Introduction

The global outbreak of COVID-19 caused by SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) has raised grievous public health crises worldwide [1]. This debouching epidemic disease was first detected in December 2019 in Wuhan, China [2]. The World Health Organization on 30th January 2020 proclaimed the outbreak of COVID-19 as a public health emergency of international concern and declared it a pandemic on 11th March 2020, in the wake of its rapid inter-human transmission and rising cases [3, 4]. Despite numerous attempts by government authorities and commercial organizations to curb the impact of SARS-Cov-2, the statistics of cases continue to increase without permanent cure hitherto.

Possible pathways that can be targeted for the treatment of SARS-CoV-2 include structural proteins responsible for inhibition of viral genome entry in the host cell, key enzymes that are involved in replication and transcription of viral genome, and the proteins that promote virulence activity. The development of antivirals can be aided by structure-based drug designs using SARS-CoV-2 crystalline protein structures available in Protein Data Bank (PDB) [5]. The primary action against SARS-CoV-2 infection is to inhibit the activity of S-glycoprotein, as it restricts the latching of virus to angiotensin converting enzyme 2 (ACE2) receptors of the host cell. There are two cysteine proteases that SARS-CoV-2 encodes, namely, the Mpro and the papain-like PLpro. It is essential to inhibit the activity of these proteases, as they catalyze the proteolysis of polyproteins into nonstructural proteins that are required for viral replication [6].

SARS-CoV-2 Mpro is the most propitious therapeutic target for the development of COVID-19 inhibitors and has been the focus of several studies [7,8,9,10,11]. The structure of Mpro suggests that it is a dimer that comprises six-stranded antiparallel β-barrels, with a substrate-binding site between them, as well as cluster of five helical complexes [12, 13]. A total of three domains, namely, I, II, and III, have been identified from the monomer of Mpro. Domains I and II have 8–101 and 102–184 residues, respectively, while domain III consists of antiparallel globular cluster of five α helices and relates to domain II via a long loop [14]. Additionally, Cys-145 and His-41 catalytic dyad is in the gap between domains I and II at the active site of SARS-CoV-2 Mpro. Other amino acids found at the active site of Mpro are Thr24, Thr26, Phe140, Asn142, Gly143, Cys145, Is163, His164, Glu166, and His 172 [15, 16]. The proteolytic action of SARS-CoV-2 Mpro is crucial for the synthesis of structural and nonstructural proteins, viral genome replication and translation, and packaging of newly generated viruses. Thus, viral replication inside the host cell can be obstructed by constraining the Mpro, which ultimately reduces the viral infection [12, 17].

Despite significant progress made in the management of this infectious disease, the treatment of patients is solely based on the visible symptoms that are diagnosed [1]. On the other hand, finding a viable cure for the highly contagious SARS-CoV-2 is a daunting task due to repeated mutations [18]. Moreover, researchers around the world are struggling to develop possible therapeutic options, including vaccines, as the development of antiviral agents and vaccines poses multiple challenges and requires considerable endeavor and time to validate. In this regard, development of innovative substitute antiviral drugs can be explored by repurposing pre-approved drugs or by using natural components [19]. Currently, multiple vaccines are available for SARS-CoV-2 infection, including Covishield, Covaxin, Pfizer-BioNTech, Johnson & Johnson’s Janssen, Moderna, Sputnik V, Novavax, Sinopharm, Coronavac, Cansinobio, and many more are under clinical trials. Various attempts have been made to manage COVID-19 using antibiotics such as antiprotozoals and azithromycin, anti-inflammatory drugs like hydroxychloroquine, chloroquine, glucocorticoids, and anti-viral drugs including lopinavir, ritonavir, remdesivir, favipiravir, and oseltamivir [17, 20,21,22]. Even though synthetic antiviral agents are efficacious against COVID-19, they cause several side effects and viral complications. The ineffectiveness of these antivirals is due to the latency and recurrence problems seen in immunosuppressed hosts, as it limits their effectual lifespan [23]. Consequently, recent studies support the use of traditional medications and natural sources as a remedy against COVID-19 [3]. This is because such plants are rich in bioactive phytocomponents that offer antiviral and immunomodulatory properties [24, 25]. Furthermore, studies with computational screening have revealed the preclusion of COVID-19 by active phytocomponents such as phenols, flavonoids tannins, alkaloids, saponins, lactones, steroids, lactones, and glycosides, which could help in the development of anti-COVID-19 medications [26].

