INTRODUCTION:

Coronavirus disease or COVID-19 is a global pandemic caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)¹. This virus is the seventh coronavirus known to infect humans after SARS-CoV, MERS-CoV, HKU1, NL3, OC43, and 229E². It could be transmitted from human to human through respiratory droplets and saliva that entered the human body^3,4. Furthermore, the virus binds to angiotensin-converting enzyme 2 (ACE-2) and it induces infection. Moreover, various symptoms are developed, including fever, dry cough, pneumonia, chest pain, and difficulty of breathing^5,6. Several COVID-19 patients also continue to experience fatigue, respiratory and neurological symptoms^3,7.

SARS-CoV-2 binds to the receptor binding-domain of ACE-2. Continuous mutations in the spike glycoprotein of SARS-CoV-2 showed that variant Alpha in England and variant Delta in India could enhance ACE-2 binding ability and reduced it sensitivity to antibody neutralization^8,9,10. Furthermore, it causes a higher spreading rate and viral growth⁹. Blocking the receptor binding-domain of ACE-2 with a specific ligand can prevent SARS-CoV-2 binding and therefore prevent its cellular entry and injury¹¹. The case number of COVID-19 is still increasing up to 1,641,194¹². Meanwhile, only 2.5% of people in Indonesia are fully vaccinated as of April 2021¹³. Furthermore, a specific cure for COVID-19 has not been found yet. Moreover, various drug candidates are still in the preclinical or clinical trial stage^14,15. As the fourth most populous country in the world, Indonesia has the urgency for developing COVID-19 drugs.

Various treatment is developed for treating COVID-19, such as convalescent plasm¹⁶, vaccine design, and natural medicine development. The traditional medicine or natural medicine has long been used as prevention or treatment for human diseases and it gives a positive impact in human immune system^17,18. The use of traditional medicinal plants in those practices becomes more common not only in a developing country but also in developed countries. Those medicinal plants can be used as sources for drug development, including COVID-19 antiviral drugs. Khayrani et al. have shown that Sulawesi propolis may prevent the interaction between SARS-CoV-2 and ACE-2¹⁹. Flavonoid and polyphenolic composition have antiviral properties that can be found in traditional medicinal plants²⁰. The (S, S) -2- {1-Carboxy-2- [3- (3,5-Dichloro-Benzyl) -3h-Imidazole-4-Yl] - Ethylamino}-4-Methyl-Pentanoic Acid (MLN-4760), a potent inhibitor which was resolved bound to ACE-2 using X-ray crystallography, and sulabiroins A are commonly used as native and comparative inhibitor respectively^19,20,21.

The activity and drug-likeness of the active compounds of traditional medicine plants were predicted and molecular docking were conducted to identify the interaction between the active compounds and ACE-2. Toxicity assay is also conducted to predict the toxicity class, lethal dose, organ toxicity, and toxicity endpoints. This in silico study provides initial data for further study in vitro and in vivo studies. It helped to select potential compounds to reduce the failure rate in research¹⁵. The aim of this study is to predict the ability of the active compounds derivate from traditional medicinal plants as a promising inhibitor of ACE-2 protein.

MATERIALS AND METHODS:

Materials:

Forty-three active compounds data of traditional medicinal plant were obtained from PubChem database (https://pubchem.ncbi.nlm.nih. gov/). MLN-4760 and sulabiroins A were selected as native inhibitors and comparative inhibitors, respectively^19,21. The data of Simplified Molecular-Input Line-Entry System (SMILES) notation of each compound was collected. Furthermore, the 3D structure of active compounds were obtained in sdf format then converted into pdbqt format with Openbabel application in PyRx software. The 3D structure of ACE-2 in complex with inhibitor MLN-4760 was obtained through RCSB Protein Data Bank (PDB) (https://www.rcsb.org/) with PDB ID 1R4L. Moreover, the 1R4L protein was prepared with ChimeraX software by removing the native ligand and water molecules²².

