|
 |
| ORIGINAL ARTICLE |
|
| Year : 2022 | Volume
: 13
| Issue : 3 | Page : 191-196 |
|
|
Prediction of the mechanism of action of catechin as superoxide anion antioxidants and natural antivirals for COVID-19 infection with in silico study
Achmad Zainuddin, Ika Wiani Hidayat, Dikdik Kurnia, Zenika Febian Ramadhanty, Rizal Padilah
Department of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Sumedang, Indonesia
| Date of Submission | 11-Mar-2022 |
| Date of Decision | 05-May-2022 |
| Date of Acceptance | 10-May-2022 |
| Date of Web Publication | 05-Jul-2022 |
Correspondence Address:
Prof. Dikdik Kurnia
Department of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Sumedang
Indonesia
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/japtr.japtr_67_22
Coronavirus disease-2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus-2 attacking the lungs, which contain the most oxygen. The involvement of oxidative stress in the body and the role of antioxidant compounds, namely catechins, are thought to be able to prevent various diseases, including the COVID-19 infection virus. An in silico approach was employed between the catechins and the protein NADPH oxidase (Nox), followed by the coronavirus protease protein, to limit the generation of reactive oxygen species. This research using the in silico method seeks to predict the mechanism of action of catechin as a superoxide radical anion inhibitor and as an antiviral for COVID-19. This study carried out molecular docking simulations of catechin compounds against Nox and coronavirus proteases and then compared them with positive controls GKT136901 and remdesivir. The binding energy of catechin and Nox in a docking simulation is − 8.30 kcal/mol, which is somewhat lower than GKT136901's binding value of − 8.72 kcal/mol. Catechin and coronavirus proteases had binding energy of − 7.89 kcal/mol, which was greater than remdesivir's binding energy of − 7.50 kcal/mol. Based on in silico data, catechin as an antioxidant compound can be antiviral for COVID-19.
Keywords: Antioxidant, antiviral coronavirus disease-2019, catechin, in silico
How to cite this article:
Zainuddin A, Hidayat IW, Kurnia D, Ramadhanty ZF, Padilah R. Prediction of the mechanism of action of catechin as superoxide anion antioxidants and natural antivirals for COVID-19 infection with in silico study. J Adv Pharm Technol Res 2022;13:191-6 |
How to cite this URL:
Zainuddin A, Hidayat IW, Kurnia D, Ramadhanty ZF, Padilah R. Prediction of the mechanism of action of catechin as superoxide anion antioxidants and natural antivirals for COVID-19 infection with in silico study. J Adv Pharm Technol Res [serial online] 2022 [cited 2023 Mar 30];13:191-6. Available from: https://www.japtr.org/text.asp?2022/13/3/191/349844 |
| Introduction | |  |
Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes coronavirus disease-2019 (COVID-19), an acute respiratory disease that has lately become a pandemic.[1] COVID-19 is spread through the respiratory tract, with the lungs being one of the organs that receive the most oxygen in the human body.[2] In this case, oxidative stress becomes an important factor that can overcome environmental conditions that are susceptible to this virus.[3] Hence, it is important to analyze the role of cellular organelles and substances directly related to oxidative stress.[4]
The main focus in the quest for alternatives to combat the COVID-19 virus's propagation is to boost the body's natural immune system and immunity by eating foods high in antioxidant bioactive substances.[5] The efficacy of antioxidants may be very useful in preventing and reducing symptoms of COVID-19; catechins are natural polyphenol compounds derived from one of the plants Uncaria gambir, and they are widely known for their ability to prevent various diseases, including viral infections. Catechins act as antioxidants because they can generate and capture free radicals either directly (removal of reactive oxygen species [ROS] and metal chelating agents) or indirectly (induction of antioxidant enzymes and inhibition of prooxidant enzymes and antioxidant enzymes).[6]
In finding alternative techniques to avoid COVID-19, it may be the best solution to use an in silico method, where multi-target inhibition of coronaviral or coronaviral-2 enzymes and proteins is one of the most promising ways to produce highly effective COVID-19 treatments. The in silico approach is a computational method, such as molecular docking, that looks at the binding affinity of a tiny molecule (ligand as an active substance) and a potential receptor to determine how interactions occur (target protein).[7],[8] This method can be carried out simply and quickly so that it is suitable for screening bioactive compounds before in vitro studies, and this in silico method can be used to obtain new drug targets.[9] The target receptor chosen in this publication to see the prediction of catechin's mechanism of action as an antidote to superoxide anions is Nox because it is the only enzyme that generates ROS. As a result of this target selection, catechin compounds are expected to decrease ROS signaling. Nox is a major role in cell differentiation, senescence, and apoptosis, according to various studies.[10],[11] Flavin adenine dinucleotide (FAD) will be used as a native ligand to validate the docking simulation between Nox and catechin. GKT136901 is one of the inhibitors that can be used against Nox, and in this article, it is used as a positive control.[12]
