Exploration of Potent Antiviral Phytomedicines from Lauraceae Family Plants against SARS-CoV-2 Main Protease

A new Coronaviridae strain, Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), emerged from Wuhan city of China and caused one of the substantial global health calamities in December 2019. Even though several vaccines and drugs have been developed worldwide since COVID-19, a cost-effective drug with the least side effects is still unavailable. Currently, plant-derived compounds are mostly preferred to develop antiviral therapeutics due to its less toxicity, easy access, and cost-effective characteristics. Therefore, in this study, 124 phytochemical compounds from plants of Lauraceae family with medicinal properties were virtually screened against SARS-CoV-2 Mpro. Identification of four phytomolecules, i.e., cassameridine, laetanine, litseferine and cassythicine, with docking scores −9.3, −8.8, −8.6, and −8.6 kcal/mol, respectively, were undertaken by virtual screening, and molecular docking. Furthermore, the molecular dynamic simulation and essential dynamics analysis have contributed in understanding the stability and inhibitory effect of these selected compounds. These phytomolecules can be considered for further in vitro and in vivo experimental study to develop anti-SARS-CoV-2 therapeutics targeting the main protease (Mpro).


Introduction
COVID-19 is a pandemic that has academics and scientists determined to developing new therapeutic tactics and plans to combat this catastrophic pandemic as soon as possible [1]. Currently, there are no specific therapeutic options for the virus, and treatment is based on symptoms and the repurposing of antiviral medicine [2].
In one study, the virtual screening of a library of FDA-approved medications revealed three promising macrocyclic antibiotics, polymyxin B, bafilomycin A, and rifampicin, that show promising and consistent in silico binding to more than one protein target of SARS-CoV-2. In contrast, other tested antimicrobials that belong to different categories, such as antituberculosis drugs or antiprotozoal drugs, did not show comparable affinity against the same targets [3].
targeting it's S-protein [19,20]. Using molecular docking, Chikale and Sinha looked at two proteins, spike receptor-binding protein from SARS-CoV-2 and NSP15 endoribonuclease, to study the phytochemicals from Asparagus racemosus. Isolated molecules such as asparagine-C, asparagine-D, and asparagine-F were vulnerable to both proteins [21]. In disease propagation, the chief protease enzyme of SARS-CoV-2 (M pro ) figures prominently by machining polypeptide, which is indispensable for viral replication and transcription. In Withania somnifera (Ashwagandha) four important molecules viz. Withanoside II, Withanoside IV, Withanoside V, Sitoindoside IX, and Somniferine, where Withanoside V and Somniferine turned out to have a strong binding affinity towards the protein active site with strong hydrogen bonds that inhibit the M pro of SARS-CoV-2, indicating Aswagandha is a powerful antiviral agent [22,23]. In Tinospora cordifolia (Giloy) a compound named Berberine which is one of the main constituent of Giloy, showed as the best docked molecule which can also regulate the protease enzyme M pro or 3CL pro acting as an inhibitor with better stability towards CoV2 protein [18], similarly in tulsi (Ocimum sanctum) three compound namely Vicenin, Isorientin 4 -O-glucoside-2"-O-p-hydroxybenzoate and Ursolic acid act against M pro of SARS-CoV-2 [24].
Likewise, Litsea being highly medicinal, showing potent biological activities against human diseases, the Litsea essential oil possessing incredible structural diversity is considered an excellent source of exploring diverse antiviral agents. Litsea verticillate was the first anti-HIV plant due to the presence of three compounds litseaverticillols L/M and Litseasesquibutenolide [25]. Litsea japonica is also effective against the Hepatitis E virus [26].
In addition to the well-known hepatoprotective silybin and other flavonoids and phenolic compounds, bioactive substances also include the antihypertensive alkaloid reserpine, potential anticancer drugs like paclitaxel, vincristine and vinblastine alkaloids, and a more significant cluster of glucosinolate glycosides that naturally occur in many pungent plants like mustard, cabbage, broccoli, rocket, and horseradish [27].
It has been reported that honey bee products containing potentially active chemical mixes have special features that may assist to protect, combat, and reduce symptoms of COVID-19 infection [28].
Shaldam et. al., suggested that the most effective substances on COVID-19 active sites included P-coumaric acid, ellagic acid, kaempferol, and quercetin (RdRb and M pro ). These bioactive substances were also discovered to have potential antiviral activity against the human rhinovirus, which causes the common cold and is an RNA virus similar to SARS-CoV-2 [29].
So far, viral diseases have become a cardinal consternation for human well-being worldwide, and till now, only a few numbers of medications are available and effective against the number of viral strains.
Lauraceae, a family of medicinal plants with antiviral potential, has encouraged researchers to find a novel antiviral lead molecule. Keeping this view, the objective of our study is to explore the possibility of phytomolecules from Lauraceae family of plants to combat the Novel CORONA virus and provide a new source of cure to humankind.