Rosmarinus officinalis L. (family: Lamiaceae) is one such ethnomedicinal plant, widely grown for its leaves [27]. The scientific communities have taken a keen interest in studying the medicinal properties of this plant, notably in the context of exploring the identification and isolation of bioactive phytocomponents and experimental validation of therapeutical properties [28]. Rosmarinus officinalis L. exhibits many pharmacological activities that have been clinically proven, including antimicrobial, antiviral, antioxidant, antiproliferative, and anti-inflammatory [29,30,31,32]. Several studies have reported the antiviral potential of rosemary extracts against HSV-1 and HIV-1 viruses; besides, various active components isolated from rosemary, such as carnosic acid, carnosol, and rosmanol display anti-HIV properties [33,34,35]. The criterion required to develop antiviral drugs to combat COVID-19 infection are bioavailability, high binding affinity toward target, cost-effectiveness, and minimum side effects [36]. The application of computer-based modules has revolutionized this approach by predicting the possible drug candidates against target receptors [20]. In computer-aided drug design, the selection of target protein is one of the most challenging tasks. In this regard, SARS-CoV-2 Mpro can be used as a target receptor, which is responsible for replication and transcription of viral genome [24]. The present study focuses on virtual screening of some selected bioactive compounds from the ethnomedicinal plant Rosmarinus officinalis L. This is achieved by employing different computational modules such as molecular docking, ADMET (absorption, distribution, metabolism, excretion, and toxicity), molecular dynamic simulation, and drug-likeness properties for anti-COVID-19 activity to inhibit SARS-CoV-2 Mpro.

Computational methodologies

Preparation of ligands

A total of thirteen bioactive polyphenols and terpenoids of Rosmarinus officinalis L. were sorted according to their reported therapeutic properties for this study [37, 38]. Furthermore, specific inhibitors like remdesivir and favipiravir were considered for comparison. The 3D structures of these phytocomponents and standards were retrieved as SDF files from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/). The Biovia Discovery Studio 2020 software was used to optimize ligands in their lower energy conformations employing a CHARMm-based minimizer. The PDB format of ligands was derived using Pymol software, while AutoDock MGL Tools 1.5.7 [39] were utilized to prepare the ligands in PDBQT file format.

Preparation of target receptor

The three-dimensional crystal structure of SARS-CoV-2 Mpro with resolution 2.16 Å (PDB: 6LU7) was obtained from Research Collaboratory for Structural Bioinformatics (RCSB), PDB (https://www.rcsb.org/) (Fig. S1). The Ramachandran plot was used to verify the reliability of the SARS-CoV-2 Mpro structure (Fig. S2). For better understanding, the protease can be split into two chains: A and C. Chain A is a protease, whereas chain C is a peptide like inhibitor N3 (N-[(5-methylisoxazol-3-yl)carbonyl]alanyl-L-valyl-N-1-((1R,2Z)-4-(benzyloxy)-4-oxo-1-{[(3R)-2-oxo pyrrolidin-3-yl]methyl}but-2-enyl)-L-leucinamide) [40]. UCSF Chimera 1.16 was employed to isolate receptor binding domain, fix the missing hydrogen atoms, and assign Kollman charges. For molecular docking, all non-interacting ions and water molecules were eliminated using UCSF Chimera, and the protein was denoted in PDBQT file format.

Molecular docking

Molecular docking was performed to unravel potential bioactive phytochemicals of Rosmarinus officinalis L. against SARS-CoV-2 Mpro. AutoDock Vina [41] was utilized to execute the docking simulation. A grid box of 40 × 40 × 40 Å was set at center, − 10.780, 12.405, and 68.951 Å for x, y, and z, respectively. For each ligand, a maximum of 9 conformers were examined, and the default parameters of AD4 were employed throughout the docking process.