Methods of Molecular Docking Simulation and Visualization of Ligands and ACE-2 Complex:

Molecular docking was conducted by specific docking with grid size according to MLN-4760 inhibitor. The grid was adjusted by using PyRx software with center position X: 40.2324, Y: 6.5102, Z: 28.6192, and dimension (Å) X: 15.0143, Y: 10.7836, Z: 12.7363. A negative binding affinity score indicated the strength of bonding between the protein and the ligand. The smaller the score, the stronger the bond^23,24. Furthermore, the complexes of ACE and potential ligands were visualized by using ChimeraX software and analyzed by using LigPlot+ software to identify the amino acid residues interaction^22,25.

Pharmacokinetic Prediction of Potential Ligands:

Drug likeness of potential compounds was analyzed by using SWISS ADME webserver (http://www.swissadme.ch/index.php)²⁶. The potential compound is required to fulfill the requirements from the Lipinski Rule of Five²⁷.

Toxicity Analysis:

Toxicity analysis of potential compounds was identified by using ProTox-II webserver (https://tox-new.charite.de/protox_II/index.php?site=compound_input). This analysis aimed to predict toxicity class, lethal dose, organ toxicity, and toxicity endpoints²⁸.

RESULT:

Molecular Docking Simulation and Visualization of Ligands and ACE-2:

Among forty-three compounds of potential ligands, two compounds showed a lower binding affinity score than the native ligand (control). However, quercetin and indirubin had the lowest binding affinity score with -9.0 kcal/mol and -8.9 kcal/mol, respectively (Table 1).

Table 1. The result of binding affinity score between potential compounds and 1Rr 4Ll

No.	Pubchem ID	Ligands Name	Binding Energy (kcal/mol)	No.	Pubchem ID	Ligands Name	Binding Energy (kcal/mol)
1	5280343	Quercetin	-9.0	24	10742	Syringic Acid	-6.3
2	10177	Indirubin	-8.9	25	11787114	Silvestrol	-6.2
3	448281	MLN-4760 (Native Control)	-8.8	26	5281783	Ethyl p-methoxycinnamate	-6.2
4	5280863	Kaempferol	-8.7	27	689043	Caffeic Acid	-6.2
5	5287969	Flavopiridol	-8.6	28	11148	Trimyristin	-6.2
6	638024	Piperine	-8.6	29	111037	Alpha-Terpinyl Acetate	-6.1
7	969516	Curcumin	-8.6	30	2519	Caffeine	-6.0
8		Sulabiroins A (Comparative Control)	-8.6	31	370	Gallic Acid	-6.0
9	1794427	Chlorogenic Acid	-8.4	32	4276	Myristicin	-6.0
10	9064	Catechin	-8.3	33	6651	Terpin	-6.0
11	3885	Beta-Lapachone	-8.2	34	8468	Vanillic Acid	-6.0
12	285033	Homoharingtonie	-8.1	35	637542	P-Coumaric Acid	-5.8
13	3220	Emodin	-8.1	36	72	Protocatechuic	-5.8
14	3213	Ellipticine	-8.0	37	91749664	2alpha,9-Dihydroxy-1,8-Cineole	-5.7
15	6918670	Ingenol Mebutate	-8.0	38	36284	4-Ipomeanol	-5.6
16	5280961	Genistein	-7.8	39	452548	Teniposide	-5.6
17	5281708	Daidzein	-7.7	40	1254	Menthol	-5.5
18	119287	Cucurbitacin	-7.6	41	26447	Menthone	-5.4
19	64971	Betulinic Acid	-7.4	42	3314	Eugenol	-5.4
20	5281794	6-Shogaol	-6.8	43	11005	Myristic Acid	-5.3
21	119307	Ginsenoside RH2	-6.6	44	10819	Perillyl Alcohol	-5.2
22	445858	Ferulic Acid	-6.4	45	2758	Eucalyptol	-5.1
23	64945	Ursolic Acid	-6.4	45	2758	Eucalyptol	-5.1

(a)

(b)

(c)

(d)

Figure 1. The ligand structures and amino acid residues of (a) MLN-4760; (b) Sulabiroins A; (c) Quercetin; (d) Indirubin complexes with ACE-2 protein

Analysis of Amino Acid Residue within Ligands and ACE-2 Complex

Figure 1 showed that all the ligands were bound at the same location with the native ligand and those ligands could successfully form hydrogen and hydrophobic bond within the binding pocket of ACE-2 receptor. Furthermore, amino acid residues of ligands and ACE-2 receptor complex were analyzed (Table 2).

