Introduction

Coronavirus disease 2019, a pandemic caused by the deadly new strain of virus severe acquired respiratory syndrome coronavirus-2 (SARS-CoV-2) identified in December 2019 in China, has claimed millions of lives throughout the globe in several countries ¹. A total of 500 million people were affected and 6 million people were claimed globally due to COVID-19 infection as of now since its outbreak and still counting. Several symptoms from mild to severe have been reported due to the viral infection, include cold, high fever, nausea, vomit, cough, shortness of breath, loss of taste, and smell persisting over five days. There has been no cure till now ²; however, several preventive medicines such as vaccines are in the process of administration to develop immunity against the virus. In addition, several drugs like remdesivir, hydroxychloroquine, ivermectin, lopinavir, darunavir, etc. have been repurposed as a drug of choice to combat the disease. The mentioned drugs are used as temporary ‘drug of choice’ to combat the infection, however, no proven treatment is available till now. This brings us in search of alternate treatment from natural sources, bringing to this research work, which is the need of the hour. One of the most important target sites in SARS-CoV-2 is the main-protease causing the proteolytic processing of polyproteins to non-structural proteins responsible for viral replication and transcription ³. The 3C-like proteinase from SARS-CoV-2 has three domains with 306 amino acids and a molecular weight of 34.29 kDa tightly bound with X77 ligand in its active site. The main-protease is involved in the replication and transcription of the virus by forming functional proteins. 3C-like proteinase is catalytically active at amino acid residues HIS41 and CYS145 in the active center of the SARS-CoV-2 main-protease. Therefore, inhibiting the active site is an excellent solution to stop the activity and virulence of the virus.

The use of herbal and ayurvedic medicines have gained pace in recent times for treating viral disease. Traditional herbal formulations of bioactive compounds are of great interest even in the present world due to their high efficiency to cure and minimal side effects ⁴. Bioactive constituents from essential oils of Chrysopogon zizanioides is a cocktail of sesquiterpene alcohols and hydrocarbons and are widely used as a promising medicine to cure various ailments ⁵. Chrysopogon zizanioides, commonly known as ‘vetiver’, is one of the most widely used phytoconstituents in Indian medicines since ancient times due to its antioxidant, anti-inflammatory, antiviral, antimicrobial, anti-tubercular, and anticancer properties ⁶. In addition, the metabolites from leaves and roots are commonly used to cure rheumatic diseases and gastritis ⁷. The present research work retrieved the bioactive compounds from Chrysopogon zizanioides, and their antiviral potential was studied. The volatile essential oils in Chrysopogon zizanioides have an immense flavor and aroma and are used widely uses as an additive to impart flavor to water. Only a handful of studies have reported the anti-COVID potential of Chrysopogon zizanioides targeting the spike protein and ACE2 receptor; however, there has been no research on their synergistic potential against main-protease. The computational tools are rapid, comprehensive, reproducible, robust, and accurate in prediction; thus, their usage is essential in every sector. Molecular docking is one of the most important and supportive tools to study the interaction between the protein and ligand at the atomic level using various algorithms and programs to discover or invent drugs specific to the target ⁸. Therefore, the present research aims to fill the gap by exploring the individual and synergistic antiviral property of Chrysopogon zizanioides against the COVID-19 M^pro using in-silico bioinformatics tools. It is very essential and immediate measures need to be taken to contain the spread of COVID-19 infection to save the lives of people as currently repurposed drugs and treatment strategies have shown poor efficiency against the viral infection. The toxicity properties of bioactive compounds are also discussed in the study. The workflow of the research is shown in Figure 1.

Figure 1: Workflow of the research. Click here to view figure

Materials and Methods

Computer parameters

The system parameters used in the present study for molecular docking were as follows, RAM: 16 GB; Operating system and type: Windows 10, 64 bit, x64-based processor; Processor: Intel(R) Core(TM) i5-10210U.

Retrieval of bioactive compounds from literature and preparation

A total of 91 bioactive compounds from Chrysopogon zizanioides were obtained from literature sources ^9,10. The bioactive compounds were subjected to Lipinski’s filter to screen the compounds that satisfy oral drug-likeliness properties ¹¹. The compounds that satisfied Lipinski’s rule were then retrieved from the PubChem database in SDF format and converted into PDBQT (Protein data bank partial charge and atom type) format using Open Babel GUI software ¹² before docking. The compounds were then energy minimized for 200 iterations to correct and optimize the geometry, which was accomplished using the Hartree-Fock algorithm of Quantum mechanics/Molecular mechanics (QM/MM) force field ^13,14.

