key: cord-0763018-j5tz797r
authors: Bharadwaj, Kaushik Kumar; Sarkar, Tanmay; Ghosh, Arabinda; Baishya, Debabrat; Rabha, Bijuli; Panda, Manasa Kumar; Nelson, Bryan Raveen; John, Akbar B.; Sheikh, Hassan I.; Dash, Bisnu Prasad; Edinur, Hisham Atan; Pati, Siddhartha
title: Macrolactin A as a Novel Inhibitory Agent for SARS-CoV-2 M(pro): Bioinformatics Approach
date: 2021-07-01
journal: Appl Biochem Biotechnol
DOI: 10.1007/s12010-021-03608-7
sha: ff3e4a5e57f1581c08a7d4716534b39f7f64023c
doc_id: 763018
cord_uid: j5tz797r

COVID-19 is a disease that puts most of the world on lockdown and the search for therapeutic drugs is still ongoing. Therefore, this study used in silico screening to identify natural bioactive compounds from fruits, herbaceous plants, and marine invertebrates that are able to inhibit protease activity in SARS-CoV-2 (PDB: 6LU7). We have used extensive screening strategies such as drug likeliness, antiviral activity value prediction, molecular docking, ADME, molecular dynamics (MD) simulation, and MM/GBSA. A total of 17 compounds were shortlisted using Lipinski’s rule in which 5 compounds showed significant predicted antiviral activity values. Among these 5, only 2 compounds, Macrolactin A and Stachyflin, showed good binding energy of −9.22 and −8.00 kcal/mol, respectively, within the binding pocket of the M(pro) catalytic residues (HIS 41 and CYS 145). These two compounds were further analyzed to determine their ADME properties. The ADME evaluation of these 2 compounds suggested that they could be effective in developing therapeutic drugs to be used in clinical trials. MD simulations showed that protein–ligand complexes of Macrolactin A and Stachyflin with the target receptor (6LU7) were stable for 100 nanoseconds. The MM/GBSA calculations of M(pro)–Macrolactin A complex indicated higher binding free energy (−42.58 ± 6.35 kcal/mol). Dynamic cross-correlation matrix (DCCM) and principal component analysis (PCA) on the residual movement in the MD trajectories further confirmed the stability of Macrolactin A bound state with 6LU7. In conclusion, this study showed that marine natural compound Macrolactin A could be an effective therapeutic inhibitor against SARS-CoV-2 protease (6LU7). Additional in vitro and in vivo validations are strongly needed to determine the efficacy and therapeutic dose of Macrolactin A in biological systems. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12010-021-03608-7.

The 2003 SARS-CoV outbreak caused 10% fatality [1] , MERS-CoV produced 35% fatality [2] , and now, SARS-CoV2 is responsible for 2.35% fatalities [3] . The

The current research target was to identify potential molecules for SARS-CoV2 treatment that are abundant in the Asia-Pacific zone (i.e., India). A thorough literature survey was conducted to select candidate compounds that are available in the selected region, have proven antimicrobial activity and other pharmacological attributes, and are cost-effective. Natural compounds (n = 30) (Table 1) with antioxidant, antimicrobial, antiviral, and anticancer properties were identified from plants and animals. These compounds were screened using Lipinski's rule against M pro to assess the binding activity following published methods [54] [55] [56] [57] . Among the 30 compounds, 17 possessed suitable drug-likeness properties (Supplementary Table S1 ). These compounds were then selected and proceeded with structure-based antiviral activity prediction using the PASS online server. The software gave a probability active (Pa Score) that ranged from 0 to 1, while previous studies showed that a value of >0.3 can be considered active [58] . A total of 5 compounds were predicted to possess the antiviral activity score (Pa) of 0.6 (60%) (Supplementary Table S2 ). These 5 compounds were further investigated for molecular docking study to identify a possible SARS-CoV2 M pro inhibitor. Two compounds, namely, Macrolactin A (PUBCHEM ID: 6451096) and Stachyflin (PUBCHEM ID: 493326), showed low binding energy (−9.22 to −8.00 kcal/mol) which indicated effectiveness (Supplementary Table S3 ). These top 2 lead inhibitory compounds were further analyzed to assess their ADME properties ( Table 2 ). Both of the compounds showed good physicochemical parameters where almost all the parameters were in suggested ranges. Then, they were further investigated by performing MD simulations which showed Macrolactin A and Stachyflin formed a stable protein-ligand complex. Finally, MM-GBSA analysis was carried out and Macrolactin A was the best inhibitor of the M pro . Various literatures have reported different compounds that possess binding energy ranges from −7.0 to −8.5 kcal/mol, which might be a key to inhibit SARS-CoV2 infection [59, 60] . The overall flow for screening naturally occurring compounds against M pro is depicted in Fig. 1 . Macrolactin A showed binging energy of −9.22 kcal/mol to SARS-CoV-2 M pro (PDB ID: 6LU7) protein and exhibited good pharmacokinetic property and could be a treatment to SARS-CoV-2 infection.

