|Year : 2022 | Volume
| Issue : 79 | Page : 773-782
Lapachol and (α/β)-lapachone as inhibitors of SARS-CoV-2 Main Protease (Mpro) and hACE-2: ADME properties, docking and dynamic simulation approaches
Mejdi Snoussi1, Iqrar Ahmad2, Harun Patel2, Emira Noumi3, Rafat Zrieq4, Mohd Saeed5, Shadi Sulaiman6, Nasrin E Khalifa7, Fakher Chabchoub8, Vincenzo De Feo9, Mohamed A M. Gad-Elkareem10, Kaïss Aouadi11, Adel Kadri12
1 Department of Biology, University of Hail, College of Science, P.O. Box 2440, Ha'il 2440, Saudi Arabia; Laboratory of Genetics, Biodiversity and Valorisation of Bioressources, High Institute of Biotechnology--University of Monastir, Monastir 5000, Tunisia
2 Division of Computer Aided Drug Design, Department of Pharmaceutical Chemistry, R. C. Patel Institute of Pharmaceutical Education and Research, Shirpur, Maharashtra 425405, India
3 Department of Biology, University of Hail, College of Science, P.O. Box 2440, Ha'il 2440, Saudi Arabia; Laboratory of Bioressources: Integrative Biology and Recovery, High Institute of Biotechnology--University of Monastir, Monastir 5000, Tunisia
4 Department of Public Health, College of Public Health and Health Informatics, Ha'il, Saudi Arabia
5 Department of Biology, University of Hail, College of Science, P.O. Box 2440, Ha'il 2440, Saudi Arabia
6 Department of Clinical Laboratory Sciences, Faculty of Applied Medical Sciences, University of Ha'il, Ha'il, Saudi Arabia
7 Department of Pharmaceutics, College of pharmacy, University of Hail, Kingdom of Saudi Arabia; Department of Pharmaceutics, Faculty of Pharmacy, University of Khartoum, Sudan
8 Laboratoire de Chimie Appliquée: Hétérocycles, Corps Gras et Polymères, Faculté des Sciences de Sfax, Université de Sfax. B. P, 802. 3000 Sfax, Tunisie
9 Department of Pharmacy, University of Salerno, Via Giovanni Paolo II, 132, Fisciano, Salerno 84084, Italy
10 Department of Chemistry, Faculty of Science, Al--Azhar University, Assiut 71524, Egypt
11 Department of Chemistry, College of Science, Qassim University, Buraidah 51452, Saudi Arabia; University of Monastir, Faculty of Science of Monastir, Avenue of the Environment, 5019 Monastir, Tunisia
12 Department of Chemistry, Faculty of Science and Arts of Baljurashi, Albaha University, Saudi Arabia; Faculty of Science of Sfax, Department of Chemistry, University of Sfax, B.P. 1171, 3000 Sfax, Tunisia
|Date of Submission||03-Jun-2022|
|Date of Decision||17-Jul-2022|
|Date of Acceptance||25-Jul-2022|
|Date of Web Publication||15-Sep-2022|
Department of Biology, University of Hail, College of Science, P.O. Box 2440, Ha'il 2440
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Background: Tabebuia impetiginosa is an important medicinal plant rich in lapachol, α-lapachone, and β-lapachone known to possess several biological activities. Objective: In this study, we investigated the drug potential of lapachol, α-lapachone, and β-lapachone using molecular docking, molecular dynamic (MD), and drug-likeness properties. Materials and Methods: The computational study was performed using SwissADME software for the determination of the pharmacokinetic properties of the tested compounds. AutoDock Vina and Genetic Optimization for Ligand Docking (GOLD) were used for the docking analysis, and MD simulations were run using Schrodinger's Desmond Simulation. Results: The three compounds lapachol, α-lapachone, and β-lapachone binds to cysteine (Cys)-histidine (His) catalytic dyad (Cys145 and His41) along with the other residues with, respectively, the following docking score 48.69, 47.06, and 47.79. Against viral entry receptor, human angiotensin-converting enzyme 2 (hACE-2), α-lapachone exhibited the highest GOLD Fitness score complex (54.82) followed by lapachol (42.53) and β-lapachone and hACE-2 (38.74) generating several active sites in the target proteins. A 100 ns MDs simulation study revealed the stable conformation of bioactive compounds within the cavity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) of hACE-2 protein and main protease (Mpro). From the dynamic study, it was observed that lapachol was tightly bound with catalytic dyad residue Cys145 of Mpro with more than 40% time of simulation, also post-simulation MM-GBSA binding free energy (ΔG Bind) revealed the highest energy score (−51.18 ± 5.14 kcal/mol) among the evaluated complex. Moreover, the absorption, distribution, metabolism, and excretion (ADME) properties demonstrated that the investigated compounds passed the pharmacokinetic and drug-likeness criteria without undesirable effects. Conclusion: The computational study highlighted that these compounds could be highly recommended and developed as part of an effective drug against the SARS-CoV-2 virus.