Table 2. Amino acid residues of ligands and ACE-2 protein complex

Ligands	SMILES	Hydrogen Bonds	Hydrophobic Bonds
MLN-4760 (Native ligand)	CC(C)CC(C(=O)O)NC(CC1=CN=CN1CC2 =CC(=CC(=C2)Cl)Cl)C(=O)O	Arg273: 2.93 Å His345: 2.81 Å Pro346: 3.08 Å His378: 3.13 Å Asp382: 2.84 Å Glu402: 2.96 Å His505: 3.20 Å Tyr515: 3.04 Å	Thr347, Met360, Asp368, Thr371, His374, Glu375, Phe504, Tyr510
Sulabiroins A (Comparative Ligand)	[H][C@@]12COC[C@@]1([H])[C@H](C1=CC (OC)=C3OCOC3=C1)C1=C(C2)C=C2OCOC2 =C1OC	His374: 3.28 Å Tyr515: 3.10 Å	Trp271, Arg273, Phe274, His345, Pro346, Glu375, Thr371, Glu402, Arg518
Quercetin	C1=CC(=C(C=C1C2=C(C(=O)C3=C(C=C (C=C3O2)O)O)O)O)O	Ala348: 3.09 Å Glu402: 2.78 Å	His345, Pro346, Thr347, Thr371, His374, Glu375, Tyr510, Tyr515
Indirubin	C1=CC=C2C(=C1)C(=C(N2)O)C3=NC4 =CC=CC=C4C3=O	His345: 2.94 Å His374: 2.87 Å Glu375: 2.95 Å	Pro346, Thr347, Ala348, Thr371, Glu402, His505, Tyr510, Tyr515

Notes: The bold letters indicated the similar bonds as compared to the control

Table 3. Drug-likeness prediction of potential ligands

Compound	Lipinski Rule of Five					Eligibility	GI Absorption
Compound	MW	HBA	HBD	MR	LogP	Eligibility	GI Absorption
MLN-4760 (Native Ligand)	428.31	6	3	107.76	-0.25	Yes	High
Sulabiroins A (Comparative ligand)	398.41	7	0	102.06	2.16	Yes	High
Quercetin	302.24	7	5	78.03	-0.56	Yes	High
Indirubin	262.26	3	2	80.62	1.70	Yes	High

Note: MW=Molecular Weight; HBD=Hydrogen Bond Donors; HBA=Hydrogen Bond Acceptors; LogP=High Lipophilicity; MR=Molar Refractivity

Table 4. Toxicity prediction of potential ligands

Compound	LD₅₀ (mg/kg¹)	Toxicity Class	Accuracy (%)	Probability Toxicity
Compound	LD₅₀ (mg/kg¹)	Toxicity Class	Accuracy (%)	H	Ca	Im	M	Cy
MLN-4760 (Native ligand)	3000	5	67.38	0.71 (I)	0.68 (I)	0.93 (I)	0.74 (I)	0.72 (I)
Sulabiroins A (Comparative ligand)	500	4	68.07	0.85 (I)	0.60 (BT)	0.99 (A)	0.63 (BT)	0.91 (I)
Quercetin	159	3	100	0.69 (BT)	0.68 (BT)	0.87 (I)	0.51 (BT)	0.99 (I)
Indirubin	1500	4	54.26	0.57 (BT)	0.61 (BT)	0.89 (I)	0.50 (BT)	0.66 (BT)

Notes: H = Hepatotoxicity; Ca = Carcinogenicity; Im = Immunotoxicity; M = Mutagenicity; Cy = Cytotoxicity. Numbers given in probability toxicity are confidence estimate for the prediction, followed by its status: I = Inactive; A = Active; BT = Below Threshold

The druglikeness of potential ligands:

All the ligand compounds are eligible as drug candidates according to Lipinski Rules of Five and it has high GI absorption (Table 3).

