key: cord-0946175-fjpq1ljp
authors: Mondal, Priya; Natesh, Jagadish; Abdul Salam, Abdul Ajees; Thiyagarajan, Saravanamuthu; Meeran, Syed Musthapa
title: Traditional medicinal plants against replication, maturation and transmission targets of SARS-CoV-2: computational investigation
date: 2020-11-05
journal: Journal of biomolecular structure & dynamics
DOI: 10.1080/07391102.2020.1842246
sha: 185160c2ad86c0c243037bdfc989a3d4c8673065
doc_id: 946175
cord_uid: fjpq1ljp

COVID-19 is an infectious pandemic caused by the SARS-CoV-2 virus. The critical components of SARS-CoV-2 are the spike protein (S-protein) and the main protease (M(pro)). M(pro) is required for the maturation of the various polyproteins involved in replication and transcription. S-protein helps the SARS-CoV-2 to enter the host cells through the angiotensin-converting enzyme 2 (ACE2). Since ACE2 is required for the binding of SARS-CoV-2 on the host cells, ACE2 inhibitors and blockers have got wider attention, in addition to S-protein and M(pro) modulators as potential therapeutics for COVID-19. So far, no specific drugs have shown promising therapeutic potential against COVID-19. The current study was undertaken to evaluate the therapeutic potential of traditional medicinal plants against COVID-19. The bioactives from the medicinal plants, along with standard drugs, were screened for their binding against S-protein, M(pro) and ACE2 targets using molecular docking followed by molecular dynamics. Based on the higher binding affinity compared with standard drugs, bioactives were selected and further analyzed for their pharmacological properties such as drug-likeness, ADME/T-test, biological activities using in silico tools. The binding energies of several bioactives analyzed with target proteins were relatively comparable and even better than the standard drugs. Based on Lipinski factors and lower binding energies, seven bioactives were further analyzed for their pharmacological and biological characteristics. The selected bioactives were found to have lower toxicity with a higher GI absorption rate and potent anti-inflammatory and anti-viral activities against targets of COVID-19. Therefore, the bioactives from these medicinal plants can be further developed as phytopharmaceuticals for the effective treatment of COVID-19.

Coronavirus disease is an infectious disease caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) from the Coronaviridae family and declared as a global pandemic by World Health Organization on 11 March 2020. The new strain of SARS-CoV-2 has lesser virulence but more contagious than its predecessors SARS-CoV and MERS-CoV (Vellingiri et al., 2020) . The highly infectious nature of the COVID-19 is due to the molecular evolution that occurred in the genome of SARS-CoV-2 (Andersen et al., 2020) . SARS-CoV-2 is a Betacoronavirus belonging to the family of enveloped positive single-stranded RNA. SARS-CoV-2 comprises four major structural proteins; among them, spike glycoprotein (S-protein) is an essential protein, involved in the receptor-host selectivity and infection to the host. The S-protein contains the S1 and S2 subunits, S1 subunit functions as the receptorbinding domain, and involved in binding with the host receptor. Whereas the S2 subunit is engaged in the fusion of viral membrane with the host cellular membrane (Lan et al., 2020; Shang et al., 2020) . S-protein selectively recognizes human angiotensin-converting enzyme 2 (ACE2) receptor and transmits the virus into the host cell. Intriguingly, the S-protein of SARS-CoV-2 has shown a higher affinity towards the ACE2 receptor compared with SARS-CoV (Lan et al., 2020; Shang et al., 2020) . The stronger association of S-protein with ACE2 might be one of the reasons behind the higher infectious efficiency of SARS-CoV-2. Apart from structural proteins, the Main protease (M pro ) is a non-structural protein and acts as a critical component of the SARS-CoV-2 viral life cycle. M pro is a cysteine protease involved in the proteolytic maturation of various polypeptides into non-structural proteins, which are involved in replication and transcription (Jin et al., 2020) . Thus, the functionalities of M pro , S-protein and ACE2 receptor grasp attention as potential therapeutic targets against COVID-19.

The primary symptoms of COVID-19 include fever, dry cough, fatigue, headache and diarrhea (Lan et al., 2020) . As the SARS-CoV-2 infection progresses, a hyperinflammatory reaction is mediated through exaggerated cytokine response, intense lymphopenia, as well as considerable mononuclear cell infiltration into the various organs (Merad & Martin, 2020) . The mortality owing to COVID-19 is mainly due to the clinical features in the advanced stages like acute respiratory distress syndrome and severe cardiac injury (Bonow et al., 2020) . Currently, there is a lack of specific anti-viral therapeutics and vaccines against COVID-19 (Rodr ıguez-Morales et al., 2020) . Some clinical studies have aimed to explore the available protease inhibitors, anti-HIV, anti-inflammatory and anti-malarial drugs. However, there is no evidence of the prophylactic and therapeutic effect of these drugs to overcome the morbidity and mortality caused by Human civilization has been marred with the occurrence of epidemic and pandemics like SARS-CoV. At the same time, the 'survival of the fittest' taught to develop treatment practices and medicines within the natural bounty. 'Ayurveda' is one of the traditional Indian medicinal practices that has appealed attention as complementary approaches against various diseases, including viral infection (Mukhtar et al., 2008) . Medicinal plant extracts are known to act as antipyretics, anti-inflammatory, expectorant, analgesic, etc. Several Table 1 . Binding energies (BEs; kcal/mol) of selected bioactives from medicinal plants with SARS-CoV-2 M pro , S-protein and human ACE2 and their chemical interactions with the binding site. studies have also shown bioactives from medicinal plants function as potential anti-viral agents by boosting the inherent immune system (Ganjhu et al., 2015; Mukhtar et al., 2008) . Furthermore, the anti-inflammatory properties of medicinal plants can reduce severe respiratory distress syndrome and acute cardiac injury, which are the leading cause of COVID-19 morbidities (Corn elio Favarin et al., 2013; Liperoti et al., 2017) . It is known that more than 25,000 plant-based formulations have been used in traditional Indian medicine (Vellingiri et al., 2020) . Traditional medicines often pioneered the discovery of modern drugs yet underestimated due to the latter's target specificity and translational potential. Unlike modern medicine, a single herb may contain many bioactives that may function alone or in combinations to produce the desired relief. Therefore, in the present study, we investigated the therapeutic prospects of bioactives from the traditional medicinal plants against COVID-19.