Keywords: Computer-aided strategies, drug repurposing, hACE-2, Mpro, SARS-CoV-2
|How to cite this article:|
Snoussi M, Ahmad I, Patel H, Noumi E, Zrieq R, Saeed M, Sulaiman S, Khalifa NE, Chabchoub F, De Feo V, M. Gad-Elkareem MA, Aouadi K, Kadri A. Lapachol and (α/β)-lapachone as inhibitors of SARS-CoV-2 Main Protease (Mpro) and hACE-2: ADME properties, docking and dynamic simulation approaches. Phcog Mag 2022;18:773-82
|How to cite this URL:|
Snoussi M, Ahmad I, Patel H, Noumi E, Zrieq R, Saeed M, Sulaiman S, Khalifa NE, Chabchoub F, De Feo V, M. Gad-Elkareem MA, Aouadi K, Kadri A. Lapachol and (α/β)-lapachone as inhibitors of SARS-CoV-2 Main Protease (Mpro) and hACE-2: ADME properties, docking and dynamic simulation approaches. Phcog Mag [serial online] 2022 [cited 2022 Sep 26];18:773-82. Available from: http://www.phcog.com/text.asp?2022/18/79/773/356136
- Three natural bioactive compounds, namely, lapachol, α-lapachone, and β-lapachone isolated from T. impetiginosa were screened for their potential use as a promising candidate for COVID-19 Mpro and hACE-2 by using in silico approaches.
Abbreviations used: 2D: Two dimensional; 3D: Three dimensional; 3CLpro: 3-chymotrypsin like protease; Mpro: Main protease; ADME: Absorption, Distribution, Metabolism, and Excretion; COVID: Coronavirus Disease; SARS-CoV-2: Severe acute respiratory syndrome coronavirus 2; hACE-2: human Angiotensin-converting enzyme 2; TMPRSS2: Transmembrane Serine Protease 2; Cys: Cysteine; His: Histidine; GOLD: Genetic Optimisation for Ligand Docking; Autodock: Automatic Docking; MM-GBSA: Molecular Mechanics-Generalized Born Surface Area: rG: Radius Giration; RMSD: Root Mean Square Deviation; RMSF: Root Mean Square Fluctuation.
| Introduction|| |
Plant-based secondary metabolites are potent reservoirs with many therapeutic and pharmacological effects.,,, They have attracted great attention due to their secreted bioactive molecules that could be developed as powerful drugs against several diseases without or with less side effects.,,, The consumption of herbal medicine is also known to improve the immune response., Currently, the arsenal of antiviral and antibiotic drugs has been strictly compromised by the earlier devastating of COVID-19, forcing the creation of a new front-line for discovering effective drugs and new vaccines., Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) enters into host epithelial and lung cells by the interaction of spike protein to angiotensin-converting enzyme 2 (ACE-2) receptors using the cellular serine protease transmembrane serine protease 2 (TMPRSS2) for S protein priming.,, The receptor binding domain in S1 directly binds to the peptidase domain of human angiotensin-converting enzyme 2 (hACE-2).
