 (Ace2) as cellular receptor. Biomedicines. 2021;9(8):1-13. doi: 10.3390/biomedicines9081038, PMID 34440241.

Hou Q, Bourgeas R, Pucci F, Rooman M. Computational analysis of the amino acid interactions that promote or decrease protein solubility. Sci Rep. 2018;8(1):14661. doi: 10.1038/s41598-018-32988-w, PMID 30279585.

Lite TV, Grant RA, Nocedal I, Littlehale ML, Guo MS, Laub MT. Uncovering the basis of protein-protein interaction specificity with a combinatorially complete library. eLife. 2020;9:1-22. doi: 10.7554/eLife.60924, PMID 33107822.

Alyami H, Dahmash E, Alyami F, Dahmash D, Huynh C, Terry D. Dosage form preference consultation study in children and young adults: paving the way for patient-centered and patient-informed dosage form development. Eur J Hosp Pharm. 2017;24(6):332-7. doi: 10.1136/ejhpharm-2016-001023, PMID 31156967.

Benet LZ, Hosey CM, Ursu O, Oprea TI. BDDCS, The rule of 5 and drugability. Adv Drug Deliv Rev. 2016;101:89-98. doi: 10.1016/j.addr.2016.05.007, PMID 27182629.

Lipinski CA, Lombardo F, Dominy BW, Feeney PJ. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev. 2001;46(1-3):3-26. doi: 10.1016/s0169-409x(00)00129-0, PMID 11259830.

Hage Melim LIDS, Federico LB, de Oliveira NKS, Francisco VCC, Correia LC, de Lima HB. Virtual screening, ADME/Tox predictions and the drug repurposing concept for future use of old drugs against the COVID-19. Life Sci. 2020;256:117963. doi: 10.1016/j.lfs.2020.117963, PMID 32535080.

Ononamadu CJ, Ibrahim A. Molecular docking and prediction of ADME/drug-likeness properties of potentially active antidiabetic compounds isolated from aqueous-methanol extracts of gymnema sylvestre and combretum micranthum. Biotechnologia. 2021;102(1):85-99. doi: 10.5114/bta.2021.103765, PMID 36605715.

Xiong G, Wu Z, Yi J, Fu L, Yang Z, Hsieh C. ADMETlab 2.0: an integrated online platform for accurate and comprehensive predictions of ADMET properties. Nucleic Acids Res. 2021;49(W1):W5-W14. doi: 10.1093/nar/gkab255, PMID 33893803.

Kumar R, Sharma A, Siddiqui MH, Tiwari RK. Prediction of human intestinal absorption of compounds using artificial intelligence techniques. Curr Drug Discov Technol. 2017;14(4):244-54. doi: 10.2174/1570163814666170404160911, PMID 28382857.

Cheng F, Li W, Liu G, Tang Y. In silico ADMET prediction: recent advances, current challenges and future trends. Curr Top Med Chem. 2013;13(11):1273-89. doi: 10.2174/15680266113139990033, PMID 23675935.

Azman M, Sabri AH, Anjani QK, Mustaffa MF, Hamid KA. Intestinal absorption study: challenges and absorption enhancement strategies in improving oral drug delivery. Pharmaceuticals (Basel). 2022;15(8):1-24. doi: 10.3390/ph15080975, PMID 36015123.

Fredlund L, Winiwarter S, Hilgendorf C. In vitro intrinsic permeability: a transporter-independent measure of Caco-2 cell permeability in drug design and development. Mol Pharm. 2017;14(5):1601-9. doi: 10.1021/acs.molpharmaceut.6b01059, PMID 28329446.

Yazdanian M, Glynn SL, Wright JL, Hawi A. Correlating partitioning and Caco-2 cell permeability of structurally diverse small molecular weight compounds. Pharm Res. 1998;15(9):1490-4. doi: 10.1023/a:1011930411574, PMID 9755906.

Larregieu CA, Benet LZ. Drug discovery and regulatory considerations for improving in silico and in vitro predictions that use caco-2 as a surrogate for human intestinal permeability measurements. AAPS J. 2013;15(2):483-97. doi: 10.1208/s12248-013-9456-8, PMID 23344793.

Roberts JA, Pea F, Lipman J. The clinical relevance of plasma protein binding changes. Clin Pharmacokinet. 2013;52(1):1-8. doi: 10.1007/s40262-012-0018-5, PMID 23150213.

Purwaniati P. Molecular docking study on COVID-19 drug activity of N-(2-phenylethyl) methanesulfonamide derivatives as main protease inhibitor. Ad-Dawaa J Pharm Sci. 2020;3(1):1-11.

Charlier B, Coglianese A, de Rosa F, de Grazia U, Operto FF, Coppola G. The effect of plasma protein binding on the therapeutic monitoring of antiseizure medications. Pharmaceutics. 2021;13(8):1-20. doi: 10.3390/pharmaceutics13081208, PMID 34452168.

Neumaier F, Zlatopolskiy BD, Neumaier B. Drug penetration into the central nervous system: pharmacokinetic concepts and in vitro model systems. Pharmaceutics. 2021;13(10):1-31. doi: 10.3390/pharmaceutics13101542, PMID 34683835.

Ma XL, Chen C, Yang J. Predictive model of blood-brain barrier penetration of organic compounds. Acta Pharmacol Sin. 2005;26(4):500-12. doi: 10.1111/j.1745-7254.2005.00068.x, PMID 15780201.

Upadhyay RK. Drug delivery systems, CNS protection, and the blood-brain barrier. BioMed Res Int. 2014;2014:869269. doi: 10.1155/2014/869269, PMID 25136634.

Honma M. An assessment of mutagenicity of chemical substances by (quantitative) structure-activity relationship. Genes Environ. 2020;42(23):23. doi: 10.1186/s41021-020-00163-1, PMID 32626544.

Tyzack JD, Kirchmair J. Computational methods and tools to predict cytochrome P450 metabolism for drug discovery. Chem Biol Drug Des. 2019;93(4):377-86. doi: 10.1111/cbdd.13445, PMID 30471192.

Bibi Z. Role of cytochrome P450 in drug interactions. Nutr Metab (Lond). 2008;5(27):27. doi: 10.1186/1743-7075-5-27, PMID 18928560.

Muralikrishnan A, Kubavat J, Vasava M, Jupudi S, Biju N. Investigation of anti-sars cov-2 activity of some tetrahydro curcumin derivatives: an in silico study. Int J App Pharm. 2023;15(1):333-9. doi: 10.22159/ijap.2023v15i1.46288.

Kirchmair J, Goller AH, Lang D, Kunze J, Testa B, Wilson ID. Predicting drug metabolism: experiment and/or computation? Nat Rev Drug Discov. 2015;14(6):387-404. doi: 10.1038/nrd4581.

Published

07-07-2023

How to Cite

MUSFIROH, I., SIGALINGGING, O. S., SUHANDI, C., KHAIRUL IKRAM, N. K., MEGANTARA, S., & MUCHTARIDI, M. (2023). IN SILICO STUDY OF SOME FLAVONOID COMPOUNDS AGAINST ACE-2 RECEPTORS AS ANTI-COVID-19. International Journal of Applied Pharmaceutics, 15(4), 225–230. https://doi.org/10.22159/ijap.2023v15i4.48109

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