In the past years, the world has experienced a profound impact due to the abrupt appearance of a new virus (COVID-19), presenting a significant threat to human health. Currently, there exists no widely established treatment for COVID-19 that proves consistently effective, but many studies have implemented drug repurposing and the use of herbal medicines. The potential of antiviral compounds from natural products can be predicted through an in silico approach. This study aimed to determine and design flavonoid compounds from red fruits and their derivatives that have the potential to suppress the SARS-CoV-2 Mpro, ensuring a stable molecular framework and adhering to a standard pharmacokinetic profile. The study started with molecular docking using a lead compound followed by Molecular dynamics (MD) simulation up to 100 ns and pharmacokinetic prediction. The analysis of docking outcomes reveals that among flavonoid compounds, quercetin 3’-glucoside exhibits the most favourable binding energy value. Furthermore, the identification of hydrogen bonds with amino acid residues Asn142 and Cys145 provides additional rationale for selecting this compound as a pivotal candidate in the design of novel derivatives. The molecular docking procedure and subsequent MD simulations were conducted utilizing the Yasara-structure software. Furthermore, the evaluation of the pharmacokinetic profile was performed utilizing pkCSM ADMET to gain insights into the compound’s absorption, distribution, metabolism, excretion, and toxicity characteristics. According to the docking outcomes, among the 225 newly designed compounds, the ligand with code SR133 demonstrated the most favourable binding energy of −8.0950 Kcal/mol, surpassing the reference compound. Subsequent MD simulation analysis indicates that this ligand demonstrates good stability. The presence of hydrogen bonds in the active site of SARS-CoV-2Mpro involving the main amino acid residues Asn142 and Cys145 further clarifies that this new compound has excellent inhibitory potential. The pharmacokinetic prediction of SR133 shows that this compound has a good pharmacokinetic profile and is worth proposing as a new drug candidate.
Ananto AD, Pranowo HD, Haryadi W, Prasetyo N. Flavonoid compound of red fruit papua and its derivatives against sars-cov-2 mpro: An in silico approach. J Appl Pharm Sci. 2024. Online First. http://doi.org/10.7324/JAPS.2024.177392
1. Minister of Health of the Republic of Indonesia Number: 381 concerning the 2007 National Traditional Medicine Policy, Jakarta, Indonesia: Minister of Health. | |
2. Covid19.go.id [Internet]. Indonesia: Covid-19 response task force, Situasi COVID-19 di Indonesia. [updated 2023 Jun 27 | |
cited 2023 Jul 15]. Available from https://covid19.go.id/id/ | |
3. Covid19.who.int [Internet]. World Health Organization: WHO Coronavirus (Covid-19) Dashboard, [cited 2023 August 4]. Available from https://covid19.who.int/ | |
4. Data.who.int [Internet]. WHO Coronavirus (COVID-19) dashboard > Cases [Dashboard], [cited 2024 Jan 2]. Available from https://data.who.int/dashboards/covid19/cases | |
5. Wang M, Cao R, Zhang L, Yang X, Liu J, Xu M, et al. Remdesivir and chloroquine effectively inhibit the recently emerged novel coronavirus (2019-nCoV) in vitro. Cell Res. 2020;30:269-71. https://doi.org/10.1038/s41422-020-0282-0 | |
6. Mahévas M, Tran VT, Roumier M, Chabrol A, Paule R, Guillaud C, et al. Clinical efficacy of hydroxychloroquine in patients with covid-19 pneumonia who require oxygen: observational comparative study using routine care data. BMJ. 2020;369:m1844. https://doi.org/10.1136/bmj.m1844 | |