During this epidemic, cancer patients are more exposed to infections and therefore are considered to be a highly vulnerable group. A literature survey outlined that the antiviral mechanism of lapachol and its derivatives have not been yet studied, but we inspired the use of lapachol and its analogs based on other studies using the anticancer drug on SARS-CoV-2, which enhances the body's immune response against cancer, were actually to treat COVID-19. Also, β-lapachone as a pro-drug, with the commercial name ARQ-761, is actually in phase I/II of clinical studies for solid tumors.
In silico docking, analysis has demonstrated that plant-derived molecules were able to bind to SARS-CoV-s main proteases two proteases [PLpro and 3-chymotrypsin like protease] responsible for the synthesis and maturation of the various viral polyproteins. In 2020, Nayak reviewed the interaction of peptidic and non-peptidic molecules with hACE-2 as potential inhibitors of SARS-CoV-2 attachment to human cells. It has been recently reported that linolenic and eicosapentaenoic acids highly block the entry of SARS-CoV-2 to the host cells. Wang and colleagues claimed that dalbavancin as a lipoglycopeptide antibiotic, directly binds to hACE-2, with high affinity, thereby blocking its interaction with the SARS-CoV-2 spike protein. Telmisartan (ClinicalTrials.gov ID: NCT04355936) and losartan (ClinicalTrials.gov ID: NCT04312009) were proposed as alternative options for treating COVID-19 patients before the development of acute respiratory distress syndrome. Recently, Alacepril and lisinopril were found to interact with hACE-2. Moreover, dermaseptin-S9 was able to prevent the attachment of SARS-CoV-2 spike protein to the surface of the ACE-2 receptor. Besides that, alatrofloxacin, azithromycin, cefoperazone, rifapentine, and vancomycin as antibacterial drugs have been proved to bind to ACE-2 to obstruct SARS-CoV-2 binding. Recent studies also reported the binding of nystatin and posaconazole against SARS-CoV-2 spike protein binding site. On the other hand, the antihypertensive (Azilsartan kamedoxomil, deserpidine, and reserpine), statins (Pitavastatin and simvastatin), antimigraine (Dihydroergotamine), antiasthmatic (Zafirlukast), antihistamine (Loratadine), cardiac glycoside (Digoxin), and antimalarial (Mefloquine). Mefloquine (an antimalarial drug) has been confirmed to compete with spike protein for binding to ACE-2, rather than hydroxychloroquine, which binds to another region of ACE-2., Other small molecules with anti-inflammatory actions like mycophenolic acid, pemirolast, isoniazid, and eriodictyol were also tested and demonstrated their good binding affinity to ACE-2, suggesting their importance in the treatment of COVID-19.
Till now, no specific drugs for COVID-19 are available despite some vaccines that have been commercialized by different pharmaceutical companies, but there are controversies on the side effects. In addition, the gravity of the situation requires the use of all resources to remedy which scourge to find out therapeutic agents valid for a long period. Therefore, lapachol, α-lapachone (1,2-naphthoquinone), and β-lapachone (1,4-naphthoquinone) [Figure 1] as three natural products belonging to the naphthoquinone's classes. Lapachol isolated from the heartwood of Tabebuia impetiginosa (syn. T. avellanedae) with the red type is known to cure several diseases such as herpes, malaria, cancer, fevers, eczema, ulcers, skin disorders, manage trypanosomiasis, syphilis, bacterial, and fungal infections., Lapachol has been found to possess antiviral activity against Epstein–Barr virus and enterovirus in vitro., Also, it has been reported that β-lapachone promotes the preparation of collagens and is responsible of whitening skin and hyperpigmentation skin diseases., Both α-lapachone and β-lapachone represent significant cytotoxicity on mammalian cells and were used as a potential leishmanicidal drug. β-Lapachone has been described to prevent the proliferation of cancer cells, to inhibit human lung cancer xenograft growth and angiogenesis, used as pro-drug, with commercial name ARQ-761, is in phase I/II of clinical studies for solid tumors as well as to promote various biological properties including anti-inflammatory, antibacterial, and anti-trypanosoma.,,,
|Figure 1: Structures of lapachol (1), α-lapachone (2) and β-lapachone (3)|
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Therefore, in the present study, we investigated lapachol, α-lapachone, and β-lapachone as potential inhibitor candidates for COVID-19 main protease (Mpro) and hACE-2, using modeling, virtual screening, molecular docking, and molecular dynamics (MDS) simulation with absorption, distribution, metabolism, and excretion (ADME) and target prediction.