Structure-Based Virtual Screening and Re-Docking Simulation
The MTiOpen Screen web server was utilised for structure-based virtual screening against SARS-CoV-2 M pro to uncover potential inhibitors from the selected phytochemical compounds [33]. The receptor molecule was prepared before virtual screening by adding hydrogen atoms and by removing co-crystallized native ligand, heteroatoms, and solvent molecules using the Dock prep tool in USCF Chimera under the default parameters [34]. The native ligand binding residues (His 41 , Phe 140 , Cys 145 , Glu 166 , and Gln 189 ) were provided to MtiOpen Screen server for calculation of grid for virtual screening. The highest four compounds were chosen for redocking, and intermolecular analysis with SARS-CoV-2 M pro compared to reference ligand GC376 based on the high intensity of binding energy values obtained after the screening [35].
Re-docking studies were performed to determine how the inhibitors were bound to their target protein. The GC376, a dipeptide protease, was taken as the reference ligand in this study, showing inhibition against SARS-CoV-2 M pro [35]. The binding pocket residues of SARS-CoV-2 M pro with the reference ligand GC376 were selected to check the binding behaviour of compounds chosen with the target protein [35]. In Dock prep Chimaera, the polar hydrogen atoms and charges were added after the selected proteins, and other ligands were synthesised under the default option. By moving and changing the grid size around center co-ordinates (−13.539 × 18.826 × 63.171) at the binding site of SARS-CoV-2 M pro [35], re-docking tests were carried out using AutoDock Vina under the default parameter [36]. Following redocking, the most advantageous ligand orientation for each molecule was picked for additional examination. Using Chimera's energy reduction programme under default settings, all docked complexes had reduced energy consumption. Additionally, molecular 2D and 3D interaction images were produced using the ligandreceptor interaction module of the free academic Maestro (Schrödinger Release 2020-2: Maestro, Schrödinger, and Maestro).

Molecular Dynamics Simulation
Using the free Maestro-Desmond Interoperability, the selected target-ligand docked complexes were utilised to a 100 ns molecular dynamics (MD) simulation to examine stability and intermolecular interactions [37,38]. Using the protein preparation wizard of the Desmond-maestro interface, all protein-ligand contacts were preprocessed and improved. The system was configured for each complex using the TIP4P solvent model, orthorhombic box shape, and buffer box size calculation method. Salt and Na+ were also added to the mixture to inimized it. They were also eliminated from placements within 20. The Desmond minimization software was used to reduce the system model after the system was set up, with a maximum iteration limit of 5000 and a convergence criterion of 1.0 kcal/mol. The 100 ns MD simulation experiment was permitted to be run on the inimized system at the default settings. The OPLS-2005 force-field was used for md simulation of all the complexes.

Essential Dynamics and Dynamic Cross-Correlation Matrix (DCCM) Profiling
Analysis of correlated fluctuations for protein was done by application of Essential dynamics to disclose the motions that are of utmost requirement in the protein function. To collect the PCA (principal component analysis) on the respective MS simulation trajectory using Bio3d package, essential dynamics analysis was necessary to perform [29]. Furthermore, the correlation coefficient was also computed to review at which degree during MD simulation, residual displacements in docked protein were correlated by dynamic cross-correlation analysis in the Bio3d package [39]. To reduce the RMS (root mean square) differences between the equivalent residues of the structure, essential dynamics and dynamic cross-correlation matrix analysis was applied to all of the C-alpha atoms in the 5000 frames extracted from the 100 ns MD simulation trajectory and then superimposed to the initial pose. All the estimations for each trajectory of the respective complex were performed in the R program environment [40] with the Bio3d package.