Approved drugs for the treatment of HIV (Darunavir, Favipiravir, Nelfinavir, Remdesivir), ACE2 inhibitors (Enalapril, Losartan, Olmesartan) and Dexamethasone were chosen as the standard drugs for docking against SARS-CoV-2 M pro , S-protein and ACE2 receptor proteins (Supporting Information Human ACE2 (PDB ID: 1R42, Resolution: 2.20 Å; Towler et al., 2004) protein molecules were retrieved from protein data bank (PDB: www.rcsb.org). Protein molecules were prepared by removing water molecules and cofactors, adding polar H bonds and charges using ADT (Morris et al., 2009 ).

Molecular docking of standard drugs and bioactives from medicinal plants with receptor molecules was performed using AutoDock Vina (Trott & Olson, 2010) . The catalytic site of SARS-CoV-2 M pro (His41 and Cys145), receptor binding motif of S-protein (Leu455, Phe486, Glu493 and Ser494) and hotspot binding residues of ACE2 receptor (Lys31 and Lys353) were chosen as binding sites for docking analysis (Jin et al., 2020; Lan et al., 2020; Shang et al., 2020; Veeramachaneni et al., 2020; Yan et al., 2020) . Grid box was generated using ADT with dimensions relative to the ligands (XYZ) with a resolution of 1 Å. The prepared ligand and receptor files were submitted to AutoDock Vina (Trott & Olson, 2010) . Each docking calculations were repeated three times using different seeds and retaining the remaining values as default. Final protein-ligand interactive models were chosen based on the binding affinity as well as the molecular contacts. The hydrogen bond (H-bond), hydrophobic contacts were calculated using LigPlotþ (Laskowski & Swindells, 2011) . The binding energy (BE) for each ligand-receptor docked complexes was obtained, and 2D conformations were generated using LigPlotþ. Further, the inhibition constant (Ki) for standard drugs and medicinal plant bioactives with SARS-CoV-2 protein targets was determined using the following equation (Onawole et al., 2018) .

Ki ¼ 10 ðBinding energy=1:366Þ

The drug-likeness properties of the standard drugs and selected medicinal plant bioactives were screened using Lipinski's rule of five (RO5; http://www.scfbio-iitd.res.in/software/drugdesign/lipinski.jsp; Lipinski, 2004) . Additional druglikeness features, including lipophilicity, solubility and the drug-likeness score of the ligands were obtained using OSIRIS Property Explorer (https://www.organic-chemistry.org/ prog/peo/) and the SWISSADME server (http://www.swissadme.ch/; Daina et al., 2017) .

The ADME/T predictions of bioactive ligands from the medicinal plants and standard drugs were analyzed by the application of the ADMETlab server (http://admet.scbdd.com). The achieved categorical and numerical values were converted into qualitative units based on explanations and interpretations provided by the ADMETlab server (Dong et al., 2018) . 

The toxic properties including LD 50 of the ligands from medicinal plants were analyzed using the ProTox-II server (http:// tox.charite.de/protox_II/) and OSIRIS Property Explorer (https:// www.organic-chemistry.org/prog/peo). To predict the toxicity class and LD 50 , the Canonical SMILES of ligands were submitted to the ProTox-II server (Drwal et al., 2014) . The LD 50 values of standard drugs were retrieved from the DrugBank (http:// go.drugbank.com) and Cayman chemical websites (https:// www.caymanchem.com/). Other toxicity parameters of both standard drugs and bioactives from medicinal plants were predicted through OSIRIS Property Explorer.

The biological activity scales for the ligands of medicinal plants and standard drugs were predicted by using the Prediction of Activity Spectra for Substances (PASS) program (Filimonov et al., 2014) . Briefly, the Canonical SMILES of ligands were used in the PASS-Way2Drug server (http://www. pharmaexpert.ru/passonline/) to predict the probability to be active (Pa) and the probability of becoming inactive (Pi). The bioactivity score (BAS) for the selected bioactives from medicinal plants and standard drugs was predicted using Molinspiration web-based tool (http://www.molinspiration. com/cgi-bin/properties). This web-based tool provides BAS against human receptors and protein molecules like GPCRs, ion channels, nuclear receptors, proteases and kinases.