| Materials and Methods|| |
Three-dimensional (3D) structure of 6LU7 and 2AJF was retrieved from RCSB Protein Data Bank.
Docking using autoDock Vina and Genetic Optimization for Ligand Docking (GOLD)
Docking of protein ligands was carried out using AutoDock Vina, GOLD,, and LibDock from Discovery Studio Client v184.108.40.20695. The receptor protein 6LU7 was prepared by removing water and co-crystal ligand (remdesivir), hydrogen and charges were added to the structures. The grid box dimensions as follow: x = −10.729 Å, y = 12.418 Å, z = 68.816 Å and grid box size as follows: x = 50 Å, y = 50 Å, z = 50 Å were set for 6LU7 a grid space of 0.375 Å. The ligand pdbqt file was prepared in AutoDock MG Tool. During the docking process, the ligand was kept flexible and receptors were set rigid.
Molecular dynamic (MD) simulation
Molecular docking studies predict ligand binding status in rigid protein structures (static conditions). Therefore, MD simulations were run using Schrodinger's Desmond Simulation as done previously.,,,,,
Post-simulation molecular mechanics-generalized born surface area (MM-GBSA) analysis
Post-simulation binding free energies (ΔG Bind) of the ligand–protein complexes were calculated using the molecular mechanics combined with a generalized MM-GBSA approach. The Python script thermal_mmgbsa.py was employed to assess Prime MM-GBSA binding free energy for 0–1000 frames having a 100-step sampling size in the simulation trajectory with the VSGB solvation model associated with the OPLS3e force field. VSGB is a novel energy model (VSGB 2.0) for high resolution protein structure modeling. The Prime MM-GBSA binding free energy (kcal/mol) is calculated following the same work of Patel et al.
ADMET and molecular target predictions
Pharmacokinetic assessment of lapachol, α-lapachone, and β-lapachone was performed using SwissADME,,, and pkCSM web tools.
| Results|| |
Binding Interaction of Lapachol, α-Lapachone, and β-Lapachone with Mpro
Molecular docking of the selected known bioactive compounds was performed to study their interaction mode against SARS-CoV-2 Mpro (PDB ID: 6LU7) and hACE-2 (PDB ID: 2AJF). [Figure 2] shows the binding affinities along with the neighboring residues of papain-like protease (PLpro) and human receptor protein hACE-2 interacting with the selected compounds.
|Figure 2: Time decedent RMSD of Simulated protein–ligand complex (Protein–RMSD is shown in gray while RMSD of Ligand is shown in red)|
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The three compounds lapachol, α-lapachone, and β-lapachone bind to cysteine (Cys)-histidine (His) catalytic dyad (Cys145 and His41) along with the other residues with, respectively, the following docking score 48.69, 47.06, and 47.79. Lapachol forms one H-bonds with Glu143 and other hydrophobic interactions. α-Lapachone established van der Waals interactions with Tyr54, Cys145, His164, Glu166, Leu167, Pro168, Val186, Asp187, Thr190; H-bond: Gln192; Unfavorable Bump interaction with only Arg188, Pi-Sigma interactions with Gln189 and Alkyl/Pi-Alkyl interactions with His41, Met49, and Met165 residues, however, β-lapachone binds to Mpro residues via several hydrophobic interactions.