Protein preparation

The three-dimensional structure of SARS-CoV-2 M^pro (PDB Id: 6W63) was retrieved from the protein data bank in PDB format. The geometry was optimized using the SwissPDB viewer ¹⁵ and GROMOS_96 force field ¹⁶ to eliminate bad clashes and correct the bond angles. The heteroatoms like water molecules and ligand were removed, polar hydrogens, Gasteiger, and Kollman charges were added using AutoDockTools-1.5.6 and used for molecular docking.

Predicting the ligand-binding site

The ligand-binding site of M^pro was predicted using Meta Pocket 2.0 webserver ¹⁷ to direct the ligands for site-directed docking. Once the amino acids present in the ligand-binding site were identified, the grid box was fixed to enclose the total amino acids present in ligand-binding site and were found to be X center = -20.774; Y center = 16.188; Z center = -31.912 and size X = 70; Y = 82; Z = 84 with a grid spacing of 0.375 Å. The grid box size and dimensions set were according to Pant et al. ¹⁸.

Molecular docking of protein and bioactive compounds using AutoDock Vina

Molecular docking using AutoDock Vina ¹⁹ was performed for 100 Genetic Algorithm runs with exhaustiveness of 4; Population size 150. The responses were studied in terms of binding energy where the compounds with low binding energy have the highest inhibition potential and vice-versa. The software calculates the free binding energy using the equation proposed by Morris et al. ²⁰.

Each compound’s inhibition constant (Ki) value was calculated using the following equation (1).

Where ΔG is the intermolecular free binding energy; R is the gas constant; T is the temperature (298 K). Sequential synergistic docking was performed to study the augmented inhibition upon docking multiple compounds to the same enzyme. The top-ranked free binding energy compound-Mpro complex was sequentially docked with successive bioactive compounds using the same procedure to increase free binding energy, and their potentials were studied. According to C et al. ²¹, the molecular docking procedure was substantiated by re-docking the X77 ligand that is co-crystallized with M^pro using the above-set docking parameters and procedure. The re-docked X77-M^pro complex was then superimposed onto the actual native co-crystallized M^pro. A low root means square deviation (RMSD < 2 Å) value denotes the validity of the docking procedure. The bound interactions between the compounds and M^pro were elucidated using PyMOL 2.3 and Discovery studio 2020 software. The toxicity properties of the top 10 low binding energy compounds were predicted using Swiss ADME and admet SAR webservers ^22,23.

Results and discussion

Docking bioactive compounds against M^pro using AutoDock Vina

The use of natural bioactive compounds has shown promising results by inhibiting the main-protease from the literature ^24–26. All compounds used in the present study fulfilled Lipinski’s rule of five. The molecular docking results (Table 1) in the present study showed significant inhibition (ΔG = -7.5 to -4.0 kcal/mol).

Table 1: Binding energy of bioactive compounds against M^pro

The lower binding energy of protein-ligand complex denotes a greater inhibition property. Of the 91 bioactive compounds from Chrysopogon zizanioides, the top five compounds (Figure 2) with low free binding energy obtained from molecular docking were reported in table 2.

Figure 2: Molecular structure of top ranked bioactive compounds. Click here to view figure

Table 2: Interaction of bioactive compounds with M^pro (PDB Id: 6W63)

*- Control drug used in the present study

The supramolecular bonding interactions of the top five bioactive compounds with M^pro were shown in Figure 3 (a) to (e).

Figure 3: Two-dimensional interaction map of top ranked compounds with Mpro a) β-Sitosterol; b) Campesterol; c) Stigmast-4-en-3-one; d) β-Vatirenene; e) Stigmasterol. Click here to view figure

The phytosterol β-Sitosterol was found to be the best potential inhibitor of M^pro with a free binding energy of -7.5 kcal/mol (Ki = 3.13 µM) that interacted with the amino acids ARG188, ASN142, ASP187, CYS44, GLN189, GLN192, GLU166, GLY143, HIS41, MET49, MET165, THR25, THR26, THR190, and TYR54 in the active site of the enzyme (Figure 4).

