2.1 Spike protein amino acid sequence retrieval and phylogenetic analysis

Global SARS-CoV-2 S-protein amino acid sequences (n = 202) were retrieved from Uniprot and comprised a set of sequences from bat, pangolin, and human samples involved in previous and recent outbreaks. Multiple sequence alignment (MSA) was performed using Clustal W program embedded in Mega software (Figure S1). Maximum-likelihood method and generalized time-reversible model of amino acid substitution were utilized to perform the phylogenetic analysis in Mega 5 software (Tamura et al., 2011). Bootstrap replications of 1,000 values of the Nearest-Neighbor Interchange procedure were used to estimate the robustness of each node, along with estimating the genetic distance using the maximum likelihood method.

2.2 Preparation of receptor protein

The cryo-electron microscopy structure of SARS-CoV-2 protein (PDB ID: 6VSB) was chosen for initial structure preparation as it is explicitly demonstrated with its ligand interacting sites (Wrapp et al., 2020). First, all the water molecules and heteroatoms were removed in Autodock tool. Then, hydrogen atoms were added to the model based on an explicit all atom model. Finally, Kollmann charges were added for ensuing interaction with the ligands, and the model was energy minimized.

2.3 Ligand preparation

The 3D conformers of Chaga mushroom components beta glycan (CID: 439262), galactomannan (CID 439336), and betulinic acid (CID: 64971) were retrieved in the 3D conformer state from Pubchem (Figure 2) and were prepared for docking in the Ligand Preparation tool of Discovery Studio v20.1.0.19295 (Studio, 2008). In addition, 3D conformer NAG (2-Acetamido-2-deoxy-3-O-beta-D-glucopyranuronosyl-beta-D-glucopyranose; CID: 5288907) that has potent binding affinity for the S-protein of SARS-CoV-2 was also retrieved from Pubchem for comparison purposes and prepared as described above. The root was detected for each ligand, which were eventually saved in.pdbqt files similar to that of receptor protein.

2.4 Molecular docking and post scoring analysis

SARS-CoV-2 cryo-electron microscopic structure (PDB ID: 6VSB) was employed for the docking analysis. Because SARS-CoV-2 is a homotrimer consisting of chain A, B, and C, chain A of the spike protein was used for the docking experiment. The active site of the target protein was predicted using the binding site module of Discovery studio (Studio, 2008) and CastP server (Tian et al., 2018) based on maximum volume (Figure 3). Blind docking with the complete spike protein was performed using Autodock tools to predict the overall receptor–ligand interactions. First, both the receptor spike protein and the ligands were processed in Autodock tools as described above and converted to.pdbqt format. Autodock Vina (Trott & Olson, 2010) docking tool was used to assess the binding ability of chaga mushroom components and viral S-protein. Blind docking was performed to know the probable binding sites on the spike protein. For this, the entire S-protein was selected with a grid box of dimension 75 Å × 96 Å × 159 Å with grid spacing 1 Å. The receptor protein was kept rigid whereas the ligands were flexible. Eight sets of docking poses were performed with exhaustiveness 100 in Autodock Vina; each set produced 11 conformations. Among them, 9 conformations consistently docked at the RBD domain of S-protein, which was again used for the local docking/site-specific docking. For site-specific docking, S-protein of SARS-CoV-2 was selected with a grid box of dimension 58 Å × 55 Å × 65 Å (corresponding to the RBD site) and a grid spacing of 1 Å and exhaustiveness at 100. Six sets of site-specific docking poses were analyzed for each ligand, and the site exhibiting the maximum number of binding conformations was indicated as a potential interacting site, followed by the assessment of hydrophilic and hydrophobic interactions in Pymol software. The interacting sites were further visualized in Discovery Studio Visualizer, and the 2D interaction, nature, types of bonds, and bond lengths were determined. The ligand–protein structures were also analyzed for molecular dynamics simulation mode of the ligand molecules docked with the protein using GROMACS 2018.3. Protein configuration file topology was generated using the GROMOS96 43a1 force field. Ligand topology was predicted through PRODRG2 server and the whole analysis was set for a MD simulation run for 100 ns time interval in GROMACS package, followed by visualization of the structure by PyMOL. Finally, rescoring of the docked conformations was performed in Mol Dock program for better clarity and refinement of ligand–protein interactions.

3.1 Phylogenetic analysis of spike protein

The evolutionary analysis revealed an unprecedented mode of SARS-CoV-2 evolution and transmission across humans, particularly in the recent pandemic. Phylogenetic analysis of the S-protein of SARS-CoV-2 sequences (n = 202) retrieved across the globe from GenBank was represented by a ML tree showing unique pattern of SARS-CoV-2 lineages (Figure S2). The analysis revealed that SARS-CoV-2 specifically originated in bats (outgroup), followed by intermittent transmission through pangolins, and then to humans. The human samples across the globe are grouped into a single major cluster, with several minor subgroups emerging depending on the geographical regions with high similarity indices. Amino acid multiple sequence alignment showed high conservativeness in the amino acid residues across all the samples. However, there was unique conservativeness in the amino acids 680–686 in all the recent COVID-19 samples compared with pre-2019 viral sequences, thereby suggesting its advantageous role in virus evolution and pathogenesis (highlighted in yellow, Figure S2). This revealed that the recent SARS-CoV-2 virus possesses a furin cleavage site near the S1/S2 junction from 680 to 686 bp (NSPRRA), which was absent in the previous virus. Furin cleavage site can cause the excision of the two segments by the furin enzyme which eventually assists in gaining entry into the host through precise fusion and proteolysis (Walls et al., 2020). This was a key difference in the SARS outbreaks from previous and current outbreaks and indicated that the RBD is being selectively evolving. Besides, several residues in the S1-CTD domain that have been reported to be key residues for binding of SARS-CoV-2 to human ACE-2 such as ASN-343, TRP-436, ASN-437, ASN-440, TYR-442, LEU-472, ASN-473, TYR-475, ASN-479, TYR-484, THR-486, and THR-487 (Chen et al., 2020; Shang, Wan, Liu, et al., 2020) were found to be positively selected and conserved in our phylogenetic analysis. Therefore, drugs/small molecules targeting these regions could play key roles in modulating the viral entry into the host cells.