The molecular dynamics (MD) simulations were performed on three proteins, M pro , S-protein and ACE2 receptor proteins. Nelfinavir was selected as a common inhibitor, as it has shown a higher binding affinity with all the three target proteins. In addition to that based on the binding energies of selected bioactives from medicinal plants, withanolide A was taken for M pro , and taraxerol was taken for both S-protein and ACE2 to perform MD. The MD simulations were performed using the AMBER20 package (Case et al., 2020) . The ff14SB forcefields were applied for proteins and ions, respectively. The antechamber program was used to develop forcefield for all inhibitors using the gaff2 force field. The topology and coordinated files for protein and complex were created using the tleap program. For each complex system including protein and the ligand, TIP3P water molecules were placed in a 12 Å cubic box in each direction from the surface of the protein. To neutralize the system, 4 Na þ , 2 Cland 28 Na þ ions were added to M pro , S-protein and ACE2 proteins, respectively. The combined system was submitted to sander for energy minimization in four stages, using 5000 cycles steepest descent algorithm. For heating, the NVT ensemble was employed, and the temperature was gradually increased until it reached 300 K. Langevin dynamics (thermostat) with a collision frequency of 2.0 ps À1 were employed. For the equilibration phase, the NPT ensemble was employed. The SHAKE algorithm was employed to restrict the protein backbone atoms, while inhibitor and solvent molecules allowed free movement. Further, the well-equilibrated complex molecules M pro with nelfinavir, M pro with withanolide A, S-protein with nelfinavir, S-protein with taraxerol, ACE2 with nelfinavir and ACE2 with taraxerol were subjected to the production phase without any restraints for 100 ns MD with a time step of 2 fs. Coordinates and energy parameters were saved every 2 ps during the simulation for downstream analysis. The root means square deviation (RMSD) and hydrogen bond analysis were calculated using the CPPTraj module on the trajectories obtained.

The binding free energy of the protein-inhibitor complexation (DG) was calculated using molecular mechanics generalized Born surface area (MM-GBSA) and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA). These classical methods were used to evaluate the energy difference between the two ends states of the system such as bound and unbound. These methods are also allowed to perform a more accurate analysis of residue wise contribution to the overall binding of the ligand to a receptor. The BE comprises of bonds, angles, dihedral, electrostatic interactions, Van der Waals interactions, polar and nonpolar solvation energies. Of the 100 ns simulation trajectories, the first 10 ns were excluded for MM-GBSA/MM-PBSA analysis to facilitate compete equilibration of the system set up. A total of 900 snapshots from the MD simulations were used to calculate the free energies using MM-GBSA, and MM-PBSA methods.

Molecular docking is a computational approach to predict the binding efficiency, and types of interactions between the ligand and receptors (Kamath et al., 2015 (Kamath et al., , 2016 Salam et al., 2018) . The bioactives from several medicinal plants, which are traditionally known to have various health benefits, were investigated in the present study and compared their BE with the standard drugs. Among the standard drugs, nelfinavir, an anti-retroviral and protease inhibitor, has shown a stronger affinity towards all three targets of SARS-CoV-2 with the BE of À8.3 kcal/mol for M pro , À6.6 kcal/mol for S-protein and À6.4 kcal/mol for ACE2 (Supporting Information Table  S1 ). Many medicinal plant bioactives have also shown a higher binding affinity towards SARS-CoV-2 targets compared to standard drugs. For example, emblicanin A had BE of À9.3 kcal/mol with M pro ; rutin had BE of À8.2 kcal/mol with S-protein and echinacin had BE of À7.8 kcal/mol with ACE2 (Supporting Information Table S2 ). Based on the overall BEs of the standard drugs and medicinal plant bioactives, we have set À8.5 kcal/mol, À7.0 kcal/mol and À6.5 kcal/mol as the threshold BEs for M pro , S-protein and ACE2 receptors, respectively. The threshold BEs were used to select the medicinal plant bioactives having a higher binding affinity towards target proteins. We have chosen the bioactive that had shown higher binding affinity against at least two or more potential targets with the minimum fixed threshold BE for further analysis. Based on these criteria, 15 medicinal plant bioactives, out of sixty screened, were having equal or more binding affinity with more than two targets of SARS-CoV-2, as highlighted in Supporting Information Table S2 .

Docking results of the selected medicinal plant bioactives with M pro illustrate that these bioactives have interactions at the catalytic site of proteases, i.e. His41 and Cys145 similar to the standard drugs (Supporting Information Fig. S1-S2 ). There are 20 amino acids of M pro that frequently make H-bonds with the medicinal plant bioactives, and their frequencies of interactions are shown in Supporting Information Fig. S3A . Similarly, 25 amino acids of M pro often make hydrophobic interactions, and their frequencies are shown in Supporting Information Fig. S3B . Similar to standard drugs, bioactives also had a higher binding affinity, and their interactions at the catalytic dyad suggest that the chosen bioactives may also inhibit the activity of M pro and thereby interfere in the process of viral replication as well as transcription. Among the various selected bioactives, pedunculagin (-8.9 kcal/mol) and echinacin (-8.9 kcal/mol) has shown the highest BE with M pro . Pedunculagin forms H-bond with Thr26, His41, Ser46, Cys145, His163 as well as it had various non-bonded interactions near the binding pocket of M pro . Similarly, echinacin forms H-bonds with Thr24, Phe140, His164, Glu166, Arg188, Thr190 and Gln192 in addition, to several non-bonded interactions at the binding pocket of M pro (Table 1 ). The interactions of the bioactives at the binding pockets may likely to inhibit the activity of M pro . In addition, Figure 1 (A) shows the common amino acids of M pro interacting with the standard drug nelfinavir, and bioactive withanolide A as well as taraxerol.