In addition, new COVID-19 evasion strategies are being developed. Anti-COVID-19 medicines are being developed as a priority target for SARS CoV-2's primary protease, which is a key component of viral replication. The goal of this study was to explore if catechin might be used as an antiviral treatment for corona. The coronavirus protease protein was selected to investigate other bioactivities of catechin as coronavirus antiviral drugs.[13] Remdesivir as the currently used corona antiviral drug was used as a positive control.[14]
Nox activity has been shown to have a role in respiratory virus-induced ROS overproduction in several in vitro and in vivo studies.[15] Changes in ROS are also associated with the coronavirus. So that in this journal, with an approach through molecular docking, it is hoped that the prediction of the mechanism of action of catechin compounds as superoxide anion radical inhibitors can also be candidates for compounds that have the potential as COVID-19 antivirals.
| Materials and Methods | | |
Materials
The Nox protein (Protein Data Bank ID: 5O0X) and the coronavirus protease structure (Protein Data Bank [PDB] ID: 5N5O) were obtained from the RCSB PDB (https://WWW.RCSB.org/). Catechin (CID: 9064), remdesivir (CID: 12134016), and GKT136901 (CID: 17027464) were downloaded from PubChem (https://pubchem.ncbi.nlm.nih. gov/), and the Open Babel tool was used to build three-dimensional (3D) structures in PDB format. Redocking with native ligands was carried out to validate the docking simulation for the respective proteins, including Nox-FAD [Figure 1] and the coronavirus protease-8O5/Query [Figure 2]. Discovery studio is used to view data analysis and docking visualization. | Figure 1: Results of FAD ligand redocking against Nox. FAD: Flavin adenine dinucleotide
Click here to view |
Methods
OPEN BABEL 2.4.1 software Arizona, USA was used to convert ligands in SDF format to 3D structure PDB format. The 3D protein structure was downloaded from the RCSB protein database. Redocking is done first with each native ligand with the AutoDock 1.5.6 program. Then, the simulation of docking with various ligands against Nox protein using a grid center and a grid box with X, Y, and Z coordinates of 71,100, − 3,398, 62,918, respectively. Meanwhile, for all COVID-19 ligands and proteins, grid centers of −23.005, 1.142, and 1.896 were used for the X, Y, and Z coordinates. Genetic algorithm is applied as parameter in docking simulation with 100 GA run. Analysis of the ligand–receptor complex can be visualized using Discovery Studio 2020 within a 5Å radius.[16],[17]
| Results | | |
Based on the results, the binding affinity of the Nox–catechin complex interaction is − 8.30 kcal/mol, which is greater than the native ligand FAD's binding affinity of −7.62 kcal/mol. The positive control, GKT136901, on the other hand, has a greater affinity value of −8.72 kcal/mol, as seen in [Table 1] and [Table 2]. Then, [Table 3] and [Table 4] show the results, the catechin–protease coronavirus has a binding affinity of −7.89 kcal/mol, which is higher than the positive control remdesivir, which has a binding affinity of −7.50 kcal/mol, according to the results of the docking simulation between the ligand and the coronavirus protease receptor. However, following redocking [Figure 2], the native ligand in this coronavirus protease protein has a relatively high binding affinity value of −8.46 kcal/mol. | Table 1: Binding affinity and hydrogen bond in complex Nox–flavin adenine dinucleotide
Click here to view |
 | Table 3: Binding affinity and hydrogen bond in complex coronavirus protease–ligands
Click here to view |
 | Table 4: Binding affinity and hydrogen bond in complex coronavirus protease–ligand
Click here to view |
| Discussion | | |
One of the events of changing the redox state of the oxidant state in infected cells is associated with respiratory viral infections, and also plays a role in COVID-19 infection.[18],[19] Based on data obtained from several research journals, it has been shown that oxidative stress induced by Nox activation is associated with thrombotic events in COVID-19 patients.[20] Docking simulations were carried out to see the relationship between antioxidant inhibition and COVID-19 antiviral inhibition, by looking at the molecular receptor and ligand interactions, both the potential for catechin compounds to be compared with native ligands that had been redocked from each receptor and positive control from each receptor.