Toxicity of potential ligands:

Table 4 shows that both quercetin and indirubin had a lower toxicity class than the native ligand with LD₅₀ 159 mg.kg^-1 and 1500 mg.kg^-1, respectively.

DISCUSSION:

The angiotensin-converting enzyme (ACE)-related carboxypeptidase, ACE-2, is a type I integral membrane protein of 805 amino acids that contains one HEXXH-E zinc-binding consensus sequence²¹. ACE-2 is critical for maintaining the homeostasis of renin-angiotensin system (RAS), which regulates the blood pressure and the balance of fluids and salt in various organs, including the heart, kidneys, and lungs²⁹. The ACE-2 implicated the regulation of heart function and is considered as a functional receptor or the coronavirus that causes severe acute respiratory syndrome (SARS). The viral entry process consist of three steps. Firstly, the N-terminal portion of S1 protein of the virus bind to a pocket of the ACE-2 receptor. Secondly, transmembrane protease serine 2 (TMPRSS2) conduct a proteolytic cleavage between the S1 and S2 viral protein. Lastly, after S1 detachment, the remaining S2 unit undergoes a conformational rearrangement which lead to the fusion between the viral and cellular membrane^30,31. Certain ligands could be used to inhibit the fusion. In this study, the redocking method was conducted between ACE-2 protein and native ligand MLN-4760 and comparative ligand sulabiroins A to evaluate the accuracy of screening process in comparison with in vitro study. The grid size of docking with center position X: 40.2324, Y: 6.5102, Z: 28.6192, and dimension (Å) X: 15.0143, Y: 10.7836, Z: 12.7363 was adjusted into a specific site of native ligand MLN-4760 that has been confirmed with in vitro research from the previous study to inhibit the ACE-2 activity¹⁹.

The score of native ligand and comparative ligand showed a different result as compared to the previous journal with binding affinity score -8.8kcal/mol and -8.6 kcal/mol, respectively¹⁹. The score difference could happen due to the different scoring function between the program algorithm used by the previous journal – Autodock Vina – and this research – Autodock 4. Autodock Vina is an empirical and knowledge-based hybrid scoring function, while Autodock 4 were based on the AMBER force field. AutoDock 4 tends to have better correlation coefficient with experimental binding affinity than that by the Autodock Vina approach, thus gives higher accuracy and precision of the calculated binding energies³². This difference in scoring function will gives a slight different outcoming results in the ligand and protein receptors. More hydrophobic interaction would lead to more negative binding energy score. It’s because hydrophobic bonds have lower binding energy than hydrogen bonds³³^,³⁴. In contrast, a higher formation of hydrogen bonds would give more positive result. The binding affinity score demonstrated the amount of energy needed by the ligand to interact with the receptor’s binding site. Lower binding affinity is considered more stable and stronger³⁵. Furthermore, the top two candidate compounds based on the molecular docking result were visualized by using Chimera X.