Recently, Jin et al. (2020) solved the structure of M pro from SARS-CoV-2 (PDB ID: 6LU7), and it is complex with an inhibitor known as N3 (PDB ID: 7BQY; Jin et al., 2020) . The N3 inhibitor forms H-bond with amino acids Phe140, Gly143, Cys145, His163, His164, Glu166, Gln189 and Thr190 of M pro and hydrophobic contacts with Thr26, Leu27, His41, Leu141, Asn142, Met165, Pro168, His172, Arg188 and Gln192 (Jin et al., 2020) . Our docking results also mimic the effects of N3, and these interactions identify some more amino acids of M pro , which may facilitate the drug interactions (Supporting Information Fig. S1 and S2) .

During viral transmission, the residues of the receptorbinding motif of S-protein bind with ACE2 receptor hotspots. The receptor-binding motif of S-protein consists of Leu455, Phe486, Gln493 and Ser494 residues, which play a critical role in interacting with the ACE2 receptor (Lan et al., 2020; Yan et al., 2020; Yi et al., 2020; Yuan et al., 2020) . In our current study, the selected bioactives from medicinal plants as well as standard drugs have shown interaction towards the key residues of the S-protein receptor-binding motif, as shown in Supporting Information Fig. S4 and S5 . The frequency of H-bonds and hydrophobic interactions are also summarized in Supporting Information Fig. S6 . Among the bioactive from medicinal plants, withametelin from Dhatura has the highest binding affinity of À8.0 kcal/mol, and it has hydrophobic and non-bonded interactions with Leu452, Phe456, Glu484, Tyr489, Phe490, Leu492, Gln493 and Ser494 of S-protein receptor-binding motif, as shown in Table 1 . These interactions at the receptor-binding motif suggest the possibility of bioactives attenuating the spike protein-ACE2 interaction. The common amino acids of the S-protein receptor-binding motif interacting with the standard drug nelfinavir, and bioactives withanolide A, as well as taraxerol, are compared and the results are highlighted in Figure 1(B) .

Based on the recent structural and MD studies, many key amino acid residues of the ACE2 receptor are identified in interacting with its partner proteins (Lan et al., 2020; Veeramachaneni et al., 2020) . The human ACE2 receptor contains two hotspot residues Lys31 and Lys353. The S-protein recognizes these hotspots, and their interaction is essential for viral infection. The selected bioactives from the medicinal plants have also shown a higher affinity towards hotspot residues of the ACE2 receptor (Table 1 and Supporting Information Fig. S8 ). The interactions of the standard drugs and medicinal plant bioactives were also similar towards hotspot residues of the ACE2 receptor as shown in Supporting Information Fig. S7 and S8. Several chosen bioactives had shown a strong interaction with hotspot Lys353 residues, e.g. echinacin (-7.8 kcal/mol) and withametelin (-7.3 kcal/mol). Apart from hotspot Lys353, taraxerol (-7.2 kcal/mol) and quercetin 3-O-robinobioside (-6.2 kcal/mol) have shown strong interactions with the hotspot Lys31. These interactions at the hotspot residues suggest that chosen bioactives can act as ACE2 receptor blockers and can hinder the binding of S-protein.

Overall, the selected medicinal plant bioactives make H-bonds with more than fifteen amino acids of the ACE2 receptor, as shown in Supporting Information Fig. S9A , which are known to interact with its partner proteins frequently. Among them, His34, Glu35, Glu37, Asp38, Ala386, Ala387 and Arg393 show strong and stable interactions with medicinal plant bioactives (Supporting Information Fig. S9A ). Besides Hbonding, 29 amino acids of the ACE2 receptor involve in hydrophobic interactions. Among them, Asn33, His34, Glu37, Asp38, Tyr41, Lys353, Gln388, Pro389 and Arg393 residues interact with more than three bioactives (Supporting Information Fig. S9B ). The common amino acids of ACE2 receptor interacting with the standard drug nelfinavir, and bioactivities withanolide A, as well as taraxerol, are shown in Figure 1 (C). Thus, our docking results revealed the interaction of potential bioactives with key amino acid residues of the SARS-CoV-2 M pro , S-protein and ACE2 receptor proteins. The bioactives from the selected medicinal plants have shown a stronger affinity with SARS-CoV-2 target proteins. Many of these medicinal plants are well known for their existing antiviral properties, as outlined in Supporting Information Table  S3 . Among Terminalia chebula possess anti-viral activity against herpes simplex virus-2 and has the efficiency to prevent virus attachment and diffusion into the host cells (Kesharwani et al., 2017) .