7. Hung IFN, Lung KC, Tso EYK, Liu R, Chung TWH, Chu MY, et al. Triple combination of interferon beta-1b, lopinavir-ritonavir, and ribavirin in the treatment of patients admitted to hospital with COVID-19: an open-label, randomised, phase 2 trial. Lancet. 2020;395:1695-704. https://doi.org/10.1016/S0140-6736(20)31042-4 | |
8. Wang Y, Zhang D, Du G, Du R, Zhao J, Jin Y, et al. Remdesivir in adults with severe COVID-19: a randomised, double-blind, placebo-controlled, multicentre trial. Lancet. 2020;395:1569-578. https://doi.org/10.1016/S0140-6736(20)31022-9 | |
9. Xu X, Han M, Li T, Sun W, Wang D, Fu B, et al. Effective treatment of severe COVID-19 patients with tocilizumab. Proc Natl Acad Sci. 2020;117:10970-975. https://doi.org/10.1073/pnas.2005615117 | |
10. FDA.gov [Internet] U.S. Food & Drugs Administration: Fact sheet for healthcare providers: emergency authorization for Paxlovid, [cited 2022 Feb 23]. Available from https://www.fda.gov/ | |
11. Yang H, Yang M, Ding Y, Liu Y, Lou Z, Zhou Z, et al. The crystal structures of severe acute respiratory syndrome virus main protease and its complex with an inhibitor. Proc Natl Acad Sci. 2003;100:13190-195. https://doi.org/10.1073/pnas.1835675100 | |
12. Ren J, Zhang AH, and Wang XJ. Traditional Chinese medicine for COVID-19 treatment. Pharmacol Res. 2020;155:104743. https://doi.org/10.1016/j.phrs.2020.104743 | |
13. Felle ZR, Wijayanti MA, and Supargiyono. The effect of pandanus conoideus lamk extract to the serum level of TNF-α, IL-10 and parasitemia of plasmodium berghei infected in Mice. Trop Med J. 2013;3:39-47. | |
14. Tafor D, Djunaidi A, Wasityastuti W, and Solikhah EN. Tumor necrosis factor-alpha (TNF-alpha) and intercellular adhesion molecule-1 (ICAM-1) expression of plasmodium berghei infected swiss mice treated with red fruit (Pandanus Conoideus Lam) ethanol extract. Trop Med J. 2013;3:155-65. | |
15. Tambaip T, Br Karo M, Hatta M, Dwiyanti R, Natzir R, Nasrum Mas M, et al. Immunomodulatory effect of orally red fruit (Pandanus conoideus) extract on the expression of CC chemokine receptor 5 mRNA in HIV patients with antiretroviral therapy. Res J Immunol. 2018;11:15-21. https://doi.org/10.3923/rji.2018.15.21 | |
16. Umar, AbdK. Flavonoid compounds of buah merah (Pandanus conoideus Lamk) as a potent SARS-CoV-2 main protease inhibitor: in silico approach, Futur. J Pharm Sci. 2021;7:158. https://doi.org/10.1186/s43094-021-00309-0 | |
17. Prieto-Martínez FD, Arciniega M, and Medina-Franco JL. Acoplamiento molecular: avances recientes y retos, TIP Rev. Espec. en Ciencias Químico-Biológicas. 2018;21:65-87. https://doi.org/10.22201/fesz.23958723e.2018.0.143 | |
18. Lin X, Li X, and Lin X. A review on applications of computational methods in drug screening and design. Molecules. 2020;25:1375. https://doi.org/10.3390/molecules25061375 | |
19. Rachmania RA, Hariyanti H, Zikriah R, and Sultan A. Studi In Silico senyawa alkaloid herba bakung putih (Crinum Asiaticum L.) pada penghambatan enzim siklooksigenase (COX). Jurnal Kimia VALENSI. 2018;4:124-36. https://doi.org/10.15408/jkv.v4i2.7686 | |
20. Masone D, and Grosdidier S. Collective variable driven molecular dynamics to improve protein-protein docking scoring. Comput Biol Chem. 2014;49:1-6. https://doi.org/10.1016/j.compbiolchem.2013.12.003 | |
21. Childers MC, and Daggett V. Insights from molecular dynamics simulations for computational protein design. Mol Syst Des Eng. 2017;2:9-33. https://doi.org/10.1039/C6ME00083E | |
22. Ahmed M, Sadek MM, Abouzid KA, and Wang F, In silico design: extended molecular dynamic simulations of a new series of dually acting inhibitors against EGFR and HER2, J Mol Graph Model. 2013;44:220-31. https://doi.org/10.1016/j.jmgm.2013.06.004 | |