Docking simulations were carried out first on catechin ligands as the target compound compared with GKT136901 as a Nox-positive control to see the potential of the compound in inhibiting the Nox enzyme which is the main producer of ROS in many cells. The interactions that will be obtained are binding energy, hydrogen bonds, and hydrophobic interactions. Observations were made to obtain a score that can indicate the strength of the protein–ligand complex in relation to intermolecular interactions between the receptor and the ligand.[21] [Table 1], [Table 2], [Table 3],[Table 4] show the binding energy of the compound representing the Gibbs free energy (ΔG) in kcal/mol. The stability of the receptor–ligand complex can be obtained with negative Δ G which will form a spontaneous reaction to the binding of the receptor–ligand complex.[22] The more negative Δ G, the more stable the interactions in the complex formed.[23] Catechin has a higher binding energy value than native ligand (FAD) but slightly lower than the positive control (GKT136901). In [Figure 3] and [Figure 4], Nox-catechin complex showed hydrophobic interactions with Ile538, Trp695, Pro460, and Phe461. The Nox–FAD complex exhibits hydrophobic interactions of Tyr445, Pro460, Trp695, Phe461, and Ile538. Meanwhile, the Nox–GKT136901 complex showed hydrophobic interactions with Ile538, Arg478, Val480, His459, Trp695, Phe461, and Pro460. Hydrogen bonding is usually considered a facilitator for receptor–ligand binding.[24] Donors and acceptors establish hydrogen bonds, and hydrogen bond donors are typically found in receptors.[25] Nox–catechin has five hydrogen bonds at residues Trp695, Pro460, Thr541, His476, and Arg478. Arg478 and Trp695 residues act as hydrogen bond donors, while Thr541, His476, Pro460, and Trp695 act as hydrogen bond acceptors. The Nox–FAD complex has five hydrogen bonds at residues Pro460, His459, His476, Arg478, and Thr 462. The residues Arg478 and Thr462 act as hydrogen bond donors, whereas Pro460 and His476 act as hydrogen bond acceptors. The Nox–GKT136901 complex has three hydrogen bonds Trp695, Pro460, and His459, with residues His459 and Trp695 acting as hydrogen bond donors, while Pro460 as hydrogen bond acceptors.