Similarly, bioactives of porcupine (Barleria prionitis) and licorice (Glycyrrhiza glabra) have shown a higher binding affinity towards S-protein and ACE-2 receptor. Bioactives from medicinal plant B. prionitis, is already known to have potent activity against the Respiratory Syncytial Virus (Chen et al., 1998) . G. glabra has been known to inhibit the viral replication of SARS-CoV and function as an inhibitor of Human Immunodeficiency Virus 1 (HIV-1; Fiore et al., 2008) . Estari et al. have shown an extract of Phyllanthus emblica (Amla) exert anti-HIV activity via inhibition of HIV reverse transcriptase activity (Estari et al., 2012) . In concurrence, we also found that bioactives of amla had a higher binding affinity with the targets of SARS-CoV-2. Overall, our results suggest that the selected medicinal plant bioactives may potentially attenuate the interaction between S-protein and ACE2 receptor as well as inhibit the activity of M pro . Thus, inhibition of M pro and attenuation of S-protein-ACE2 interaction may affect replication, maturation and transmission of SARS-CoV-2. Furthermore, by analyzing the additional properties such as druggability and pharmacological features one can gain knowledge about the druggable option of these bioactives.

Further, we determined inhibition constant (Ki) for the bioactives from the medicinal plants and standard drugs. Ki measures the concentration required to produce half-maximum inhibition and 1-40 mM is considered as a preferred range for a hit compound (Naidoo et al., 2020) . The Ki calculated for the bioactives from medicinal plants for all three target proteins are summarized in Table 2 . In comparison with bioactives, some of the standard drugs such as favipiravir have demonstrated higher Ki values for all three protein targets. Overall, these results suggest that selected medicinal bioactives have a significant binding affinity towards all the protein targets.

The drug-likeness property is an essential parameter to find the ability of a compound to become a drug. Based on the Lipinski's rule of five (RO5), we have analyzed the drug-likeness properties of eight standard drugs (Table 3) and fifteen selected medicinal plant bioactives (Table 4 ). Among them, bioactives from medicinal plants having a maximum of three violations were selected for analyzing other pharmacological features since the selected standard drug Nelfinavir has shown three violations. Seven bioactives (daturaolone, deoxytubulosine, gallotannins taraxerol, tinosporide, withametelin, withanolide A) have qualified the features of drug-likeness with maximum acceptable violations of three, as highlighted in Table 4 .

The lipophilicity (LogP) is an essential factor in drug-likeness properties, which influences the absorption rate of the drug molecule in the body. A higher LogP value represents a lower absorption. The standard drugs and medicinal plant bioactives were further screened for Ghose filter rule, Veber rule, Egan rule and Muegge rule, which are also associated with the drug-likeness properties. Most of the standard drugs have qualified all the drug-likeness features, as shown in Supporting Information Table S4 .1. In medicinal plant bioactives, tinosporide has qualified all the drug-likeness features, as shown in Supporting Information Table S4 .2. All the other chosen medicinal plant bioactives may have good oral bioavailability and optimal cell permeability as they have low molecular weight and less TPSA value similar to standard drugs. Synthetic accessibility (SA) evaluates the feasibility of the chemical synthesis of the compound. The SA value 1 signifies easy to synthesize, whereas 10 means challenging to synthesize (Ertl & Schuffenhauer, 2009 ). The SA value of these selected bioactives was in between 4.05 and 6.60, which implies that they can be chemically synthesized with a moderate effort.

ADME/T analysis is aimed to analyze the absorption, distribution, metabolism, excretion and toxicity of the medicinal plant bioactives in silico. The ADME/T results are calculated for the standard drugs and bioactives are represented in Tables 5 and 6 , respectively. A desirable compound should have excellent human intestinal absorption (HIA) and Caco-2 cell permeability (Radchenko et al., 2016) . Generally, the in vitro drug permeability is analyzed using the Caco-2 cell line. We found that most of the chosen medicinal plant bioactives have shown an optimal Caco-2 permeability with higher HIA-and GI-absorptions. In contrast, some of the standard drugs including remdesivir and nelfinavir have not shown an optimal Caco-2 permeability and high GI-absorption. Irrespective of absorption and probable toxicity, a recent doubleblind study has shown that the administration of remdesivir improved the recovery of patients who were infected with SARS-CoV-2 and lower respiratory tract infections (Beigel et al., 2020) . Advantageously, the selected bioactives not only having comparable BEs but also have better pharmacological distributions over selected standard drugs. Further, we also found that bioactives have the potential to inhibit P-glycoprotein (P-gp) as similar to standard drugs. P-gp is one of the important drug efflux transporters involved in maintaining intracellular drug concentrations (S eve & Dumontet, 2005) .

After intestinal absorption, the bioactive molecules circulate into the different parts of the body through blood. Most of the selected bioactives have shown a lesser affinity to bind with plasma protein (PPB) in contrast to some of the standard drugs and, therefore, they are expected to be freely available at the required tissue or organ. After the circulation, the bioactives are metabolized in the liver by the family of the Cytochrome P450 enzymes (Glue & Clement, 1999) . Here, few drugs and bioactives functioned as the substrate for these enzymes; consequently, the corresponding CYP450 enzyme might metabolize them. 

Toxicity prediction is one major factor in scoring any compound as a drug. The in silico toxicological profile of the medicinal plant bioactives was determined by the ProTox-II server and compared with the standard drugs (Drwal et al., 2014) . The LD 50 values of standard drugs and predictive different organ toxicity are given in Supporting Information Recently, different chemical strategies such as applying the structural alert in molecules can reduce the toxicity. These structural alerts reduce the toxicity by partial replacement or a full replacement, or by reducing the electronic density or by introducing the structural element involved in metabolism (Limban et al., 2018) . The level of toxicity also can be reduced by consuming them as dietary formulations rather than purified compounds or drugs. Therefore, toxicity can be reduced by structural alteration or by chemical strategies. Most of the chosen bioactives did not show any hepatotoxicity, mutagenicity and cytotoxicity.