Structure-Based Virtual Screening
The structural-based virtual screening (SBVS) technique searches the small molecules from a library to identify compounds most likely to bind to a receptor protein [41]. After the virtual screening experiment, the binding poses were evaluated to find out the best-docked complexes by re-docking protein and selected ligand molecules. In this communication, we used an SBVS technique to predict the binding potential of 124 compounds against SARS-CoV-2 M pro with significant binding energy between −9.3 and −3.9 kcal/mol. The top 4 screened phytomolecules viz. cassameridine, laetanine, litseferine, and cassythicine ( Figures 1 and S1), were selected based on their binding energy. The docked complexes with the best binding poses of selected phytomolecules within the active pocket of SARS-CoV-2 M pro , were selected for protein-ligand complex preparation and intermolecular interaction analysis.
MD simulation, residual displacements in docked protein were correlated by dynamic cross-correlation analysis in the Bio3d package [39]. To reduce the RMS (root mean square) differences between the equivalent residues of the structure, essential dynamics and dynamic cross-correlation matrix analysis was applied to all of the C-alpha atoms in the 5000 frames extracted from the 100 ns MD simulation trajectory and then superimposed to the initial pose. All the estimations for each trajectory of the respective complex were performed in the R program environment [40] with the Bio3d package.

Structure-Based Virtual Screening
The structural-based virtual screening (SBVS) technique searches the small molecules from a library to identify compounds most likely to bind to a receptor protein [41]. After the virtual screening experiment, the binding poses were evaluated to find out the bestdocked complexes by re-docking protein and selected ligand molecules. In this communication, we used an SBVS technique to predict the binding potential of 124 compounds against SARS-CoV-2 M pro with significant binding energy between −9.3 and −3.9 kcal/mol. The top 4 screened phytomolecules viz. cassameridine, laetanine, litseferine, and cassythicine (Figures 1 and S1), were selected based on their binding energy. The docked complexes with the best binding poses of selected phytomolecules within the active pocket of SARS-CoV-2 M pro , were selected for protein-ligand complex preparation and intermolecular interaction analysis.  The binding energy observed for cassameridine, laetanine, litseferine and cassythicine, were −9.3, −8.8, −8.6, and −8.6 kcal/mol (Tables 1 and S1), respectively. However, in a recent study, doxycycline and minocycline antibiotics have been shown as potential inhibitor against SARS-CoV-2 M pro with binding energy of >−7 kcal/mol [42]. In an in silico, the binding energy observed for Withanoside V, a natural compound from Withania somnifera, against SARS-CoV-2 M pro was −8.96 Kcal/mol [22]. The binding energies observed in the above studies are higher than in the present study.

Re-Docking and Intermolecular Interaction Analysis
After molecular docking, molecular interaction analysis is essential to understand the forces and interactions providing strength and stability to the docked complexes [43,44]. Molecular interactions analysis of each protein-ligand complex showed various noncovalent interactions between SARS-CoV-2 M pro and selected drug molecules, viz. cassameridine, laetanine, litseferine, and cassythicine. The reference ligand GC376 residual interaction with SARS-CoV-2 M pro binding pocket were also studied at a 4 Å radius, along with the selected ligands. (Figure 2, Table 2). The SARS-CoV-2 M pro -cassameridine complex exhibited interaction by two hydrogen bonds in the active region with Gly 143 and Glu 166 residues, respectively. The complex also revealed the π-π stacking interaction at residue His 41 . The interaction profiles of SARS-CoV-2 M pro -laetanine reflected a single hydrogen bond formed with residue Glu 166 . Additionally, docked litseferine complex with SARS-CoV-2 M pro displayed moderate hydrogen bonding with His41 and Glu166 residues, along with π-π stacking interaction at res0idue His 41 . In SARS-CoV-2 M pro -cassythicine docked complex two single hydrogen bonds at residues Gly 143 and Glu 166 , were formed while His 41 exhibited π-π stacking ( Figure 2).   Additionally, hydrophobic, polar, positive and negative charge interactions with binding site residues were recorded in the SARS-CoV-2 M pro -phytochemical compound complex ( Figure 2, Table 2). The re-docking and intermolecular interaction analysis of the selected compounds within the active pocket of viral protease suggested good molecular contacts with active residues and substrate binding residues. Notably, the confirmation of the binding pocket and interacting residues of SARS-CoV-2 M pro are similar for the selected phytochemical compound and the reference compound GC376. Hence, computed docking scores and molecular contacts indicate the potential role of screened compounds in inhibiting viral protease, as reported for the GC376 inhibitor ( Figure S2).