Binding interaction of Lapachol, α-Lapachone, and β-Lapachone with hACE-2
The obtained data of docked complexes between the selected molecules and the crystal structure of hACE-2 unveiled that lapachol expressing high binding score was found to interact with binding pockets to form hydrophobic interactions with Glu310, Lys313, Phe314, Ser317, Lys416, His417, Ser420, Ile421, Ser545, Asn546, and Asp543 amino acids. α-lapachone-hACE-2 complex (54.82) generated van der Waals interactions with Ser420, Asp543, Ile544, and Ser547. The other significant interactions that stabilize α-lapachone and hACE-2 complex include Pi-Lone Pair with Ser545, C-H bonds with Ser545, Amide-Pi Stacked interactions with Asn546, and Alkyl/Pi-Alkyl with Lys416, His417, Ala533. The highest binding energy between β-lapachone and hACE-2 established H bonds interactions with Lys416, van der Waals interactions with His417, Ser420, Cys530, Lys534, His535, Asp543, Ile544, Asn546, Ser547, Pi-Lone Pair interaction with Ser545, and Alkyl/Pi-Alkyl with Ala533, Cys542 residues.
Molecular dynamics simulation
In order to understand the stability and conformations changes of the hACE-2 protein (2AJF) and Mpro (6LU7) domain complexed with the bioactive compounds lapachol and α/β-lapachone, we performed the root mean square deviation (RMSD), root mean square fluctuations (RMSF), protein–ligand contact mapping and the time-dependent radius of gyration (rGyr)., The RMSD value for the Cα atoms was computed over 100 ns simulations to evaluate the stability of all the systems. Lower the RMSD fluctuation infers a more stable structure of the protein. The RMSD plot of simulated complex is presented in [Figure 2]. The simulation results of the 2AJF-β-lapachone complex showed that ligand has crossed the RMSD value of more than 4 Å (acceptable RMSD 1–3) and was found unstable during the 100 ns time of the simulation. The RMSD of the 2AJF-α-lapachone, 6LU7-lapachol, 6LU7-α-lapachone, and 6LU7-β-lapachone was observed to be 4.2 Å, 2.4 Å, 3.0 Å, and 3.5 Å, respectively, as compared to the initial structure (zero frame ligand). Slightly higher RMSD was observed for the 2AJF lapachol at around 96 ns as shown in [Figure 3]. In the 2AJF-β-lapachone complex, the highest fluctuation was observed at a time span of 91 ns with an RMSD of 3.6 Å. To assess remdesivir stability in complex with SARS CoV-2 main protease, the RMSD value for the Cα backbone was monitored for 100 ns simulations.
During the simulation, the flexibility of the protein system was also examined by computing the RMSF of individual amino acid residues in the protein to examine the binding efficiency of bioactive compounds with hACE-2 and Mpro proteins [Figure 3]. The average RMSFs assessed for the complex of 2AJF-Lapachol, 2AJF-α-lapachone, 6LU7-Lapchol, 6LU7-α-lapachone, and 6LU7-β-lapachone and 6LU7-remdesivir are 1.123 Å, 0.893Å, 0.921 Å,1.094 Å, 1.777 Å, and 1.245 Å, respectively, that implying that hACE-2 protein and Mpro protein exhibit minimal fluctuation and relative secondary conformational stability upon binding of reported bioactive compounds.,,, All the RMSF values in Å of ligand contacted residues are listed in [Table 1].
|Table 1: RMSF values Ca atoms of ligand contacted residues with hACE-2 protein (2AJF) and Mpro protein (6LU7) after binding of lead compounds|
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Throughout the simulation, protein interactions with the ligand were also monitored. These interactions can be categorized by type, reviewed, and portrayed in [Figure 4]. The amino acid residues Asn546 and Lys313 of hACE-2 exhibited hydrogen bond and water-mediated hydrogen bond interactions with the Lapachol, as revealed by docking studies, which also existed in MD throughout the trajectory, with 46 and 64% interaction of stipulated time. The second bioactive compound α-lapachone on target 2AJF revealed significant hydrophobic interaction with hydrophobic amino acid residues Pro321 and Phe555, during the entire simulation. Apart from these residues, amino acid Val318, Gly319, Asp543, Asn546, Ser547, and Arg559 also contributed to the water-mediated hydrogen bond with the target molecule in the active site. It is noticed that simulated bioactive compound (Lapachol and α-lapachone) in 2AJF Protein mostly interacted through hydrophobic and water-mediated hydrogen bonding.