PASS is used to estimate the probable biological activities of drug-like compounds (Filimonov et al., 2014) . Different biological activities, including anti-viral activities, were assessed by determining the Pa and Pi values. The PASS analysis of standard drugs and bioactives from the medicinal plants is presented in Supporting Information Similarly, the BAS of the selected medicinal plant bioactives were evaluated for various biological ligands and enzymes. It is known that if the BAS of a ligand is < À0.50, then it is inactive on that target receptors, likewise, if BAS is À0.50 to 0.00, ligands are moderately active, and if BAS is >0.00, then it is biologically active against human receptor and proteins like GPCRs, ion channels, nuclear receptor, proteases and kinases (Mishra et al., 2018) . Our results of selected medicinal plant bioactives exhibited biological activities and have a physiological effect. Further, standard drugs were shown to have high activity towards protease inhibition, similarly, the selected medicinal plant bioactives also demonstrated moderate to high activity against protease inhibition, apart from having an activity like enzyme inhibition, and interaction with nuclear and GPCR ligand receptors as shown in Supporting Information Table S7 . The protease inhibitory activity of selected medicinal plant bioactives provides further evidence that these bioactives can bind and potentially modulates the main proteases of SARS-CoV-2.

Unrestrained MD simulations were performed for M pro with nelfinavir, M pro with withanolide A, S-protein with nelfinavir, S-protein with taraxerol, ACE2 with nelfinavir and ACE2 with taraxerol complexes, each for 100 ns. In the M pro -nelfinavir complex, nelfinavir is fairly stable throughout the simulation at the binding pocket (Supporting Information video S1). Similarly, in M pro -withanolide A complex (Supporting Information video S2), withanolide A molecule is stable and remains inside the pocket. From the RMSD plot, it is evident that the backbone of the M pro did not converge in both cases. The RMSD of the M pro -nelfinavir complex is sampling Bioactives in the bold column were chosen for further analysis based on the minimum acceptable Lipinski's violations. higher values after 70 ns, whereas in M pro -withanolide A complex, the RMSD is reaching a maximum of around 40 ns, then is stable at 4 Å minimum and gain the stability ( Figure  2(A) ). Since the stability of ligand binding at its pocket is evident from the simulation videos, the fluctuations in the RMSD are likely due to changes in the regions other than its catalytic site; hence, these do not alter our main discussion points. The S-protein-nelfinavir complex (Supporting Information video S3) showed quite interesting binding patterns during the simulations. The nelfinavir molecule is initially bound at the cavity formed by the amino acids Leu452-Phe456, and Glu484-Gly496 of S-protein, and it retained its pose up to 24 ns. It then dissociates from the binding pocket, floats free among the bulk solvent and binds again to the protein between 40 and 69 ns. It dissociates from the second position too and it finally moves to a third pose at a site diametrically across the molecule from the starting pocket and stays stable from 80 to 100 ns (Figure 3(A) ). The S-protein-taraxerol complex, taraxerol moves away from its initial binding pose taking up a second position after 15 ns, reaches its final position around 30 ns and remains stable during the rest of the simulation (Figure 3(B) ). The recent X-ray crystallographic structural studies of S-protein with monoclonal antibody CR3022 revealed that the CR3022 binds the same site where the nelfinavir and taraxerol move to the final position (third pose; Huo et al., 2020) . The authors postulated that the CR3022 binding to amino acids 369-392, and 427-430 of S-protein, leads to neutralization mechanism by destroying the prefusion spike conformation. Figure 2 (A) plot shows that S-proteinnelfinavir or taraxerol complex structures remain stable with their RMSD mostly staying below 2 Å from their starting respective structures.

In the ACE2-nelfinavir complex (Supporting Information video S5), the nelfinavir is stable in the entire study. In the ACE2-taraxerol complex study (Supporting Information video S6), the taraxerol molecule is flipping from the docked position in early stages around 1.7 ns, then become stable and change its orientation around 84 ns simulation. The RMSD plot of ACE2-nelfinavir and ACE2-taraxerol shows that the overall structure of ACE2-nelfinavir is relatively more stable than the ACE2-taraxerol complex structure during the course of the MD simulation (Figure 2(A) ).

Binding free energies calculated using MM-GBSA and MM-PBSA methods are shown in Table 7 for all the six complex molecules. Initial 10 ns frames or omitted for equilibration, and a total of 900 frames out of the remaining 90 ns simulations were used to obtain the free energy all the systems. In terms of MM-GBSA M pro -nelfinavir showed the highest energy (-51.7 kcal/mol). M pro -withanolide A (-27.9 kcal/mol), ACE2-nelfinavir (-26.3 kcal/mol) and ACE2-taraxerol (-26.2 kcal/mol) showed similar energies. In terms of MM-PBSA, ACE2-taraxerol (-7.3 kcal/mol) showed the highest affinity than other complex molecules. The BE versus time graphs (Figure 2(B-D) ) is drawn for all the complexes. In terms of M pro complexes, both nelfinavir and taraxerol showed similar energies, whereas the ACE2, and S-protein complexes, taraxerol shows better binding energies than the standard drug nelfinavir. It should be noted that taraxerol has only one hydroxyl and seven methyl groups attached to the pentacyclic triterpenoid. The taraxerol possess anti-tumor (Hong et al., 2016) , and anti-inflammatory (Yao et al., 2013) activities, and one of the abundantly available medicinal phytochemicals that can be extracted from more than 50 medicinal plants (Sharma & Zafar, 2015) .