Figure 4: Interaction of β-Sitosterol with Mpro: a) three-dimensional surface image; b) three-dimensional cartoon image Click here to view figure

This binding energy was accomplished by forming non-covalent intermolecular bonding like van der Waals, carbon-hydrogen, π-alkyl, alkyl, and π-sigma bonds. The low binding energy is accomplished due to the hydrophobic nature of β-Sitosterol, causing a low entropy (ΔS) change in the enzyme’s surface, causing fluid displacement. The molecular solvent accessibility for the interaction was 3555 Å. Campesterol ranked second with the binding energy of -7.4 kcal/mol (Ki = 3.71 µM) binding with ARG188, ASN142, ASN187, CYS44, GLN189, GLU166, HIS41, HIS164, MET49, MET165, THR25, THR45, and TYR54 amino acids in the active site cleft. The other supramolecular bonding interactions like non-covalent van der Waals, conventional hydrogen, alkyl, and π-alkyl intermolecular interactions. One hydrogen bond was formed between the OH^– donor of Campesterol and oxygen acceptor of ASN142 at a distance of 2.5 Å. The compounds Stigmast-4-en-3-one (ΔG = -7.3 kcal/mol; Ki = 4.39 µM) > β-Vatirenene (ΔG = -6.7 kcal/mol; Ki = 12.1 µM) > Stigmasterol (ΔG = -6.7 kcal/mol; Ki = 12.1 µM) were ranked successively with decreasing inhibition potential. It is important to note that the compounds β-Sitosterol, Campesterol, and Stigmast-4-en-3-one outperformed the atazanavir’s control drug. Atazanavir is one best protease inhibitors against several viral diseases. Atazanavir possessed an energy of -7.0 kcal/mol and Ki = 7.3 µM forming seven conventional hydrogens, π-alkyl, van der Waals, and π-sulphur interactions with protease (Figure 5).

Figure 5: Two-dimensional supramolecular bonding interaction of atazanavir with Mpro. Click here to view figure

Thus, the bioactive compounds that showed greater potential than atazanavir were chosen for sequential synergistic docking. Synergism is defined as the cooperation of multiple agents or substances (here inhibitors) to display enhanced effects compared to the personal effect.

Sequential synergistic docking

Figure 6 shows the synergistic interaction of bioactive compounds with M^pro. The synergistic docking revealed promising results upon the interaction of multiple compounds. The docked β-Sitosterol-M^pro complex was kept constant and used as the enzyme; then, Campesterol and Stigmast-4-en-3-one were sequentially docked into the β-Sitosterol-M^pro complex. Initially, docking Campesterol onto the β-Sitosterol-M^pro complex did not significantly improve the free binding energy. However, upon docking Stigmast-4-en-3-one, the free binding energy reduced drastically from its initial -7.5 kcal/mol to -7.9 kcal/mol, which is a significant sign of inhibition more remarkable than their individual effects. The decrease in binding energy is attributed to the low entropy change as the bioactive compounds are hydrophobic in nature. The formation of hydrophobic supramolecular bonding interactions including van der Waals, hydrogen, alkyl, π-alkyl, π-sigma, and carbon-hydrogen was dominant (Table 3).

Figure 6: Synergistic interaction of bioactive compounds against Mpro: 1) β-Sitosterol; 2) Campesterol; 3) Stigmast-4-en-3-one. Click here to view figure

Table 3: Synergistic interaction of bioactive compounds with M^pro

Moreover, no existing intermolecular bonds were broken or dislocated upon docking multiple compounds; thus, an improvement in binding energy was achieved. It is to be noted that Campesterol and Stigmast-4-en-3-one did not overlap on the β-Sitosterol in the active site; instead, they interacted with allosteric sites of M^pro, causing inhibition. Therefore, the combined effect of bioactive compounds showed augmented inhibition, and it is clear that the compounds have the potentials to be used for further studies to develop novel drug candidates. Muralidharan et al. performed similar synergistic docking of lopinavir, ritonavir, and oseltamivir against SARS-CoV-2 main-protease and obtained free binding energy of -8.3 kcal/mol, which is slightly lower than the present study ²⁷

Validation of docking procedure

The re-docked X77 ligand onto M^pro showed free binding energy of -8.3 kcal/mol (Figure 7). The re-docked protein-ligand complex was precisely bound to the active site and was superimposed onto the PDB co-crystal structure and an RMSD of 0.7 Å was obtained. The re-docked complex also interacted with the same amino acids as the actual co-crystal structure. The superimposition was done successfully with no atomic and stearic clashes between the complexes, which proved that the docking procedure was valid. Joshi et al. also reported a low RMSD (< 2.0 Å) ²⁸.