23. Shivanika C, Kumar D, Ragunathan V, Tiwari P, Sumitha A. Molecular docking, validation, dynamics simulations, and pharmacokinetic prediction of natural compounds against the SARS-CoV-2 main-protease. J Biomol Struct Dyn. 2022;40:585-611. https://doi.org/10.1080/07391102.2020.1815584 | |
24. Krieger E, Koraimann G, Vriend G. Increasing the precision of comparative models with YASARA NOVA-a self-parameterizing force field. Proteins Struct Funct Genet. 2002;47(3):1-10. https://doi.org/10.1002/prot.10104 | |
25. Biovia. Dassault Systèmes, Discovery studio visualizer, V21.1.0.20298. San Diego, CA:Dassault Systèmes; 2020. | |
26. Douangamath A, Fearon D, Gehrtz P, Krojer T, Lukacik P, Owen CD. et al. Crystallographic and electrophilic fragment screening of the SARS-CoV-2 main protease. Nat Commun. 2020;11:5047. https://doi.org/10.1038/s41467-020-18709-w | |
27. 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. https://doi.org/10.22159/ijap.2021v13i3.41202 | |
28. Nugraha G, Pranowo HD, Mudasir M, & Istyastono EP. Virtual target construction for discovery of human histamine H4 receptor ligands employing a structure-based virtual screening approach. Int J Appl Pharm. 2022;14(4):213-18. https://doi.org/10.22159/ijap.2022v14i4.44067 | |
29. Lengauer T, and Rarey M. Computational methods for biomolecular docking. Curr Opin Struct Biol. 1996;6(3):402-6. https://doi.org/10.1016/S0959-440X(96)80061-3 | |
30. 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 a molecular docking prediction. Int J App Pharm. 2022;14:256-66. https://doi.org/10.22159/ijap.2022v14i2.43784 | |
31. Jin Z, Du X, Xu Y, Deng Y, Liu M, Zhao Y, et al. Structure of Mpro from SARS-CoV-2 and discovery of its inhibitors. Nature. 2020;582:289-93. https://doi.org/10.1038/s41586-020-2223-y | |
32. Meanwell NA. Synopsis of some recent tactical application of bioisosteres in drug design. J Med Chem. 2011;54(8):2529-91. https://doi.org/10.1021/jm1013693 | |
33. Kubitzki MB, and de Groot BL. Molecular dynamics simulations using temperature-enhanced essential dynamics replica exchange. Biophys J. 2007;92(12):4262-70. https://doi.org/10.1529/biophysj.106.103101 | |
34. Jung J, Kobayashi C, and Sugita Y. Optimal temperature evaluation in molecular dynamics simulations with a large time step. J Chem Theory Comput. 2018;15(1):84-94. https://doi.org/10.1021/acs.jctc.8b00874 | |
35. Hospital A, Goni JR, Orozco M, and Gelpi JL. Molecular dynamics simulations: advances and applications. Adv Appl Bioinform Chem. 2015;8:37-47. https://doi.org/10.2147/AABC.S70333 | |
36. Arora S, Lohiya G, Moharir K, Shah S, and Yende S. Identification of potential flavonoid inhibitors of the SARS-CoV-2 main protease 6YNQ: a molecular docking study. Digital Chinese Med. 2020;3:239-48. https://doi.org/10.1016/j.dcmed.2020.12.003 | |
37. Schneider G. “De novo molecular design”. Weinheim, Germany: Wiley-VCH Verlag GmbH & Co; 2014. | |
38. Chaudhary N and Aparoy P. Deciphering the mechanism behind the varied binding activities of COXIBs through molecular dynamic simulations, MM-PBSA binding energy calculations and per-residue energy decomposition studies, J Biomol Struct Dyn. 2017;35(4):868-82. https://doi.org/10.1080/07391102.2016.1165736 | |
39. Zhang QY, and Aires-de-Sousa J. Random forest prediction of mutagenicity from empirical physicochemical descriptors. J Chem Inf Model. 2007;47(1):1-8. https://doi.org/10.1021/ci050520j | |
40. Pires DE, Blundell TL, and Ascher DB. pkCSM: predicting small-molecule pharmacokinetic and toxicity properties using graph-based signatures. J Med Chem. 2015;58(9):4066-72. https://doi.org/10.1021/acs.jmedchem.5b00104 | |
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