The MLN-4760 formed eight hydrogen bonds in total with five essential amino acid residues such as Arg273, His345, Pro346, His505, and Tyr515 that responsible for substrate binding and catalysis¹⁹. The terminal carboxylate of MLN-4760 is H-bonded to the side chain of Arg273, His345, and His505; while 2° amine of MLN-4760 is H-bonded to His345 and Pro346¹⁹. Arg273 was found to be critical for substrate binding and its replacement causes enzyme to be inactive³⁶. In addition, the phenolic group of Tyr515 bonds with zinc-bound carboxylate group of MLN-4760 and contribute for the carboxyl anion stabilization by mimicking the zinc-bound tetrahedral intermediate characteristic of nucleophilic attack of the scissile bond by the zinc-bound water during peptide hydrolysis¹⁹. The sulabiroins A compound as the comparative ligand only bond only had an essential residue that is Tyr515 with a distance of 3.10 Å. Among the candidate compounds, indirubin was observed to have an interaction bond with the important residue His345 at 2.94 Å in distance. Indirubin can be found in Isatis indigotica, Indigofera tinctoria, Couroupita guianensis, Calanthe discolor Lindl, Calanthe liukiuensis Schltr, Baphicacanthus cusia, Cephalanceropsis gracilis, and Polygonum tinctorium³⁷. Even though quercetin has the lowest score in binding energy, it has no interaction with the important residue. Therefore, it could be suggested that quercetin has different bond with ACE-2 receptor and has no inhibitor properties in vitro or in vivo³⁸.

The potency of potential ligands were predicted by using Lipinski Rules of Five (Ro5) with requirement including (1) molecular weight ≤500 Dalton, (2) hydrogen bond acceptors ≤10, (3) hydrogen bond donors ≤5, (4) high lipophilicity ≤5, and (5) molar refractivity between 40-130²⁷. These physicochemical properties are important in oral absorption since it affected the aqueous solubility and intestinal permeability of the compound. Potential ligands will absorbed by duodenum’s epithelial cells called enterocytes via paracellular (between enterocytes), transcellular (passive diffusion through enterocytes, the most common drug absorption route), or active transport (use transport protein). The process is followed by diffusion across the cell, through the basolateral membrane, and finally into the blood³⁹. Ligands that fulfill the Ro5 have a higher chance to be orally bioavailable and associated with 90% of orally active drugs that have achieved phase II clinical status²⁷. According to study by Giménez et al, among 60 small molecule compounds obtain from 82 drugs listed in IMS-Health Institue, 89% were fit the Ro5 requierments⁴⁰. This finding is highlighted the importance of Ro5 as a pre-filter, but not the only consideration, in drug development.

After absorption, the drug is transported to the liver and undergo hepatic metabolism before reaching the systemic circulatory system⁴⁰. Using drug repeatedly can caused an accumulation of drug and it is by products in the liver and can lead to liver damage or failure, known as hepatotoxicity. Meanwhile, assessment in toxicity endpoints is needed to avoid the adverse drug reaction in patients. Score in organ toxicity and toxicity endpoints are estimated score which followed by its status. The confidence estimation scores below 0.70 is considered under the threshold and safe. Furthermore, toxicity prediction demonstrated that MLN-4760 had inactivity for hepatotoxicity, carcinogenicity, immunotoxicity, mutagenicity, and cytotoxicity. Moreover, both quercetin and indirubin are also suggested safe and they had no probability for inducing hepatotoxicity, carcinogenicity, immunotoxicity, mutagenicity, and cytotoxicity. Moreover, this study of COVID-19 is necessary to remain studied and updated⁴¹. Furthermore, experiment by using in vitro and in vivo are still needed for further analysis and confirmed the in silico result.

CONCLUSION:

SARS-CoV-2 binds to the receptor binding-domain of human ACE-2. Blocking it with a specific ligand could prevent SARS-CoV-2 binding and therefore prevent its cellular entry. Various ligands derivate from traditional medicinal plants are considered for having huge potential as an antiviral drug. Based on the molecular docking result, Indirubin showed a lower energy binding affinity score as compared to the control. Furthermore, it interacted with similar amino acid residue as control, low toxicity class, and no tendency of organ toxicity. Therefore, it is suggested as a promising compound for further assessment.

CONFLICT OF INTEREST:

The authors have no conflicts of interest regarding this investigation.

ACKNOWLEDGMENTS:

Authors thank to Faculty of Biotehnology, University of Surabaya for supporting this research.