Assessment of pharmacokinetic properties

SWISS ADME (http://www.swissadme.ch/), an online web server, was utilized to study the pharmacokinetic properties such as number of hydrogen bond acceptors (NHBA), number of hydrogen bond donors (NHBD), topological polar surface area (TPSA), and number of rotatable bonds (NRB). All selected ligands were examined as possible drug-like molecules based on Lipinski’s rule of five (ROF), which proposes that NHBA, NHBD, hydrophobicity, and molecular weight should not exceed 10, 5, 5, and 500 kDa, respectively. Similarly, based on Veber’s rule, which states that TPSA and NRB should not exceed 140 Å2 and 10, respectively [42, 43]. Furthermore, ADMET descriptors including blood–brain barrier (BBB) permeability, cytochrome P450 inhibitors (CYP1A2, CYP2C9, CYP2D6, CYP2C19, and CYP3A4), gastrointestinal (GI) absorption, Caco-2 permeability, and Ames toxicity of selected compounds were determined using ADMET SAR database (http://lmmd.ecust.edu.cn/admetsar1/predict).

Molecular dynamics

The promising Mpro complexes with apigenin, betulinic acid, luteolin, carnosol, and rosmarinic acid were further subjected to molecular dynamics, to explore their stabilities, conformational changes, and dynamics. Desmond module of Schrodinger software was utilized to assess molecular dynamics simulation for 50 ns. The docked complexes with potent ligands were solvated with TIP3P molecules in an explicit orthorhombic periodic boundary box of size 10 and were neutralized by adding appropriate number of Na+ and Cl− ions using system builder module. The systems were kept at a constant temperature of 300 K and a constant pressure of 1 bar using NPT ensemble of Nose–Hoover thermostat and barostat. The molecular dynamics simulation was employed for 50 ns using OPLS-3e force field in molecular dynamics module of Desmond. The Desmond simulation interaction analysis module was used to determine root mean square deviation (RMSD) and root mean square fluctuation (RMSF), protein–ligand contacts, and ligand torsion profiles.

Results and discussions

In silico molecular docking and drug-likeness analysis are crucial factors that were considered during the initial stages of drug development. Bioactive molecules of Rosmarinus officinalis L. have already been explored for their viability as antiviral agents [44,45,46,47,48,49,50,51,52,53,54]. In this work, we employed molecular docking and drug-likeness to investigate bioactive polyphenols and terpenoids of Rosmarinus officinalis L., along with controls like remdesivir and favipiravir that have been used to treat COVID-19 patients. The protein–ligand binding interactions were determined using AutoDock Vina [39], and the stable complexes of protein–ligand were then ranked based on their lowest binding energy, which was utilized to interpret the results. The binding interactions of protein and ligand were analyzed using PyMOL visualization tool (the PyMOL Molecular Graphics System, version 1.8, Schrodinger, LLC).