Molecular docking is considered an important computational tool in the drug discovery process. It is performed to select the potential inhibitor compounds and study the different bond formations in the protein-ligand complex at the binding site. M pro belongs to a protease class of proteins and which play an important role in the replication process of many viruses [61] . The catalytic site in SARS-CoV-2 main protease M pro is formed of two amino acids: His41 and Cys145. These two amino acids formed a catalytic dyad [62] which serves in the maturation of the virus. Thus, it was considered an active target site in the protein for the inhibitors.

Docking interactions of these two naturally occurring compounds (Macrolactin A and Stachyflin) with the binding site residues are shown in Figs. 3 and 4 and (Fig. 3) . Macrolactin A showed good binding affinity (−9.22 kcal/mol) with 0.175 μM, forming 3 hydrogen bonds, 9 Van der Waals interactions, hydrophobic interactions, carbon-hydrogen bond, and alkyl interactions (Fig. 3) . Stachyflin (Fig. 2 ) also showed good binding affinity (−8.00 kcal/mol) with 1.37 μM with the Stachyflin formed two hydrogen bonds, 9 Van der Waals interactions, hydrophobic interactions, π donor-hydrogen bonds, and alkyl and π-Alkyl interactions ( Fig. 4 ). This result was in agreement with a previously published report that candidate and lead compounds formed the highest number of hydrogen with GLU 166 [63] . Previous studies also showed that natural compounds can interact with the catalytic site of M pro proteases at HIS41 and CYS145 [57, Previous research indicated that binding energy of −7.0 kcal/mol or less could be effective against SARS-CoV-2 which causes COVID-19 [59] . Studies reported that polyphenols like broussochalcone A, papyriflavonol A, 3′-(3-methylbut-2-enyl)-3′,4′,7-trihydroxyflavane, broussoflavan A, kazinol F, and kazinol J had good interaction with the catalytic residues of His41 and Cys145 of M pro and exhibited good binding affinity −7.6 to −8.2 kcal/mol. These binding affinity values with the SARS-CoV-2 main protease M pro are similar to our findings with Macrolactin A and Stachyflin compound [65] . Previous studies reported that the inhibitor N3 docks in the active binding site of 6LU7 and forms hydrogen bonds with THR190, GLN189, GLU166, HIS 164, PHE 140, and GLY 143 [66] . As mentioned previously, Thailand approved the use of A. paniculate for mild COVID-19 cases. Phytochemicals from A. paniculate also formed hydrophobic interactions and hydrogen bonding interactions with different residues THR24 to GLN192 [15] . The binding energy of the co-crystallized N3 inhibitor was previously reported to be −7.6 kcal/mol [63] . The binding energy of andrographolide (−6.26 kcal/mol) and dihydroxy dimethoxy flavone (−6.23 kcal/mol) from A. paniculate were better compared to hydroxychloroquine (−5.47 kcal/mol) [15] . Amentoflavone, a natural compound synthesized by plants, formed 3 hydrogen bonds and numerous hydrophobic interactions with 6LU7 had binding energy of −10.2 kcal/mol in a previous study [63] . Although all the three compounds showed comparatively good binding energies, the physicochemical properties and stability of the docking complexes needed to be tested.

Evaluations of physicochemical properties via ADME analysis are essential for assessing the efficacy of potential drug candidates and predict the drug-likeness properties. The calculated ADME properties and predicted physicochemical properties of the two-hit compounds are given in Table 2 . All the analyzed parameters like molecular weight, SASA, hydrogen bond donor and acceptor, QPlogPo/w, QPlogS, QPlogkhsa, QplogBB, and number of metabolites of the two top compounds were in the recommended range. The higher percentage (%) of human oral absorption (94.59 and 84.45) of both compounds signifies the reduction of the amount of drug to attain the needed pharmacological effect. The drug-likeness scores of both the compounds were in the recommended range except dipole moment. Macrolactin A was the best compound; however, further derivatization in molecular structure could improve pharmacokinetic descriptors generally. Our percentage (%) of human oral absorption for values (94.59 and 84.45%) were comparable with andrographolide (77.65%) and dihydroxy dimethoxy flavone (93.829%) from A. paniculate and hydroxychloroquine (93.21%) [15] .