Molecular Dynamics Simulation Analysis
Molecular dynamics simulation (MDS) is a computative approach used to discover new drug lines to monitor the stability of molecular docked complexes over time [43,44]. In this study, root mean square deviation (RMSD) and root square mean fluctuation (RMSF) retrieved from corresponding 100 ns simulation trajectories were used to assess the stability of selected complexes. Usually, the structural variations necessary to determine the system's dynamic stability are observed using RMSD and RMSF. To examine the stability of docked ligands at the active pocket of viral protease, intermolecular interactions between the protein and ligands were also estimated from the respective 100 ns simulation trajectories.

RMSD and RMSF Analysis
First, the protein and ligand RMSD concerning the reference frame were examined in docked complexes of candidate drugs with SARS-CoV-2. With the exception of SARS-CoV-2 M pro -Cassythicine, the RMSD for SARS-CoV-2 M pro showed deviations of <2.5 Å until 60 ns. This was followed by the state of equilibrium until the simulation's conclusion (<3 Å). (Figure 3). These findings were also confirmed by the calculated respective RMSF values (<3 Å) which suggested the rigid structure of viral protease during simulation, except major fluctuations were recorded in the N-and C-terminal of the protein in respective complexes ( Figures S4 and S5). These observations suggested that all the docked viral protease has attained the stability within 100 ns interval without significant structural distortions. Additionally, cassameridine and litseferine were docked to the viral protease's active pocket showed fluctuations <5 Å till 80 ns and then followed by state of equilibrium. Whilst laetanine and cassythicine in respective docked complexes were logged for superior state stability and acceptable deviations <7 till end of 100 ns. Furthermore, calculated RMSF values for each ligand showed <2 Å fluctuation during the 100 ns simulation, suggested the considerable stability of docked compound on the active pocket of viral protease. However, viral protease docked with GC376 reference inhibitor showed deviation <3.5 Å, ( Figure S3) and RMSF value (<3 Å) calculation supported this observation. These observations suggests that the selected phytochemical shows considerable dynamic stability with the SARS-CoV-2 M pro .

Protein-Ligand Interaction Profiling
The docked complexes of viral proteins with potential compounds were also considered for protein-ligand interaction profiling in hydrogen bonding, hydrophobic interactions, ionic interactions, and water bridge formation throughout a 100 percent simulation period. Remarkably, all the complexes were logged for significant encounters with the active residues of the viral protease during 100 ns simulation. For instance, in SARS-CoV-2cassameridine, the hydrogen bond formation was exhibited by residue Glu166 for 100% of the simulation time. In contrast, His41 and Met165 residues were noted for hydrophobic interaction with the docked ligands for more than 35% of the total interaction fraction. Additionally, residues Thr26 and Gly143 demonstrated water bridge formation throughout more than 10% of the simulation interval (Figures 4a and 5a). Similar to this, for 20% of the simulation interval, Cys145 in the M pro -Laetanine complex of SARS-CoV-2 demonstrated hydrogen bond formation. Additionally, His41 and Met49 exhibit hydrophobic contacts at 80% and 40% of the total interaction percentage, respectively. Besides, Tyr54, Asp187 and Asn142 contribute to water bridge formation for 30% of 100 ns simulation time (Figures 4b and 5b). In SARS-CoV-2 M pro -Litseferine docked complex, Glu166 and His41 Viruses 2022, 14, 2783 9 of 16 exhibit hydrogen bond and hydrophobic interaction for 70% total interaction fraction in addition to water bridge formation (40% interaction fraction) (Figures 4c and 5c). Additionally, protein-ligand contact analysis of SARS-CoV-2 M pro -Cassythicine complex showed a substantial contribution of Thr190 and Gln192 in hydrogen bond formation for more than 70% of total interaction fraction and Met165 contributes in hydrophobic interaction for 30% of total interaction fraction. Gln189, Glu166 and His164 residues contributes in water bridge formation (Figures 4d and 5d). Interestingly, the protein-ligand mapping of the SARS-CoV-2 with the reference ligand GC376 substantially demonstrates hydrogen bond formation via Gly143, Cys145, Glu166 and Gln189 for more than 70% of total simulation period. Moreover, His41 and His164 contributes for water bridge formation for 80% of total interaction fraction ( Figure S6a,b). All the phytochemical compound exhibits H-bond, hydrophobic bond and water bridge formation that contributes to stabilising the selected compounds within the target protein's active site.