|Figure 4: Protein–ligand contact analysis of MD trajectory, monitored throughout the 100 ns simulation time|
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It was observed [Figure 2] that lapachol interacted with the Mpro active site with Gly143, Ser144, and Gln189 mainly through hydrogen bonding with 29–86% throughout the simulation time. A crucial catalytic dyad residue, Cys145, was also actively contributed by a bidentate hydrogen bond with Lapachol in the active site. The terminal carbonyl group of α-lapachone interacted with Thr190 (35%) and Gln192 (53%) via hydrogen bonding. Active site amino acid residues of 6LU7 like Asn142, Cys145, His164, Glu166, and Gln189 were also contacted with α-lapachone through water-mediated hydrogen bonding. In the complex of β-lapachone-Mpro, mainly hydrophobic and water-mediated hydrogen bond interactions were observed. In this complex, crucial residue Cys145 interacts with β-lapachone via three types of interaction, hydrogen bonding, hydrophobic, and water-mediated hydrogen bonding. Protein–ligand contact mapping shows that remdesivir binds to the main protease protein through Thr25, Thr45, Asn142, Gly143, Cys145, Glu166, Gln189, and Thr190 and exhibited more than 10% hydrogen bond interactions. Among them, catalytic dyed residue Cys145 makes all three (hydrogen, hydrophobic, and water-mediated hydrogen bonding) types of interaction with remdesivir [Figure 4].
The rGyr property was also investigated to demonstrate the stability of the bioactive compounds in the hACE-2 protein and Mpro binding pockets over a 100 ns simulation. The extension of a ligand is estimated by its rGyr, which is comparable to its principal moment of inertia [Figure 5]. A high value or abnormal variation of rGyr in different frames signifies the instability of the system, whereas a low and consistent variation of rGyr indicates the stability of the system. The bioactive compounds in complexes with hACE-2 protein and Mpro exhibited an average rGyr value of 3 Å [Table 2]. The rGyr did not show any significant changes. These constant values exhibited a consistent pattern of behavior.
|Figure 5: Radius of gyration (rGyr) graph of the simulated complex at 100 ns simulation time|
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|Table 2: Radius of gyration of and post-simulation MM-GBSA-based binding free energy (ΔG Bind) for the protein–ligand complexes|
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The MM-GBSA method uses molecular mechanics, generalized Born solvation models, and a solvent accessibility approach to estimate binding free energies (ΔG Bind) based on MD simulation trajectories. The post-simulation MM-GBSA was calculated from frame 0 to 1000 at every 10th frame, totaling 100 structures of each protein–ligand complexes, and average binding energies with standard deviation have been tabulated in [Table 2]. The calculated average ΔG Bind of the complex of 2AJF-Lapachol, 2AJF-α-lapachone, 6LU7-Lapchol, 6LU7-α-lapachone, 6LU7-β-lapachone, and 6LU7-remdesivir was found to be − 24.9477 kcal/mol, −34.0672 kcal/mol, −51.1813 kcal/mol, −42.1107 kcal/mol, −39.3305 kcal/mol, and − 46.50 kcal/mol, respectively, (49,50). 6LU7-Lapchol results displayed the promising binding free energy scores when compared with the remdesivir complex MM-GBSA calculations.