The MD simulation (MDS) was performed for M pro -Macrolactin A, and M pro -Stachyflin docking complex with 100 ns simulation time and results were analyzed for root mean square GLU 166 as significant contacts (Fig. 8B) . Thus we may conclude that the compound Macrolactin A is successful in making good interactions with the binding site residues of M pro than Stachyflin and is involved in the stabilizations in the complex. M pro protein interactions with the ligand Macrolactin A and Stachyflin were plotted as stacked bar chart plot ( Fig. 9) , which was mainly categorized into four types: hydrogen bonds, hydrophobic, ionic, and water bridges. In the case of Macrolactin A-M pro protein complex, water bridges play followed by hydrogen bonds and hydrophobic interactions play a very important role in interactions. The amino acids ASN 142, GLU 166, and GLN 189 exhibited hydrogen bond contact with the protein, while in the case of Stachyflin the amino acids LEU50 and GLU166 form hydrogen bond interactions. This indicated that the Macrolactin A-M pro protein complex was stable throughout the simulation time. The conformational strains that might destabilize the complex were studied via ligand torsions dynamics, and detailed information was obtained. The ligand torsions dynamics for the rotatable bonds present in the Macrolactin A compound are plotted in Fig. 10 , while for Stachyflin they were added to Supplementary Figure S1 . The plot showed the simulation trajectory of the ligand from 0.00 to 100 ns and the conformational evolution of rotatable bonds (RB). Rotatable bond torsions were plotted in 2D and the bonds were color-coded. Dial plots showed the conformation of the torsion throughout the simulation. The beginning of the simulation is 

MM-GBSA is a widely used technique to accurately calculate the binding free energy of protein-ligand binding affinities [67] . Utilizing the MD simulation trajectory, the binding free energy along with other contributing energy in form of MM-GBSA was determined for each M pro (PDB ID: 6LU7) complex with the 2 ligands. The results (Table 2) suggested that the maximum contribution to ΔG bind in the stability of the simulated complexes was due to ΔG bind Coulomb, ΔG bind vdW, and ΔG bind Lipo, while ΔG bind Covalent and ΔG bind SolvGB contributed to the instability of the corresponding complexes. The M pro -Macrolactin A docked complexes showed comparatively higher binding free energy (−42kcal/mol), compared to other docking complexes of SARS CoV-2 M pro -Stachyflin (−38.35kcal/mol). The binding energy obtained from MM-GBSA was found to be significantly lower than the binding free energy obtained from molecular docking using Autodock, which signifies stronger proteinligand binding. These results supported the potential of screened compounds in inhibiting M pro and showed the efficiency in binding to the selected protein and the ability to form stable protein-ligand complexes Table 3 . The analysis of the trajectories of the first and the last frame displayed significant differences in the conformation of Macrolactin A bound 6LU7 (Fig. 11) . It was observed that at the beginning of the simulation, the ligand Macrolactin A was outward from the binding site (Fig.  10 , red, 0 ns) whereas, at the final stage of 100 ns simulation, the ligand moved more inside the Fig. 9 Protein-ligand stacked bar chart plot of the interactions formed between ligand and protein residues during 100 ns molecular dynamics simulation of M pro in complex with A Macrolactin A and B Stachyflin. Abscissa represents the amino acid number and ordinate represents interactions fraction binding cavity (Fig. 12, blue, 100 ns) . Apart from the movement of the ligand (around 270°r otation) toward binding cavity and stable fitting, that conformed into a more stabilized helical turn at GLY11-GLU14 and LEU227-TYR237 in 6LU7. These conformational variances were absent before simulation and visibly clear from the last trajectory of 100 ns dynamics. This entire structural evidence (Fig. 10) of ligand movement and conformational changes within the protein was captured from the MMGBSA calculations of the first and the last trajectories. The binding energy in MMGBSA calculations performed rigorous statistical sampling from first to the last trajectory. Therefore, the rotational event of the ligand as displayed in Fig. 11 is reproducible and the pose prediction corroborated the findings of MMGBSA calculations.