Molecular docking analysis

The virtual screening analysis was conducted to find the plausible binding interaction modes and docking scores for selected phytochemicals of Rosmarinus officinalis L. as well as the controls, namely remdesivir and favipiravir, against SARS-CoV-2 Mpro (Tables 1 and 2). Potential candidates were chosen based on their interactions with amino acid residues as binding sites and dock scores. The catalytic dyad residues, CYS A:145, and HIS A:41, as well as active binding pocket residues including GLU A:166, SER A:144, MET A:165, LEU A:141, GLY A:143, THR A:26, THR A:25, and GLN A:189, showed excellent conventional hydrogen bonding, carbon–hydrogen bonding, pi-alkyl, pi-sulfur, and alkyl interactions with selected compounds. Details of the three-dimensional molecular docking interaction between selected thirteen phytocomponents and SARS-CoV-2 Mpro as a surface and cartoon model are provided in Figures S3, S4, S5, S6, S7, S8, S9, S10, S11, S12, S13, S14, and S15. The results revealed that most of the compounds had a higher binding energy than native ligand N3 (− 6.5 kcal/mol) and favipiravir (− 5.0 kcal/mol), while some of them showed binding energy comparable to that of remdesivir (− 8.0 kcal/mol). Diosmin exhibited highest binding energy of − 9.3 kcal/mol, followed by apigenin and betulinic acid with binding energies of − 7.8 kcal/mol. Diosmin was stabilized by conventional and carbon–hydrogen bonding with residues, HIS A:163, MET A:165, SER A:144, LEU A:141, CYS A:145, GLY A:143, HIS A:41, THR A:26, THR A:25, GLN A:189, GLU A:166, and pi-alkyl interaction with PRO A:168. Besides diosmin, several other selected bioactive compounds showed good binding affinity toward SARS-CoV-2 Mpro (PDB: 6LU7). Apigenin showed hydrogen bonding interactions with ASP A:189, GLU A:166, HIS A:163, SER A:144, LEU A:141, and pi-alkyl and pi-sulfur interactions with residues MET A:49 and CYS A:145, respectively. Whereas betulinic acid formed hydrogen bonds and pi-alkyl interaction with residues CYS A:145, GLU A:166, THR A:24, HIS A:41, and MET A:165 (Fig. 1). Furthermore, luteolin and carnosol were ranked third with a docking score of − 7.6 kcal/mol. Luteolin shared nine conventional carbon–hydrogen bond interactions with THR A:26, THR A:25, CYS A:145, SER A:144, HIS A:163, LEU A:141, GLU A:166, and one pi-alkyl bond with CYS A:145 residue, whereas carnosol had five conventional hydrogen bonds with residues CYS A:145, SER A:144, LEU A:141, HIS A:163, and two alkyl interactions with LEU A:27 and HIS A:41. The other four components of Rosmarinus officinalis L. also docked with a good binding affinity of − 7.2 kcal/mol and showed excellent interactions with amino acid residues GLN A:189, HIS A:163, MET A:49, SER A:144, CYS A:145, GLY A:143, HIS A:41, THR A:26, THR A:25, THR A:24, GLU A:166, ASN A:142, LEU A:141, and MET A:165. Figures 2 and 3 represent 2D and 3D binding interactions between luteolin, carnosol, rosmarinic acid, genkwanin, epirosmanol, ursolic acid, and SARS-CoV-2 Mpro, while binding interactions of the remaining four phytocomponents are shown in the supplementary file (Figs. S3 and S4). It is worth noting that the most accountable non-covalent interactions involved in ligand–protein binding for its druggable actions are H-bond. Consequently, rosmarinic acid may be more potent in inhibiting SARS-CoV-2 Mpro despite its low binding affinity, as it showed efficient H-bond interactions with the key residues HIS A:163, SER A:144, CYS A:145, GLY A:143, HIS A:41, THR A:26, THR A:25, and GLU A:166. Taking this into consideration, diosmin, apigenin, betulinic acid, luteolin, carnosol, and rosmarinic acid were considered for possible anti-COVID-19 activity because of their optimal binding interactions with key amino acid residues.

Table 1 List of sorted bioactive compounds and standard drugs with docking score for SARS-CoV-2 Mpro
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Table 2 Interaction details of 13 screened phytochemicals of Rosamarinus officinalis L. docked against SARS-CoV-2 Mpro (PDB 6LU7)
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Fig. 1
figure 1

2D and 3D docking confirmations of SARS-CoV-2 Mpro (PDB 6LU7) with a diosmin; b apigenin; c betulinic acid illustrating best fit complexes with highest binding energy. The order of inhibitory action against 6LU7 was diosmin > apigenin = betulinic acid

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Fig. 2
figure 2

2D interaction map between Mpro (6LU7) and a luteolin; b carnosol; c rosmarinic acid; d genkwanin; e epirosmanol; f ursolic acid, exhibiting several non-covalent interactions

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Fig. 3
figure 3

Three-dimensional interaction poses displaying the position of a luteolin, b carnosol, c rosmarinic acid, d genkwanin, e ursolic acid, and f epirosmanol within the active site of M.pro (6LU7)