REFERENCES:

1. Jain RS, Awad BB, Patil SB, Patil PA, Karnawat DR. Review on coronavirus its different types. Asian Journal of Pharmaceutical Research 2020; 10(2): 115-123. doi: 10.5958/2231-5659.2020.00022.3

2. Andersen KG. Rambaut A. Lipkin WI. Holmes EC. Garry RF. The proximal origin of SARS-CoV-2. Nat. Med. 2020; 26(4):450-455. doi.org/10.1038/s41591-020-0820-9

3. Jan H. Faisal S. Khan A. Khan S. Usman H. Liaqat R. Shah SA. COVID-19: Review of epidemiology and potential treatments against 2019 novel coronavirus. Discoveries (Craiova) 2020; 8(2):e108. doi.org/10.15190/d.2020.5.

4. Naresh BV. A review of the 2019 novel coronavirus (COVID-19) pandemic. Asian Journal of Pharmaceutical Research 2020; 10(3): 233-238. doi: 10.5958/2231-5691.2020.00040.4

5. Starr TN. Greaney AJ. Hilton SK. Ellis D. Crawford KHD. Dingens AS. Navarro MJ. Bowen JE. Tortorici MA. Walls AC. King NP. Veesler D. Bloom JD. Deep mutational scanning of SARS-CoV-2 receptor binding domain reveals constraints on folding and ACE2 binding. Cell 2020; 182(5):1295-1310.e20. doi.org/10.1016/j.cell.2020.08.012.

6. Dewangan V, Sahu R, Stapathy T, Roy A. The exploring of current development status and the unusual symptoms of Coronavirus pandemic (COVID-19). Research Journal of Pharmacology and Pharmacodynamics 2020; 12(4): 172-176. doi: 10.5958/2321-5836.2020.00031.2

7. Ghogare RD, Navale AS, Shaikh SB. Novel corona virus: one biological disaster of 2020. Research Journal of Science and Technology 2020; 12(2): 147-156. doi: 10.5958/2349-2988.2020.00019.4

8. Planas D. Veyer D. Baidaliuk A. Staropoli I. Guivel-Benhassine F. Rajah MM. Planchais C. Porrot F. Robillard N. Puech J. Prot M. Gallais F. Gantner P. Velay A. Le Guen J. Kassis-Chikhani N. Edriss D. Belec L. Seve A. Courtellemont L. Péré H. Hocqueloux L. Fafi-Kremer S. Prazuck T. Mouquet H. Bruel T. Simon-Lorière E. Rey FA. Schwartz O. Reduced sensitivity of SARS-CoV-2 variant delta to antibody neutralization. Nature 2021. Epub ahead of print. doi.org/10.1038/s41586-021-03777-9.

9. Conti P. Caraffa A. Gallenga CE. Kritas SK. Frydas I. Younes A. Di Emidio P. Tetè G. Pregliasco F. Ronconi G. The British variant of the new coronavirus-19 (Sars-Cov-2) should not create a vaccine problem. J Biol Regul Homeost Agents 2021; 35(1):1-4. doi.org/10.23812/21-3-E.

10. Ghogare RD, Navale AS, Shaikh SB. Novel corona virus: One biological disaster of 2020. Research Journal of Science and Technology 2020; 12(2): 147-156. doi: 10.5958/2349-2988.2020.00019.4

11. G Mostafa-Hedeab G. ACE2 as drug target of covid-19 virus treatment, simplified update review. Reports Biochem Molecular Bio 2020; 9(1): 97-105. doi.org/10.29252/rbmb.9.1.97.

12. Worldometers. Covid 19 coronavirus pandemic. 2021 available on https://www.worldometers.info/coronavirus/

13. Github. Covid-19-data. 2021 available on https://github.com/owid/covid-19-data/blob/master/public/data/vaccinations/ vaccinations.csv