3.2 Molecular docking analysis

Docking analysis revealed that Chaga mushroom components (beta glycan, galactomannan, and betulinic acid) bound to the S1-CTD residues of SARS-CoV-2 (PDB: 6VSB) involved in ACE-2-RBD interaction (Figures 4-7). Computational assessment using Autodock tools for S-protein and the three ligands beta glycan, galactomannan, and betulinic acid revealed that the highest interaction occurred at the RBD involving site 2 (X = 212.255, Y = 194.938, Z = 285.952). The Autodock and Moldock score values among the ligands varied between −7.40 kcal/mol and −8.67 kcal/mol and −24.71 kcal/mol and −32.78 kcal/mol respectively. For beta glycan, the best interacting site comprised the amino acids: ASN-440, SER-373, TRP-436, ASN-343, and ARG-509 for the protein–ligand interaction with minimum energy required for stability (energy minimization, −8.4 kcal). The binding site cavity showed the presence of all the active amino acid residues. For the interaction of 6VSB and galactomannan, the best interacting site was the same site 2 and comprised amino acids ASN-437, SER 373, TRP-436, ASN-343, and ALA 344 that interacted with the receptor S-glycoprotein with high binding energy of −7.4 kcal. For the interaction of 6VSB and betulinic acid, the best interacting site was the same site 2 and comprised amino acids ASN-437, SER-373, TRP-436, PHE-342, ARG-509, and ALA-344 that interacted with the S-protein with a high binding energy of −8.1 kcal. Further analysis showed that the TRP-436, followed by ASN-440, was detected to be the amino acids having maximum affinity to all the three ligands and was shown to be hydrogen bonded strongly with the receptor protein. The control molecule NAG demonstrated a binding energy of ΔG = −8.6 Kcal/mol with the interacting residues, such as THR 430, PHE 515, and GLU 516 that resided near the active site region and formed 4 hydrogen bonds. The RMSD values for all the above ligand–protein conformations ranged between 0.6 and 0.8 nm till 100 ns during MD simulation, which demonstrated high stability of the complexes. Furthermore, the amino acids in the active site residues formed H bonds with the ligand molecule and remain stable throughout the time frame. Therefore, the molecular interaction results in this study revealed that all the ligand interacting sites were located in the S1 domain (highlighted in yellow) and can be thus considered as crucial targets for SARS-CoV-2 spike protein. The interacting sites were primarily hydrophilic in nature and suggested strong interaction with the ligands. A positive correlation was obtained between the interaction of S-protein and galactomannan, betulinic acid, and beta glycan in an ascending order of binding energies (−7.4 > −8.1 > −8.4 kcal/mol). The conformations with maximum negative binding energy are represented in the figures, and different types of interactions and the nature and types of bonds are shown in Table 1.

Through docking, we could gain insight into the interactions of the ligands with the amino acids in the binding pocket of the virus S-protein. Docking results demonstrated significant binding interaction of the S1-RBD of the SARS-CoV-2 with beta glycan, galactomannan, and betulinic acid. More importantly, all the ligand interacting sites specifically fitted within the carboxy-terminal domain of the RBD (Figure 8) and included amino acid residues that have been previously reported to aid the virus in host entry in a conservative manner, such as TRP-436, ASN-437, and ASN-440. Such interaction of Chaga mushroom components with the S-protein of SARS-CoV-2 could modulate its binding and thus can cause inhibition of virus entry into the host cell. Besides, the docking results were at par with the binding affinity of control molecule NAG with S-protein that has been reported to exhibit strong binding affinity for S-protein (Tai et al., 2020). Therefore, Chaga mushroom would also exhibit similar effects by various interactions and modulate the virus–host cell interaction.

The versatile benefits of Chaga mushroom could be attributed to its unique composition through which it can specifically targeting the S1-RBD of SARS-CoV-2 (Ibrahim et al., 2021). Chaga mushroom is a natural compound and indicates no side effects when administered in proper dosages (Eid et al., 2021). It also enhances specific innate immunity system and assists in lowering the proinflammatory cytokines, such as IL-6, IL-10, TNF-α, MCp, and many others. (Van et al., 2009; Mishra et al., 2012; Balandaykin & Zmitrovich, 2015). This attribute will greatly assist in reducing the case fatalities of SARS-CoV-2 due to a phenomenon called “cytokine storm” that results in an uncontrollable amplification and recruitment of inflammatory cytokines and immune cells to combat the infection, eventually resulting in organ damage and death (Pedersen & Ho, 2020). Therefore, Chaga mushroom can be a health-promoting booster in severe SARS-CoV-2 cases that exhibit excessive inflammation. Hence, delineating the role of Chaga mushroom components in SARS-CoV-2 interaction using and laboratory-based studies and clinical trials could reveal promising potential for the development of natural antiviral therapeutics.