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ADMET and drug-likeness study

ADMET studies and drug-likeness analysis for nine phytochemicals that exhibited good binding affinities toward SARS-CoV-2 Mpro studied using ADMET SAR database (http://lmmd.ecust.edu.cn/admetsar1/predict) and SWISS ADME (http://www.swissadme.ch/) (Tables 3 and S1). The ADMET study plays an important role in drug discovery, as potential drug candidates must have adequate ADMET attributes at the optimum dose of medication. The drug-like molecules can be differentiated from other molecules by evaluating Lipinski’s rule of five (ROF). This rule suggests that the following criteria, H-bond acceptors ≤ 10, H-bond donors ≤ 5, molecular weight ≤ 500 Daltons, and Log P ≤ 5, is to be observed for orally active drugs in humans, and no more than one violation is acceptable (Fig. 4; Table S2) [55]. There was no observed violation in apigenin, luteolin, carnosol, rosmarinic acid, genkwanin, and epirosmanol, while betulinic acid and ursolic acid showed only one violation. Consequently, diosmin is not deliberated as a drug-like molecule due to three violations despite the highest binding affinities. The bioavailability radar provides a quick glance at the pharmacokinetic parameters and bioavailability properties of the best docked compounds and standards (Fig. 5). All sorted compounds except diosmin and rosmarinic acid were found to have TPSA < 130, indicating that all the compounds except these two have greater oral absorption. Another crucial aspect of drug discovery is evaluating the dosing levels for toxic effects in the animal model, and thus the computational approach improves the chances of successful experiments with fewer trials using animal model. The metabolic activities of bioactive phytocomponents were also predicted using cytochrome P450 inhibitors (CYP1A2, CYP2C9, CYP2D6, CYP2C19, and CYP3A4). Betulinic acid, rosmarinic acid, ursolic acid, and diosmin were non-inhibitors of all the cytochrome P450 enzymes, which improves their metabolism as therapeutic agents. The compounds luteolin, carnosol, and epirosmanol were found to be good inhibitors of CYP1A2, while apigenin and genkwanin were effective in inhibiting CYP1A2, CYP2C9, CYP2C19, and CYP3A4 enzymes. Ames toxicity test, which helps in screening potential genotoxic carcinogens, was negative for all the compounds except genkwanin. Skin permeability of compounds was measured in terms of Log Kp value, which was lower than − 2.5 for all compounds, indicating lower skin permeability. To summarize the results observed, apigenin, betulinic acid, luteolin, carnosol, and rosmarinic acid can be considered effective and safer inhibitors against SARS-CoV-2 Mpro.

Table 3 Drug-like properties of potential leads from Rosamarinus officinalis L
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Fig. 4
figure 4

Diosmin, apigenin, betulinic acid, luteolin, carnosol, rosmarinic acid, genkwanin, epirosmanol, and ursolic acid are illustrated along with their hydrogen bond acceptors (HBA), hydrogen bond donors (HBD), LogP, molecular weight (MW), and number of Lipinski’s violation (VIO) using six separate ideograms and various colored connecting ribbons to represent respective values of mentioned parameters in Circos plot (Circos Galaxy Version 0.69.8 + galaxy9; https://usegalaxy.eu/, https://circos.ca/) (Table S2) (Rasche and Hiltemann 55)

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Fig. 5
figure 5

Bioavailability radar of a diosmin; b apigenin; c betulinic acid; d luteolin; e carnosol; f rosmarinic acid; g genkwanin; h epirosmanol; i ursolic acid where SIZE = molecular weight, POLAR = polarity, FLEX = flexibility, LIPO = lipophilicity, INSOLU = insolubility, and INSATU = unsaturation. The specified region (in red) represents adequate area for given bioavailability characteristics

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Molecular dynamic (MD) simulations