In addition to that, we analyzed the contribution of each residue to the BE using the decomposition tool present in the AMBER: MM-GBSA method. Forty residues of M pro has shown significant interaction with nelfinavir and/or withanolide A (Figure 4(A) ). Among those His41, Met49, Met165 and Gln189 are common residues that showed favorable binding energies with the medicinal phytochemical compounds. Apart from that Thr25, Leu29, Asn142, Gly143, Cys145, His164 and Gln189 of M pro showed good interaction with nelfinavir, and Ser46, Leu50, Asp187, Arg188, Gln189, Asn142 and Cys145 of M pro showed higher binding energies with withanolide A. Recent studies on M pro with bioactive molecules from the tea plant, showed similar interactions (Bhardwaj et al., 2020) . Among those residues, His41 and Cys145 form a catalytic dyad located at the interface between domains I and II, and most of the remaining residues are involved in substrate binding and dimerization (Goyal & Goyal, 2020) . Thr478, Pro479, Cys480, Asn481, Gly482 and Val483 of S-protein show better binding energies with nelfinavir, whereas the taraxerol have significant binding energies at three different positions Ser359-Val363, Cys391-Phe392 and Pro521-Cys525 (Figure 4(B) ). Recent mutagenesis studies identified that Arg439, Lys452, Leu455, Ala475, Glu484, Phe486, Gln493, Gln498, Pro499 and Asn501 of S-protein play a major role in human ACE2 binding (Yi et al., 2020) , and these residues are closely matching with our results. It is also interesting to note that the taraxerol is having reasonable binding energies with three cysteine residues (Cys361, Cys391 and Cys525), which play role in stabilizing the secondary structure of S-protein (Lan et al., 2020) . The ACE2 complexes, His34 and Phe28 of ACE2 are the two major amino acids that have a higher binding affinity with nelfinavir and taraxerol, respectively (Figure 4(C) ). Interestingly His34 of ACE2 is the common residues interacting with both SARS-Cov S-protein and SARS-Cov-2 S-protein (Lan et al., 2020) .

The hydrogen bonds formed during the simulation time in all the six complex molecules were calculated using CPPTRAJ (Roe & Cheatham, 2013) . The amino acids His164, Gly143 (M pro -nelfinavir), His164, Gln189 (M pro -withanolide A), Glu484, Cys480 (S-protein-nelfinavir), Gly381, Glu484 (S-protein-taraxerol), His34, Asp30 (ACE2-nelfinavir) and Gln76, Glu75 (ACE2-taraxerol) are the top two residues interacting with the respective ligands.

The infectious pandemic COVID-19 has emerged as a massive threat to humankind. The main challenges are to control the spread of the disease, developing immunity as the -17.7 (6.4) -12.0 (6.8) -9.3 (8.1) -0.8 (2.0) -32.5 (7.7) -1.4 (3.4) EPB 39.1 (6.0) 24.9 (6.6) 13.0 (9.1) 6.3 (2.4) 46.3 (8.3) 7.9 (2.9) ENPOLAR -39.0 (3.0) -25.0 (3.1) -11.2 (6.8) -15.2 (3.0) -24.8 (3.0) -21.8 (2.8) Total -3.1 (6.4) -0.7 (4.4) -2.4 (4.0) -4.2 (3.0) -2.4 (4.9) -7.3 (3.2) preventive as well as prophylactic, and discovering therapeutics in a feasible time. Nature has always blessed us with plentiful remedies like herbs and medicinal plants for numerous ailments. Therefore, the virtual screening based on molecular docking was executed to identify potential bioactives from medicinal plants as effective inhibitors of M pro , Sprotein and ACE2. We found many bioactives from the medicinal plants have shown either comparable or better binding affinity with targets of SARS-CoV-2 with desirable pharmacological properties over the standard drugs. Further, we also observed that the selected bioactives have better intestinal and GI absorptions and lower toxicity than the standard drugs used. Therefore, these selected bioactives may further be developed as pharmacological inhibitors against SARS-CoV-2 target proteins involved in viral replication, propagation and transmission. Among them, taraxerol from Clerodendrum has shown potential anti-viral activities with desirable pharmacological features (Sharma & Zafar, 2015; Verma & Baranwal, 1983) . Further, withanolide A from Withania somnifera has shown the highest binding affinity with S-protein and ACE-2 receptor. The active constituents of ayurvedic herb W. somnifera have shown promising antiinfluenza properties by targeting neuraminidase of H1N1 influenza (Cai et al., 2015) . AYUSH Ministry of Health, India, has further recommended the use of the aqueous extract of this plant as a preventive and prophylactic for treating COVID-19. Withametelin, from the Datura innoxia plant, has shown a better binding affinity against M pro , S-protein and ACE2. However, the pharmacological analysis revealed its toxicity to health. Instead, daturaolone, another compound from D. innoxia, have shown lower toxicity and higher HIA with potent anti-viral and anti-inflammatory activities.