DCCM was generated in order to analyze the correlative motion of structural domains to attain a stable conformation of 6LU7 after Macrolactin A binding from MD trajectories (Fig. 12A) . The correlation scores on the central mean line (blue) displayed four distinct blocks having a high correlation of movement of amino acids in 6LU7 (Fig. 12A) . The domain D1 comprised of residues 61-90 conforming into three distinct β-sheets and an extended loop (green, Fig. 12B ), whereas, D2 domain having the highest cross-correlation between residues 95-165 conforming into more flexible extended loops and four β-sheets (red, Fig. 12B ), while D3 and D4 domains conforming into α-helices from 245-265 (cyan) and 270-280 (purple) residues, respectively. Therefore, the dynamics cross-correlation matrix enables the domain conformations into better stability of 6LU7 at Macrolactin A bound state. DCCM analysis also corroborates with the RMSF of C-α backbone of 6LU7 (discussed in the previous section) of Macrolactin A bound state with moderate to fewer fluctuations of respective amino acid residues confirming good stable structure. Similarly, Piao and coworkers (2019) reported the domain conformation and stability of N-PDZ and E-PBM proteins by their correlation function from DCCM analysis [68] .

PCA displayed the contribution of principal dynamic global motion (PC1) and local dynamic behavior (PC2) from the MD trajectories having the second-highest variance of 6LU7 with Macrolactin A bound complex (Fig. 12C) . The eigenvalues (covariance) were plotted in the PCA contour plot indicating the motion magnitude as well as directions of residues in MD trajectories. It was observed that Macrolactin A bound 6LU7 showed large movement toward positive eigenvectors and the majority of the domain movements were contributed by global slow motion (PC1) and conforming into the more stable conformation of 6LU7 depicting the significant binding of Macrolactin A thus corroborating MMGBSA result. Moreover, PCA revealed the final MD trajectories after 100 ns seemed to be highly converged into stable geometry (Fig. 12C) . Therefore, it may be suggested that Macrolactin A binds strongly and giving a stable conformation of C-α backbone of 6LU7.

The natural compound Macrolactin A showed excellent interaction with the active site residues along with the surrounding residues of M pro . The MD simulations and MMGBSA binding energy calculations also showed it as a potential inhibitor candidate with good stability of the docking complex. Besides this, the compound also showed good pharmacokinetic parameters. The identified inhibitors open up the possibilities for designing potential drug molecule which selectively act as an inhibitor against SARS-CoV2 M pro . In the present study, we have found a novel natural inhibitor against SARS-CoV2 main protease by targeting the core pocket of the protein active site. 

Virtual screening of the naturally occurring compounds (n = 30) for drug likeliness properties was carried out according to Lipinski's rule of five [69] . The DruLiTo stand-alone software (http://www.niper.gov.in/pi_dev_tools/DruLiToWeb/DruLiTo_index.html) was implemented for the drug-likeness screening [70] . The compounds were selected from the literature based on cost, sustainable harvest, and year-round availability in India (Table S1 ). The drug-likeness compounds were then predicted for antiviral activity in silico using the PASS online server (http://www.pharmaexpert.ru/passonline/predict.php). The predicted antiviral activity score (Pa) ranges between 0 and 1, where the value 1 is considered the best antiviral activity, and zero stand for no antiviral activity (Table S4 ). The ADME properties of the selected lead compounds were calculated using a QikProp module in Schrodinger suite [71, 72] . Results from ADME properties like SASA, QPlogPo/w, QPlogS, QPlogkhsa, QplogBB, No. of Metabolites, and % human oral absorption were compared with a recommended range of values provided in the manual. The QikProp generated descriptors which were used to perform ADMET predictions or drug-likeness parameter (indicated by # stars). The #stars parameter [73] [74] [75] .

The Ligand was prepared using the LigPrep tool in the Maestro module of Schrodinger [72, 76] . Epik was used and Optimized Potential Liquid Simulations (OPLS3) force field (pH 7.0 ± 2.0, allowing 32 stereoisomers per ligand) were applied for optimization and energy minimization for each ligand compound [77] . The receptor protein crystal structures of the Mpro in [78] . The PDB structure and the protein-ligand complexes were prepared using the Protein Preparation Wizard in the Schrödinger suite [76] . The water molecules in all protein structures were deleted before the missing residues and side chains were corrected using a Prime module [79] . The protein and the protein-ligand complexes were subjected to geometry refinement using OPLS2005 force field.