Hydrogen interactions and hydrophobic contacts are two types of receptor and ligand interactions that can show bond stability; the more the number of bonds formed, the higher the complex bond affinity.[26],[27] In the interaction between the receptor and the compound, hydrogen bonds will be represented by a green dotted line, while hydrophobic bonds are purple. The existence of competitiveness between ligands and receptors can be observed through the residues bound to the ligands, which indicates that if there are the same or more residues, the ligands will compete with each other.[28]
On the other hand, the interaction of the ligand and the COVID-19 receptor was also seen with a docking simulation. The binding affinity of catechin and remdesivir to the coronavirus protease is shown in [Table 2] where the binding affinity of catechin to the coronavirus protease protein is lower than that of remdesivir. Binding affinity is a parameter of protein binding strength to ligands. The smaller the binding affinity, the stronger the ligand and protein bonds. The binding strength or low binding affinity of catechin compared to remdesivir is due to the interaction between the amino acid residues of the coronavirus protease more than remdesivir. [Figure 5] and [Figure 6] showed six hydrogen interactions (Gly143, Ser144, Glu166, Arg188, Leu141, and Cys145) and three hydrophobic interactions (His41, Met49, and Met165) of catechin with amino acid residues of corona proteases, whereas remdesivir has only five hydrogen interactions (Gly143, Ser144, Cys145, Glu166, and Gln189) and three hydrophobic interactions (Met165, Leu167, and Pro168). The overlapping contacts of remdesivir with native ligands in the corona protease active site area with amino acid residues Gly143, Ser144, Cys145, Glu166, and Gln189 through hydrogen interactions have led to research on remdesivir as a coronavirus protease inhibitor.Similar interactions observed when catechin was docked against coronavirus proteases, specifically with amino acid residues Gly143, Ser144, Glu166, Arg188, Leu141, and Cys145, suggest catechin's potential as coronavirus protease inhibitors. [Figure 5] depicts catechin's contact with coronavirus protease amino acid residues, while [Figure 6] depicts remdesivir's interaction with coronavirus protease amino acid residues. | Figure 5: Ligand positions on coronavirus protease: catechin (a) and remdesivir (b)
Click here to view |
 | Figure 6: Interaction coronavirus protease with ligand: catechin (a) and remdesivir (b)
Click here to view |
| Conclussions | | |
According to a docking simulation, catechin, which has antioxidant activity against Nox proteins, which are ROS producers, can also inhibit the coronavirus protease protein, where the inhibition occurs when compared to remdesivir, a drug commonly used as a COVID-19 drug, catechin can help COVID-19 patients'respiratory cells.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
| References | | |
| 1. | Li Q, Guan X, Wu P, Wang X, Zhou L, Tong Y, et al. Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia. N Engl J Med 2020;382:1199-207.  |
| 2. | Marco C, Michael R, Arturo C, Scott CD, Raffaela DN. Features, evaluation and treatment coronavirus (COVID-19). In: StatPearls. Vol. 1. Treasure Island (FL): StatPearls Publishing; 2022. p. 1-17. |
| 3. | Samir D, Dalal D, Noura A. Effect of routine iron supplementation on copper level and oxidative stress status in pregnant women. Asian Pacific J Reprod 2020;9:64-9. |
| 4. | Ntyonga-Pono MP. COVID-19 infection and oxidative stress: An under-explored approach for prevention and treatment? Pan Afr Med J 2020;35:12. |
| 5. | Lammi C, Arnoldi A. Food-derived antioxidants and COVID-19. J Food Biochem 2021;45:e13557. |
| 6. | Youn HS, Lee JY, Saitoh SI, Miyake K, Kang KW, Choi YJ, et al. Suppression of MyD88- and TRIF-dependent signaling pathways of Toll-like receptor by (-)-epigallocatechin-3-gallate, a polyphenol component of green tea. Biochem Pharmacol 2006;72:850-9. |