Though small molecule docking is a straightforward and a rapid approach to estimate the binding interactions between a given compound and the target protein, however, it generally fails to provide a good estimate of the role of the solvation penalties related to the binding. Consequently, a long range molecular dynamic simulation is a good approach to achieve maneuvering of molecules and atoms in solvent conditions over a given time interval. The five lead docked complexes (Mpro-ligand) and main protease with N3 inhibitor (PDB: 6LU7) were subjected to MD simulations for 50 and 100 ns, respectively. The MD simulations were conducted using Desmond module of Schrodinger software and OPLS-3e force field. Protein–ligand contacts (H-bonds, hydrophobic, ionic, and water bridges), RMSF, and RMSD were evaluated to scrutinize structural stability and conformational and dynamical changes in protein–ligand complex.

RMSD determines the average deviations of group of atoms for a given frame corresponding to their initial reference frame. The most allowable RMSD value is < 3 Å, as lower RMSD values are ascribed to the greater stability of the complex. However, a broad range of fluctuations may suggest that the protein–ligand complex is likely to endure remarkable conformational changes throughout the molecular dynamic simulation. The RMSD graph of the luteolin and betulinic acid in complex with SARS-CoV-2 Mpro is presented in Fig. 6. As observed in trajectory analysis, the protein RMSD value varied between 0.6 and 2.7 Å, while the luteolin and betulinic acid writes on protein RMSD between 0.8 and 3.6 Å indicated ligand’s higher stability in binding site during 50 ns simulations. The RMSD plot of Mpro-luteolin complex showed that the RMSD value of protein initially increases up to 8 ns; thereafter, minor deviations in RMSD were observed, indicating the higher stability of protein throughout the simulation. While Mpro-betulinic complex displayed superior stability as there were very minor fluctuations in RMSD graph. The other ligands, including apigenin, carnosol, and rosmarinic acid, writes on protein RMSD were between 2 and 16 Å, 1.5 and 10.5 Å, and 1.6 and 7.2, respectively, clearly suggesting the lower stability of ligand in the protein binding site. While the protein RMSD lies below 2.7 Å for SARS-CoV-2 Mpro in complexes with apigenin, carnosol, and rosmarinic acid, suggesting higher stability of protein during simulation.

Fig. 6
figure 6

RMSD graph of Mpro with a luteolin and c betulinic acid. The RMSD plot indicates conformational changes of Mpro (left Y-axis) and ligand (right Y-axis) in reference with initial Mpro conformation. RMSF graph of Mpro with b luteolin and d betulinic acid