14. Beigel JH. Tomashek KM. Dodd LE. Mehta AK. Zingman BS. Kalil AC. Hohmann E. Chu HY. Luetkemeyer A. Kline S. Lopez de Castilla D. Finberg RW. Dierberg K. Tapson V. Hsieh L. Patterson TF. Paredes R. Sweeney DA. Short WR. Touloumi G. Lye DC. Ohmagari N. Oh M. Ruiz-Palacios GM. Benfield T. Fätkenheuer G. Kortepeter MG. Atmar RL. Creech CB. Lundgren J. Babiker AG. Pett S. Neaton JD. Burgess TH. Bonnett T. Gresn M. Makowski M. Osinusi A. Nayak S. Lane HC. Remdesivir for the treatment of Covid-19 — Preliminary report. N. Engl. J. Med. 2020; 383(19): 1813-1826. doi.org/10.1056/NEJMoa2007764

15. Ghasemiyeh P. Mohammadi-Samani S. COVID-19 outbreak: challenges in pharmacotherapy based on pharmacokinetic and pharmacodynamic aspects of drug therapy in patients with moderate to severe infection. Heart Lung 2020; 49(6):763-773. doi.org/10.1016/j.hrtlng.2020.08.025.

16. Yadav AR, and Mohite SK. A novel approach for treatment of COVID-19 with convalescent plasma. Research Journal of Pharmaceutical Dosage Forms and Technology 2020; 12(3): 227-230. doi: 10.5958/0975-4377.2020.00037.3

17. Zhang QW. Lin LG. Ye WC. Technique for extraction and isolation of natural products: a comprehensive review. Chin Med 2018; 13(1):1-26. doi.org/10.1186/s13020-018-0177-x.

18. Shankhdhar PK, Mishra P, Kannojia P, Joshi H. Turmeric: plant immunobooster against COVID-19. Research Journal of Pharmacognosy and Phytochemistry 2020; 12(3): 174-177. doi: 10.5958/0975-4385.2020.00029.1

19. Khayrani AC. Irdiani R. Aditama R. Pratami DK. Lischer K. Ansari MJ. Chinnathambi A. Alharbi SA. Almoallim HS. Sahlan M. Evaluating the potency of sulawesi propolis compounds as ACE-2 inhibitors through molecular docking for COVID-19 drug discovery preliminary study. J. King Saud University 2021; 33(2): 101297. doi.org/10.1016/j.jksus.2020.101297.

20. Güller HI. Tatar G. Yildiz O. Belduz AO. Kolayli S. Investigation of ethanolic propolis extracts: their potential inhibitor properties against ACE-II receptors for COVID-19 treatment by molecular docking study. Archives of Microbio 2021. doi.org/10.1007/s00203-021-02351-1.

21. Towler P. Staker B. Prasad SG. Menon S. Tang J. Parsons T. Pantoliano MW. ACE2 X-Ray structures reveal a large hinge-bending motion important for inhibitor binding and catalysis. J. Biological Chemistry 2004; 279(17): 17996-18007. doi.org/10.1074/jbc.M311191200.

22. Pettersen EF. Goddard TD. Huang CC. Couch GS. Greenblatt DM. Meng EC. Ferrin TE. UCSF Chimera - A visualization system for exploratory research and analysis. J. Comput. Chem. 2004; 25(13): 1605-1612. doi.org/10.1002/jcc.20084.

23. Dallakyan S. Olson AJ. Small-molecule library screening by docking with Pyrx. Methods Mol Biol 2015; 1263:243-250. doi.org/10.1007/978-1-4939-2269-7_19.

24. Kumar RS, Basha SN, Nallasivan PK, Solomon WDS, Venkatnarayanan R. Computer aided docking studies on antiviral drugs for bird flu. Asian Journal of Research in Chemistry 2010; 3(2): 370-373.

25. Laskowski RA. Swindells MB. LigPlot+: Multiple ligand protein interaction diagrams for drug discovery. J. Chem. Inf. Model. 2011; 51(10): 2778-2786. doi.org/10.1021/ci200227u.

26. Daina A. Michielin O. Zoete V. SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci Rep 2017; 7(10):1-13. doi.org/10.1038/srep42717.

27. Limpinski CA. Lead-and-drug-like compounds: the rule-of-five revolution. Drug Discov Today Technol 2004; 1(4):337-341. doi.org/10.1016/j.ddtec.2004.11.007.