| 7. | Hernndez-Santoyo A, Yair A, Altuzar V, Vivanco-Cid H, Mendoza-Barrer C. Protein-protein and protein-ligand docking. Protein Eng Technol Appl 2013; 3:63-81. |
| 8. | Chaudhary KK, Mishra N. A review on molecular docking: Novel tool for drug discovery. JSM Chem 2016;4:1029. |
| 9. | Martínez-Campos Z, Pastor N, Pineda-Urbina K, Gómez-Sandoval Z, Fernández-Zertuche M, Razo-Hernández RS. In silico structure-based design of GABAB receptor agonists using a combination of docking and QSAR. Chem Biol Drug Design 2019;94:1782-98. |
| 10. | Sirokmány G, Donkó Á, Geiszt M. Nox/Duox family of NADPH oxidases: Lessons from knockout mouse models. Trends Pharmacol Sci 2016;37:318-27. |
| 11. | Gao HM, Zhou H, Hong JS. NADPH oxidases: Novel therapeutic targets for neurodegenerative diseases. Trends Pharmacol Sci 2012;33:295-303. |
| 12. | Yi J, Yuan Y, Zheng J, Zhao T. Hydrogen sulfide alleviates uranium-induced rat hepatocyte cytotoxicity via inhibiting No×4/ROS/p38 MAPK pathway. J Biochem Mol Toxicol 2019;33:e22255. |
| 13. | Katalinić V, Milos M, Modun D, Musić I, Boban M. Antioxidant effectiveness of selected wines in comparison with (+)-catechin. Food Chem 2004;86:593-600. |
| 14. | Mothay D, Ramesh KV. Binding site analysis of potential protease inhibitors of COVID-19 using AutoDock. Virusdisease 2020;31:194-9. |
| 15. | Khomich OA, Kochetkov SN, Bartosch B, Ivanov AV. Redox biology of respiratory viral infections. Viruses 2018;10:E392. |
| 16. | Rodrigues LB, Oliveira Brito Pereira Bezerra Martins A, Cesário FR, Ferreira E Castro F, de Albuquerque TR, Martins Fernandes MN, et al. Anti-inflammatory and antiedematogenic activity of the Ocimum basilicum essential oil and its main compound estragole: In vivo mouse models. Chem Biol Interact 2016;257:14-25. |
| 17. | Abou El-Soud NH, Mohamed D, El-Kassem LA, Khalil M. Chemical composition and antifungal activity of Syzygium aromaticum L. essential oil. Iran J Med Aromat Plants 2017;33:552-61. |
| 18. | Delgado-Roche L, Mesta F. Oxidative stress as key player in severe acute respiratory syndrome coronavirus (SARS-CoV) infection. Arch Med Res 2020;51:384-7. |
| 19. | Suhail S, Zajac J, Fossum C, Lowater H, McCracken C, Severson N, et al. Role of oxidative stress on SARS-CoV (SARS) and SARS-CoV-2 (COVID-19) infection: A review. Protein J 2020;39:644-56. |
| 20. | Violi F, Oliva A, Cangemi R, Ceccarelli G, Pignatelli P, Carnevale R, et al. No×2 activation in COVID-19. Redox Biol 2020;36:101655. |
| 21. | Pantsar T, Poso A. Binding affinity via docking: Fact and fiction. Molecules 2018;23:E1899. |
| 22. | Afriza D, Suriyah WH, Ichwan SJ. In silico analysis of molecular interactions between the anti-apoptotic protein survivin and dentatin, nordentatin, and quercetin. J Phys Conf Ser 2018;1073: 032001. |
| 23. | Fitriani IN, Ansory HM. Molecular docking study of nutmeg ( Myristica fragrans) constituents as anti-skin cancer agents. J Kim Pendidik Kim 2021;6:14-22. |
| 24. | Chen D, Oezguen N, Urvil P, Ferguson C, Dann SM, Savidge TC. Regulation of protein-ligand binding affinity by hydrogen bond pairing. Sci Adv 2016;2:e1501240. |
| 25. | Ul-Haq Z, Khan W, Kalsoom S, Ansari FL. In silico modeling of the specific inhibitory potential of thiophene-2,3-dihydro-1,5-benzothiazepine against BChE in the formation of β-amyloid plaques associated with Alzheimer's disease. Theor Biol Med Model 2010;7:1-26. |
| 26. | Wu MY, Dai DQ, Yan H. PRL-Dock: Protein-ligand docking based on hydrogen bond matching and probabilistic relaxation labeling. Proteins 2012;80:2137-53. |
| 27. | Saputra DE, Handayani N, Wartono MW. Isolation and identification of B-sitosterol and stigmasterol mixture from root bark of slatri ( Calophyllum soulattri Burm. f). ALCHEMY J Penelit Kim 2016;10:87. |
| 28. | Holshue ML, DeBolt C, Lindquist S, Lofy KH, Wiesman J, Bruce H, et al. First case of 2019 novel coronavirus in the United States. N Engl J Med 2020;382:929-36. |
[Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6]
[Table 1], [Table 2], [Table 3], [Table 4]
|
Search Pubmed for