Overall, the selected medicinal plant bioactives can be further developed and assessed as phytoformulations against SARS-CoV-2 infection.

The proximal origin of SARS-CoV-2

Remdesivir for the treatment of Covid-19 -Preliminary report

Identification of bioactive molecules from tea plant as SARS-CoV-2 main protease inhibitors

Association of coronavirus disease 2019 (COVID-19) with myocardial injury and mortality

Promising anti-influenza properties of active constituent of Withania somnifera Ayurvedic herb in targeting neuraminidase of H1N1 influenza: Computational study

New iridoids from the medicinal plant Barleria prionitis with potent activity against respiratory syncytial virus

Potential effects of medicinal plants and secondary metabolites on acute lung injury

SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules

Admetlab: A platform for systematic ADMET evaluation based on a comprehensively collected ADMET database

ProTox: A web server for the in silico prediction of rodent oral toxicity

Estimation of synthetic accessibility score of drug-like molecules based on molecular complexity and fragment contributions

Human immunodeficiency virus (HIV-1) reverse transcriptase inhibitory activity of phyllanthus emblica plant extract

Prediction of the biological activity spectra of organic compounds using the pass online web resource

Antiviral effects of Glycyrrhiza species

Herbal plants and plant preparations as remedial approach for viral diseases

Cytochrome P450 enzymes and drug metabolism -Basic concepts and methods of assessment

Targeting the dimerization of the main protease of coronaviruses: A potential broad-spectrum therapeutic strategy

Antidiabetic, analgesic and anti-inflammatory activity of aqueous extracts of stem and leaves of Alangium salvifolium and Pavonia zeylanica

Anticancer activity of taraxerol acetate in human glioblastoma cells and a mouse xenograft model via induction of autophagy and apoptotic cell death, cell cycle arrest and inhibition of cell migration

Neutralization of SARS-CoV-2 by destruction of the prefusion spike

Structure of Mpro from SARS-CoV-2 and discovery of its inhibitors

Synthesis of indole-quinoline-oxadiazoles: Their anticancer potential and computational tubulin binding studies

Some new indole-coumarin hybrids; Synthesis, anticancer and Bcl-2 docking studies

Anti-HSV-2 activity of Terminalia chebula Retz extract and its constituents, chebulagic and chebulinic acids

PubChem 2019 update: Improved access to chemical data

Structure of the SARS-CoV-2 spike receptor-binding domain bound to the ACE2 receptor

LigPlotþ: Multiple ligand-protein interaction diagrams for drug discovery

The use of structural alerts to avoid the toxicity of pharmaceuticals

Herbal medications in cardiovascular medicine

Lead-and drug-like compounds: The rule-of-five revolution

MarvinSketch was used to convert chemical structures from 2D to 3D

Pathological inflammation in patients with COVID-19: A key role for monocytes and macrophages

Identification and in silico screening of biologically active secondary metabolites isolated from Trichoderma harzianum

AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility

Antiviral potentials of medicinal plants

Comparative evaluation of antiinflammatory potential of medicinally important plants

Cyanobacterial metabolites as promising drug leads against the Mpro and PLpro of SARS-CoV-2: An in silico analysis

Open Babel: An open chemical toolbox

Structure based virtual screening of the Ebola virus trimeric glycoprotein using consensus scoring

Antiviral prospective of Tinospora cordifolia on HSV-1

Prediction of human intestinal absorption of drug compounds

Going global -Travel and the 2019 novel coronavirus

PTRAJ and CPPTRAJ: Software for processing and analysis of molecular dynamics trajectory data

Evaluation of in vitro antiviral activity of Datura metel Linn. against rabies virus

Homology modeling and docking studies of Bcl-2 and Bcl-xL with small molecule inhibitors: Identification and functional studies

Chemoresistance in non-small cell lung cancer

HIV-inhibitory diterpenoid from Anisomeles indica

Structural basis of receptor recognition by SARS-CoV-2

Occurrence of taraxerol and taraxasterol in medicinal plants

ACE2 X-ray structures reveal a large hinge-bending motion important for inhibitor binding and catalysis

AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading

Structural and simulation analysis of hotspot residues interactions of SARS-CoV 2 with human ACE2 receptor

COVID-19: A promising cure for the global panic

Antiviral activity and the physical properties of the leaf extract of Chenopodium ambrosoides L

Antiviral activity in leaf extracts of different Clerodendrum species

Structural basis for the recognition of SARS-CoV-2 by full-length human ACE2

Taraxerol inhibits LPSinduced inflammatory responses through suppression of TAK1 and Akt activation

Key residues of the receptor binding motif in the spike protein of SARS-CoV-2 that interact with ACE2 and neutralizing antibodies

A highly conserved cryptic epitope in the receptor binding domains of SARS-CoV-2 and SARS-CoV

CSIR-CFTRI for the support and infrastructure facility. We thank Dr. Laskowski (The European Bioinformatics Institute (EMBL-EBI, Cambridgeshire, UK) for his valuable suggestions and providing customized LigPlot program. We thank Professor David A. Case (Rutgers University, NJ, USA) for providing access to the latest AMBER20 software.

No potential conflict of interest was reported by the authors.