Protein-Ligand Interaction Profiling
The docked complexes of viral proteins with potential compounds were also considered for protein-ligand interaction profiling in hydrogen bonding, hydrophobic interactions, ionic interactions, and water bridge formation throughout a 100 percent simulation period. Remarkably, all the complexes were logged for significant encounters with the active residues of the viral protease during 100 ns simulation. For instance, in SARS-CoV-2-cassameridine, the hydrogen bond formation was exhibited by residue Glu166 for 100% of the simulation time. In contrast, His41 and Met165 residues were noted for hydrophobic interaction with the docked ligands for more than 35% of the total interaction fraction. Additionally, residues Thr26 and Gly143 demonstrated water bridge formation throughout more than 10% of the simulation interval (Figures 4a and 5a). Similar to this, for 20% of the simulation interval, Cys145 in the M pro -Laetanine complex of SARS-CoV-2 demonstrated hydrogen bond formation. Additionally, His41 and Met49 exhibit hydrophobic contacts at 80% and 40% of the total interaction percentage, respectively. Besides, Tyr54, Asp187 and Asn142 contribute to water bridge formation for 30% of 100 ns simulation time (Figures 4b and 5b). In SARS-CoV-2 M pro -Litseferine docked complex, Glu166 and His41 exhibit hydrogen bond and hydrophobic interaction for 70% total interaction fraction in addition to water bridge formation (40% interaction fraction) (Figures 4c and 5c). Additionally, protein-ligand contact analysis of SARS-CoV-2 M pro -Cassythicine complex showed a substantial contribution of Thr190 and Gln192 in hydrogen bond formation for Additionally, the putative inhibitors of SARS-CoV-2 M pro residues interacted inside molecules. Calculations of the SARS-CoV-2 M pro , cassameridine, laetanine, litseferine, and cassythicine at total intervals of 30% of 100 ns simulation demonstrated strong binding of the relevant ligands with active residues. It is intriguing to notice that all of the selected ligands displayed hydrogen bonding and pi-pi interactions, indicating that they would be stable in the viral protein's active area. Based on examination of a 100 ns molecular dynamics simulation, docked complexes can be arranged in order of stability, namely SARS-CoV-2-cassameridine, SARS-CoV-2-litseferine, SARS-CoV-2-laetanine, and SARS-CoV-2-cassythicine. for 80% of total interaction fraction ( Figure S6a,b). All the phytochemical compound exhibits H-bond, hydrophobic bond and water bridge formation that contributes to stabilising the selected compounds within the target protein's active site.   for 80% of total interaction fraction ( Figure S6a,b). All the phytochemical compound exhibits H-bond, hydrophobic bond and water bridge formation that contributes to stabilising the selected compounds within the target protein's active site.