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The binding efficacy of active phytocomponents was also assessed using RMSF analysis for protein Cα atoms over a given time. The RMSF value represents the flexibility and agility of the chain; a higher RMSF value signifies greater flexibility and less stability, while a lower RMSF suggests higher stability. The RMSF values of Cα atoms of five Mpro-ligand complexes ranged from 0.3 to 4.8 Å, indicating secondary structural changes in the complexes. The RMSF graphs showed lower fluctuations in Mpro-luteolin and Mpro-betulinic acid complexes, denoting greater stability of ligand–protein interactions. Protein–ligand contacts were monitored during simulation, in which the presence of hydrophobic, ionic, H-bond, and water bridge interactions was observed (Fig. 7). Over the duration of the trajectory, the bar charts were normalized; for example, a value of 0.8 indicates that specific contact is maintained for 80% of the time during the simulation. As many protein residues may form multiple interactions of the same subtype with the ligand, values higher than 1.0 are feasible. The protein–ligand interaction histogram showed that HIS41, CYS A:44, THR A:45, SER A:46, GLY A:143, SER A:144, CYS A:145, and GLU A:166 made the most significant H-bond contacts, and THR A:24, THR A:25, THR A:26, HIS A:41, CYS A:44, THR A:45, SER A:46, PHE A:140, LEU A:141, ASN A:142, SER A:144, HIS A:163, GLU A:166, and GLN A:189 made prominent water bridge contacts that provided stability to the Mpro-luteolin complex during simulation. While Mpro-betulinic acid was stabilized using H-bond contacts with THR A:25, THR A:26, and water bridges with THR A:24, THR A:26, HIS A:41, CYS A:44, ASN A:142, GLU A:166, ARG A:188, GLN A:189, THR A:190, and GLN A:192. Such significant interactions increased residence time of ligands at the protein binding site. Thus, luteolin appeared to be the most effective among the five simulated ligands in occupying the binding site cavity for a sustained period, followed by betulinic acid. The binding interactions of the remaining three phytocomponents and ligand N3 are shown in the supplementary file (Figs. S18–S21). Based on the results obtained the two top-ranked compounds were betulinic acid and luteolin. Betulinic acid is a naturally occurring pentacyclic triterpenoid compound found in various plant species, including birch trees (Betula spp.) and a variety of medicinal plants. The chemistry of betulinic acid involves five fused rings with numerous functional groups, including six methyl groups, three hydroxyl groups, and one carboxylic acid group. The five-ring structure includes four cyclohexane rings and one cyclopentane ring, which gives the molecule its characteristic shape and properties. On the other hand, luteolin is a flavonoid, a type of organic compound that occurs naturally in a variety of plants. Luteolin is classified as a polyphenolic compound, and its chemical properties are mainly due to its two main functional groups: the flavone skeleton (a benzene ring fused to a pyrone ring) and four hydroxyl (–OH) groups attached to the benzene ring. These hydroxyl groups make luteolin highly soluble in water and other polar solvents. Although there is no direct resemblance between betulinic acid and luteolin with the controls, namely favipiravir and remdesivir, however, all the compounds contain hydroxyl and carbonyl functional groups, which are important for their biological activity. Also, luteolin and favipiravir are relatively small and polar compounds, which may have an impact on their bioavailability and solubility.

Fig. 7
figure 7

Bar graph of Mpro protein contacts with a luteolin and b betulinic acid showing hydrogen bond, hydrophobic, ionic, and water bridges interactions

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The 3D structural images in MD for betulinic acid and luteolin are shown in Figs. 8 and 9, respectively. While the 3D structural images for apigenin, carnosol, and rosmarinic acid are presented in the supplementary file (Figs. S22–S24). Overall, the findings from the RMSD, RMSF, and protein–ligand contacts suggest that luteolin, betulinic acid, and rosmarinic acid showed appreciable binding. However, luteolin is a more potent inhibitor than betulinic acid and rosmarinic acid because it binds strongly with the protein and for longer duration.

Fig. 8
figure 8

Molecular dynamics 3D structural images of Mpro protein with betulinic at a 1 ns, b 25 ns, and c 50 ns

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Fig. 9
figure 9

Molecular dynamics 3D structural images of Mpro protein with luteolin at a 1 ns, b 25 ns, and c 50 ns

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Conclusion

Computational approach is a prudent, effective, and quick strategy for predicting inhibitory potency of natural phytoconstituents. The present molecular docking study identified diosmin, apigenin, betulinic acid, luteolin, and carnosol with high binding interactions (≥ − 7.8 kcal/mol) and potential inhibition toward SARS-CoV-2 Mpro. Substantial contributions were made by hotspot residues CYS A:145, HIS A:41, GLU A:166, SER A:144, MET A:165, LEU A:141, GLY A:143, THR A:26, THR A:25, and GLN A:189 to the protein–ligand binding, which can be further explored for the drug discovery targeting SARS-CoV-2 Mpro. The ADMET analysis showed prominent pharmacokinetic characteristics such as blood–brain barrier, permeability, cytochrome P450 inhibitors, gastrointestinal absorption, Caco-2 permeability, and Ames toxicity for apigenin, betulinic acid, luteolin, carnosol, and rosmarinic acid. The five lead docked complexes were further subjected to molecular dynamic simulation to evaluate structural stability and conformational changes. The obtained findings suggest that luteolin and betulinic acid may emerge as potential drug candidates for the inhibition of SARS-CoV-2. Though the results are encouraging, there is further need for in vivo and in vitro evaluation. Nevertheless, we believe that the outcome of this work may help in lead optimization to develop therapeutics for SARS-CoV-2 infection.