Assessment of pharmacokinetic possessions for a successful drug in the early phases of drug discovery and development through in silico ADME screens is essential to achieve their drug-likeness and minimize their risk attrition in the late stage. Results [Table 3] showed good drug-likeness properties and that the selected compounds could not be substrates of P-glycoprotein (P-gp). The cytochrome P450 monooxygenase (CYP) enzymes super-family regrouping cytochrome CYP1A2, CYP2C19, CYP2C9, CYP2D6, and CYP3A4 are important in drug metabolism in the liver and biotransformation of drugs through O-type oxidation reactions have been predicted, especially those of 2D6, 2C9, and 3A4 which are the most important forms in human. Data showed that all hits are inhibitors of CYP1A2 and CYP2C19, not inhibitors of CYP2C9 and CYP2D6; however, CYP3A4 was only inhibited by β-lapachone. The selected compounds exhibited good lipophilicity results with a bioavailability score (85%) and suitable skin permeation (LogKP) values suggesting making them easily accessible via the skin.
|Table 3: ADME profiles of lapachol, α-lapachone and β-lapachone according to SwissADME software|
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The pink area of bioavailability radar chart of three compounds [Figure 6] representing the most drug-likeness parameters justified that the designed compounds are fully included in the pink area suggesting their good oral bioavailability.
|Figure 6: Bioavailability radar of the selected compounds, based on their physicochemical indices ideal for the oral bioavailability. (a) Lapachol; (b) α-Lapachone; (c) β-Lapachone|
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BOILED-Egg graph (WLOGP vs. TPSA) indicates that the three molecules are non-substrate of P-gp [Figure 7].
Data [Figure 8] outlined that lapachol has 26% enzyme, 12% protease, and 4% of kinase, whereas α-lapachone predicts 18% enzyme, 20% protease, and 2% of kinase and β-lapachone can be targeted for 26% enzyme and 4% of the kinase.
|Figure 8: Pie-chart of top-50 target predicted for selected molecules. (a) Lapachol; (b) α-Lapachone; (c) β-Lapachone|
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| Discussion|| |
This study aimed to screen three bioactive molecules, lapachol, α-lapachone, and β-lapachone identified in the medicinal plat, T. impetiginosais that can target Mpro and hACE-2 to find novel compounds that can be used as a new drug against coronavirus as a strategy in antiviral drug discovery and development. Results were confirmed when compared to the residues of the high-volume pocket of Mpro sharing more identical amino acids. Lapachol, α-lapachone, and β-lapachone also show high binding efficiencies suggesting their high potential for repurposing. Recently, different synthetic drugs were docked with SARS-CoV-2 proteins including hydroxychloroquine, chloroquine, ivermectin, raltegravir, daclatasvir, simeprevir, cobicistat, oseltamivir, and remdesivir demonstrated that drug molecules of oseltamivir, ritonavir, remdesivir, ribavirin, and favipiravir had a greater capability to inhibit SARS-CoV-2, since they demonstrated high-affinity interactions with the COVID-19 Mpro in complex with the N3 inhibitor.,,
In order to validate our results, the viral RNA polymerase inhibitors, remdesivir have been also docked against 6LU7 and compared to lapachol, α-lapachone, and β-lapachone. Results showed that remdesivir interacts with 6LU7 forming the following interactions: H-bond with Glu166 (2.38 Å), Gln189 (2.63 Å); Carbon H-bond with Thr190 (1.86 Å); Pi-Anion with Glu166 (4.26 Å) and Alkyl/Pi-Alkyl with His41 (4.05 Å), Met49 (3.75 Å), and Ala 191 (4.34 Å) residues [Figure 9]. Based on the above data, lapachol, α-lapachone and β-lapachone shared several residues as remdesivir when interacting with 6LU7, especially those of His41, Met49, Glu166, and Gln189 (lapachol), and His41, Met49, Glu166, Gln189, and Thr190 (α-lapachone and β-lapachone). Thus lapachol, α-lapachone, and β-lapachone hold the potential to be developed as treatment toward COVID-19.