28. Banerjee P. Eckert AO. Schrey AK. Preissner R. ProTox-II: a webserver for the prediction of toxicity of chemicals. NAR 2018; 46: W257. doi.org/10.1093/nar/gky318.

29. Li Y. Zhou W. Yang L. You R. Physiological and pathological regulation of ACE2, the SARS-CoV-2 receptor. Pharmacological Research 2020; 157: 104833. doi.org/10.1016/j.phrs.2020.104833.

30. Verdecchia P. Cavallini C. Spanevello A. Angeli F. The pivotal link between ACE2 deficiency and SARS-CoV-2 infection. European J Internal Med 2020; 76:14-20. doi.org/10.1016/j.ejim.2020.04.037.

31. Gupta R. The management of coronavirus pandemic 2019-2020. Asian Journal of Pharmaceutical Research 2020; 10(4): 327-330. doi: 10.5958/2231-5691.2020.00056.8

32. Nguyen NT. Nguyen TH. Pham TNH. Huy NT. Bay MV. Pham MQ. Nam PC. Vu VV. Ngo ST. Autodock [sic] Vina adopts more accurate binding pose but Autodock4 [sic] forms better binding affinity. J Chem Inf Model 2019; 60(1): 204-211. doi.org/10.1021/acs.jcim.9b00778.

33. Khanmohammadi A. Theoritical study of various solvents effect on 5-fluorouracil-vitamin B3 complex using PCM method. J Chil Chem Soc 2019; 64(1). doi.org/10.4067/s0717-97072019000104337

34. Upgade A, Faldu N, Kaleeswaran B. In silico analysis of non-structural protein (NS4b) from DENV-2 Indian strain for antiviral drug discovery. Research Journal of Pharmacy and Technology 2018; 11(4): 1671-1676. doi: 10.5958/0974-360X.2018.00311.6

35. Pantsar T, and Poso A. Binding affinity via docking: Fact and fiction. Molecules 2018; 23(8): 1899. Doi: 10.3390/molecules23081899

36. Guy JL. Jackson RM. Jensen HA. Hooper NM. Turner AJ. Identification of critical active-site residues in angiotensin-converting enzyme-2 (ACE2) by site-directed mutagenesis. FEBS Journal 2005; 272(2): 3512-3520. doi.org/10.1111/j.1742-4658.2005.04756.x.

37. Nakamura Y, Asahi H. Altaf-Ul-Amin M. Kurokawa K. Kanasya S. Knapsack: Metabolite information. 2021 available on http://www.knapsackfamily.com/knapsack_core/information.php?mode=r&word=C00026982&key=6

38. Neto-Neves EM. Montenegro MF. Dias-Junior CA. Spiller F. Kanashiro A. Tanus-Santos JE. Chronic treatment with quercetin does not inhibit Angiotensin-converting enzyme in vivo or in vitro. Basic & Clinical Pharmacology & Toxicology 2010; 107(4): 825-829. doi.org/10.1111/j.1742-7843.2010.00583.x.

39. Doak BC. Over B. Giordanetto F. Kihlberg J. Oral druggable space beyond the rule of 5: insights from drugs and clinical candidates. Chem Bio 2014; 21(9): 1115-1142. doi.org/10.1016/j.chembiol.2014.08.013.

40. Giménez BG. Santos MS. Ferrarini M. Fernandes JPS. Evaluation of blockbuster drugs under the Rule-of-five. Pharmazie 2010; 65(2): 148-152. doi.org/10.1691/ph.2010.9733.

41. Chavan AB, Jadhav PS, Shelke S. COVID-19: Outbreak, structure and current therapeutic strategies.Asian Journal of Pharmacy and Technology 2021; 11(1): 76-83. doi: 10.5958/2231-5713.2021.00013.1

Received on 10.08.2021 Modified on 13.11.2021

Research J. Pharm. and Tech 2022; 15(9):4235-4240.

DOI: 10.52711/0974-360X.2022.00712