Essential Dynamics and Dynamic Cross-Correlation Matrix (DCCM) Analysis
Essential dynamics, also known as principal component analysis (PCA), was performed on the MD trajectories to collect the key eigenvalues to better understand the dynamics of the protein domains and residual displacements. This statistical technique is based on covariance matrices. Specifically, PCA components were taken from 100 ns for the SARS-CoV-2 M pro docked with cassameridine, (b) laetanine, (c) litseferine, and (d) cassythicine. Figure 6 shows the variance (%) (eigen fraction) as a function of the 20 eigenmodes and the mean square positional fluctuations in the covariance matrix as MD trajectories. With the selected compounds of each SARS-CoV-2 M pro docked system showed a sharp decline in Eigen fraction that matched the early three eigenmodes, indicating a significant degree of conformational mobility brought on by the docked ligand within the active pocket of the viral protease. After the 4th eigen value, however, a subsequent elbow point and no change in the fluctuations of the eigen fraction were found. (Figure 6). These findings suggested that SARS-CoV-2 M pro exhibits significant flexibility when docked with particular compounds during the MD simulation's early stages, which reduced flexibility. The gradual drop in the relative contribution of the eigen modes also suggested that further localised variations in SARS-CoV-2 M pro docked with each molecule be added to achieve the desired stability. Therefore, it was proposed that these changes within each complex were crucial to the stability of the corresponding docked complexes.
Apart from the SARS-CoV-2 M pro -Cassythicine complex, the first three SARS-CoV-2 M pro engine vectors that docked with each compound and were derived from the associated MD trajectory as cluster groups displayed compact and cluster motions for SARS-CoV-2 M pro in the corresponding trajectory ( Figure 6). Additionally, the generated plots showed that throughout the MD simulation, there were variations in the cluster distribution in each conformation. The blue to red colour gradient represents repeated jumps between the several structural positions of the docked viral protease. A corelated fluctuating motion of the viral protease during MD simulation in all of the systems under study, with the exception of SARS-CoV-2 M pro -Cassythicine, depicts the stiffness and stability of the associated docked complexes.
DCC matrix analysis was used to quantify the frequency of associated motions during MD simulation based on the positions of C-alpha atoms to calculate the structural dynamics changes brought about in SARS-CoV-2 M pro as a result of the docked ligands' inhibitory activity. Figure 7 displays motions with high correlation, from light blue to cyan (+1), and motions with low correlation, from light purple to red brick black (−1). Analysis of the residue cross correlation, which suggested substantial correlated motions and dynamic changes, revealed no significant correlated motions and dynamics changes in any of the systems, with the exception of complexes docked with laetanine and cassythicine. The other two complexes, however, revealed variations in the residues involved in molecular interactions with the respective ligand. The calculated results established that Laetanine and Cassythicine significantly changed the conformation of docked viral protease during the MD simulation.
Based on the structural analysis of the MD simulation results for Tyrosinase complexes with specific ligands and molecular docking, i.e., (a) Cassameridine, (b) Laetanine, (c) Litseferine, and (d) Cassythicine, we suggested that screened potential compounds holds the potential to inhibit the activity of viral protease via strong intermolecular interactions for stable docked complex formation as well disturbing the conformation of viral protease active pocket. Viruses 2022, 14, x FOR PEER REVIEW 12 of 16 Apart from the SARS-CoV-2 M pro -Cassythicine complex, the first three SARS-CoV-2 M pro engine vectors that docked with each compound and were derived from the associated MD trajectory as cluster groups displayed compact and cluster motions for SARS-CoV-2 M pro in the corresponding trajectory ( Figure 6). Additionally, the generated plots showed that throughout the MD simulation, there were variations in the cluster distribution in each conformation. The blue to red colour gradient represents repeated jumps between the several structural positions of the docked viral protease. A corelated fluctuating motion of the viral protease during MD simulation in all of the systems under study, with the exception of SARS-CoV-2 M pro -Cassythicine, depicts the stiffness and stability of the associated docked complexes. laetanine (e-h), litseferine (i-l), and cassythicine (m-p). Each direction's logged deviations in the residue location are categorised by the analogous eigenvalue's total percentage of mean square displacements (PCs). Periodic jumps between the structural conformations taken from the 100 ns simulation trajectories are visible in the continuous colour change from blue to white to red. of the residue cross correlation, which suggested substantial correlated motions and dynamic changes, revealed no significant correlated motions and dynamics changes in any of the systems, with the exception of complexes docked with laetanine and cassythicine. The other two complexes, however, revealed variations in the residues involved in molecular interactions with the respective ligand. The calculated results established that Laetanine and Cassythicine significantly changed the conformation of docked viral protease during the MD simulation. Based on the structural analysis of the MD simulation results for Tyrosinase complexes with specific ligands and molecular docking, i.e., (a) Cassameridine, (b) Laetanine, (c) Litseferine, and (d) Cassythicine, we suggested that screened potential compounds holds the potential to inhibit the activity of viral protease via strong intermolecular interactions for stable docked complex formation as well disturbing the conformation of viral protease active pocket.

Conclusions
With the progression of SARS-CoV-2 infection and the lack of a prospective antiviral medicine, plant-based natural products are being investigated as a potential source for antiviral medication development. This study applied molecular docking and simulation approach to identify potential SARS-CoV-2 M pro inhibitory antiviral phytomolecules derived from Lauraceae family plants. Four prominent compounds, i.e., cassameridine, laetanine, litseferine and cassythicine, were identified through virtual screening with acceptable docking scores (>−8.6 kcal/mol) belonging to plants of Laucrace family, respectively. The binding affinity, intermolecular interactions, and dynamic stability of all the respective docked complexes were further evaluated using various computational approaches against the SARS-CoV-2 M pro -GC376 as reference complex. A collective analysis suggested that all four selected phytomolecules posses' significant affinity and stability within the binding pocket of SARS-CoV-2 M pro . Therefore, these phytomolecules can be appraised as potential anti-SARS-CoV-2 compounds and examined through in vitro experiments to assess their efficacy and potency.

Data Availability Statement:
The datasets used and analysed during the current study are available from the corresponding author at reasonable request.