|Figure 9: GOLD Fitness docking score, 2D, 3D, and interacting residues of remdesivir with the active site of COVID-19 6LU7 (Mpro). AutoDock Vina Docking Score: remdesivir-6LU7 (-7.8 kcal/mol); Residues interacting with compounds: Conventional hydrogen bond: Glu166 (2.38 Å), Gln189 (2.63 Å); Carbon hydrogen bond: Thr190 (1.86 Å); Pi-Anion: Glu166 (4.26 Å); Alkyl/Pi-Alkyl: His41 (4.05 Å), Met49 (3.75 Å), Ala 191 (4.34 Å)|
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Previous reports have investigated the interaction between plant-derived compounds and marine-based molecules with SARS-CoV-2 key enzymes.,,,,,,, In 2020, Bhuiyan and colleagues reported that about 219 plants belonging to 83 families with antiviral activities, and among them 149 plant species (from 71 families) possess several secondary metabolites (glycosides, flavonoids, alkaloids, tannins, saponins, phenolic acids, terpenoids, coumarins, organosulfur compounds, nitrogen-containing compounds, etc.) that can interfere with SARS-CoV-2 enzymes. Using computational approaches (molecular docking and dynamic simulation), Maurya and Sharma demonstrated that traditional Kadha preparation (Ayurvedic medicine) possesses diverse phytoconstituents that can be useful for the treatment and prevention of COVID-19 virus as they showed high binding affinity (low binding energy). The same authors reported that withaferin A (−9.1 kcal/mol), stigmasterol (−8.8 kcal/mol), vicenin (−8.8 kcal/mol), and ursolic acid (−8.7 kcal/mol) were the highest molecules binding to hACE-2.
A 100 ns molecular dynamics simulation study showed the stable conformation of bioactive compounds within the cavity of hACE-2 protein and Mpro. From the dynamic study, it was assumed that the promising bioactive compound lapachol has been tightly bound with catalytic dyad residue Cys145 of Mpro with more than 40% time of simulation, also post-simulation MM-GBSA binding free energy (ΔG Bind) revealed the highest energy score (−51.18 ± 5.14 kcal/mol) among the evaluated complex.
All these findings highlighted the potential use of natural compounds from medicinal and aromatic plant extract as SARS-CoV-2 inhibitors.
| Conclusion|| |
In this study, we have demonstrated the potential of lapachol, α-lapachone, and β-lapachone as main ligands for the SARS-CoV-2 and that SARS-CoV-2 Mpro and hACE-2 may be a viable target for antiviral development. Molecular dynamics simulations were performed on protein–ligand complex using Desmond at 100 ns to investigate their binding conformational stability. The stability of the protein–ligand complex was observed to be maintained throughout the 100 ns simulations based on RMSD, RMSF, and protein–ligand interactions. Also, all the amino acid interactions identified during docking studies of the bioactive compounds were also shown during the dynamic simulation study. Especially, lapachol was found that have tightly bound to Mpro crucial residue Cys145 with a significant −51.1813 ± 5.14 kcal/mol ΔG Bind score. As per pharmacokinetics investigation, the compounds showed excellent drug-likeness properties. This study shows the effectiveness and importance of studying protein–ligand complex stability via dynamics to corroborate docking studies. Furthermore, these bioactive molecules would have the potential to act as promising drug candidates and could be utilized for further investigations as a template against SARS-CoV-2 with mandatory in vitro assays, before their evaluation in patients through clinical trials.
Our work shows the importance of studying protein–ligand complex stability via dynamics to corroborate docking studies. Although the results seem promising, it is important to validate this activity. Therefore, these molecules should be further investigated for in vitro and/or in vivo antiviral activity. They may also be used as templates for the development of future drugs against SARS-CoV-2 and other coronaviruses. Thus, these data may provide relevant information to advance our ability to combat COVID-19.
The authors would like to thank the Scientific Research Deanship at University of Ha'il for funding this project.
Financial support and sponsorship
This research has been funded by Scientific Research Deanship at University of Ha'il—Saudi Arabia through project number RG-20 230.
Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6], [Figure 7], [Figure 8], [Figure 9]
[Table 1], [Table 2], [Table 3]