Figure 7: Superimposed re-docked X77-Mpro (green) structure onto native co-crystal structure (red) from PDB (RMSD = 0.7 Å) Click here to view figure

Thus, the compounds from Chrysopogon zizanioides showed good antiviral potential by inhibiting the proteolytic activity of SARS-CoV-2 M^pro using computational approaches. This was accomplished by forming wide intermolecular supramolecular bonding between viral protease and bioactive compounds. The top compounds were sequentially docked into the protease and showed good binding potential. To validate the molecular docking, re-docking and superimposition were performed to validate the study. Alagu Lakshmi et al. studied the antiviral potential of a few essential compounds β-Sitosterol, Stigmasterol, β-Vetivenene, Vetivone, α-Cadinene, α-Calacorene from Chrysopogon zizanioides against SARS-CoV-2 M^pro (PDB Id: 5R82), human ACE2 recceptor (PDB Id: 1R42), and spike protein (PDB Id: 6VYB), and reported similar inhibition potentials compared to the present work ²⁹. Santra et al. studied the antiviral property of essential bioactive compounds from Chrysopogon zizanioides against the spike glycoprotein of SARS-CoV-2 and human ACE2 receptor and reported binding energies -8.0 to -7.1 kcal/mol, which closely resembles to the results reported in the present work. There has been no report on the simultaneous synergistic effect of Chrysopogon zizanioides against M^{pro 30}. The top-ranked β-Sitosterol, plant-based cholesterol, is a medicinal herb commonly used in Chinese medicine showed promising potential as an antiviral agent against influenza A virus targeting the p38 mitogen-activated protein kinase pathway at 150 to 450 µM concentration ³¹. β-Sitosterol isolated from Isatis indigotica roots inhibited SARS-CoV-1 3C-like protease under in-vitro ³². Tsai et al. reported the promising inhibition potential of β-Sitosterol at low concentrations from methanolic Strobilanthes cusia leaf extracts against Human Coronavirus NL63 ³³. Oladele et al. reviewed the anti-COVID potential of β-Sitosterol, stigmasterol, campesterol, etc., from Nigerian medicinal plants with excellent inhibition potentials ³⁴. These pieces of evidence proved the antiviral potential of bioactive compounds from Chrysopogon zizanioides against COVID-19. Apart from essential oils, the antiviral potentials of various flavonoid polyphenols, alkaloids, saponins, tannins, terpenoids, etc., were studied ^35–39. No compounds possessed toxicity and carcinogenic properties predicted using SwissADME and admetSAR webservers (Table 4), thus are safe for consumption without any side effects. Bioactive compounds from the essential oils of Chrysopogon zizanioides have been reported to be non-genotoxic, non-hepatotoxic, and non-carcinogenic and are safe ^40–44. As the bioactive compounds possessed good binding energies with least toxicity, these compounds can be taken to next level of in-vitro studies.

Table 4: Predicted toxicity of top ranked bioactive compounds from Chrysopogon zizanioides

Summary and Conclusions

Thus, the bioactive compounds from Chrysopogon zizanioides showed promising results towards the SARS-CoV-2 inhibition. Phytosterol β-Sitosterol displayed a free binding energy of -7.5 kcal/mol and Ki = 3.13 µM was found to be the most potent inhibitor against the M^pro of SARS-CoV-2 followed by Campesterol and Stigmast-4-en-3-one. The sequential synergistic inhibition of compounds was more effective than their individual potentials. The compounds were non-toxic and thus are safe for consumption. This study provides a road map for developing plant-based drugs. Future works will focus on in-vitro and further in-vivo clinical trials for developing herbal-based medicines against COVID-19.

Acknowledgement

The authors sincerely thank Vels Institute of Science Technology and Advanced Studies, Chennai for the successful completion of research work.

Conflicts of interest

No conflicts of interest declared by the authors.

Funding sources

No specific grant was received from any funding agency to carry out the research work.

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Abbreviations

COVID-19 – Coronavirus disease 2019; SARS-CoV-2 – Severe acquired respiratory syndrome coronavirus-2; M^pro – Main-protease; ACE2 – Angiotensin-converting enzyme 2; anti-COVID – anti Coronavirus disease; RAM – Random access memory; GB – Giga byte; SDF – Spatial Data File; PDBQT – Protein data bank partial charges and atom types; PDB – Protein data bank; QM/MM – Quantum mechanics/Molecular mechanics; GROMOS_96 – GROningen MOlecular Simulation ; ΔG – Free binding energy; ΔS – Entropy change; kcal/mol – Kilocalories/mole; Ki – Inhibition constant; µM – Micromolar; nM- Nanomolar; RMSD – Root means square deviation