The crystal structure of M pro (PDB ID: 6LU7) was used for molecular docking studies. All the protein-ligand docking complexes were performed using Autodock 4.2 [80] [81] [82] . The catalytic site of Mpro (His41 and Cys145) was chosen as binding sites for docking analysis [78] .

The protein was kept rigid, while the natural compound structures (ligands) were kept flexible. Polar hydrogen and gasteiger charges were added to the Mpro protein (M pro ) and ligands. AutoDock Tools (v.1.5.6) of the MGL software package was used to prepare PDBQT files of the ligands and proteins. Lamarckian genetic algorithm (LGA) method was used to analyze the protein-ligand docking complexes. The grid box size was set to 22.5 Å, with a grid point spacing of 0.375Å, centered on x = −13.01, y =18.361, and z = 71.031Å. The binding interactions of the docking complexes were analyzed and its 3D and 2D interaction plots were analyzed using Discovery studio visualizer [83] . Only molecular docking complexes with the least binding energies were considered for further study.

The top inhibitory compounds Macrolactin A and Stachyflin were further analyzed by molecular dynamics simulation under a Linux environment using the Desmond modules of the Schrodinger [67, 84] . The SPC (simple point charge) water box solvent model was used and the OPLS2005 force field was applied for the protein-ligand docking complexes. An orthorhombic periodic boundary box (X, Y, and Z-axis) conditions were set up at 10 Å distances to specify the shape and size of the protein-ligand docking complex. Counter ions (14 Na + , and 18 Cl − ions) were added to neutralize charges and then 0.15 M NaCl salt concentrations were added to make the system close to mimic the human physiological condition. The MD simulation was carried out for 100 ns at NPT (isothermal-isobaric ensemble, constant temperature, pressure, and the number of particles) ensemble temperature of 300k and 1.01325 bar of pressure. The Desmond simulation interaction diagram tool of Maestro was used to generate the simulation interaction diagram. Root-mean-square deviation (RMSD), root mean square fluctuation (RMSF), number of H-bonds, total contacts timeline, and protein-ligand interactions were recorded throughout the simulation data and were analyzed to validate our findings in molecular docking.

The binding free energy calculation of the protein-ligand docking complexes was calculated by using the Prime-MM/GBSA and OPLS2005 force field [66, 67, 76] according to the procedures described elsewhere [85] . Prime MM-GBSA method calculates the binding free energy as follows:

where ΔG binding = total binding free energy and G docking complex , G protein , and G ligand are the free energies of the docking complex, protein, and ligand, respectively. The obtained results were presented as mean ± standard deviation (SD).

In order to analyze the domain correlations, a dynamic cross-correlation matrix (DCCM) was generated across all Cα-atoms for Macrolactin A and 6LU7 complex during the MD simulation of 100 ns. PCA was performed to extract the fast and slow motions of the trajectories during 100 ns simulation. A covariance matrix was generated to calculate the PCA for global slow motion and local fast motion of the contributing amino acid residues from each MD trajectory as described elsewhere [68] . The DCCM and PCA were done using trj_essential_dynamics script of Schrodinger [71, 72, 84] .

Virtual screening of 30 natural compounds resulted in the identification of Macrolactin A as a lead compound for further in vitro and in vivo studies, and ultimately as a treatment of COVID-19. The molecular docking study showed that Macrolactin A strongly interacted with the key amino acids (His41 and Cys145) at the active site of SARS-CoV-2 Main protease (M pro ). The docking score of −9.22 kcal/mol was good and 3 hydrogen bonds and several other interactions were formed [23] . ADME and drug-likeness revealed that it possesses favorable physicochemical properties and provides a favorable characteristic according to Lipinski's rule of five and could be used in developing a drug. The molecular dynamic simulation studies showed that the compound is thermodynamically feasible and binds stably with the active site of SARS-CoV-2 Mpro. MD simulations showed that bounds in M pro -Macrolactin A complex were strong and stable throughout 100 ns. MM-GBSA analysis showed ΔGbind of −42.58 kcal/mol. Contacts timeline analysis of Macrolactin A exhibited that HIS 41, ASN 142, TYR 154, GLU 166, and GLN 189 were the crucial interactions. Thus, Macrolactin A could inhibit the protease's catalytic activity and be a potential drug candidate against SARS-CoV2. However, slight modification via derivatization might be required to improve its percentage of human oral. To study the conformational dynamics changes in the structure of SARS-CoV-2 M pro protein due to the inhibitory activity of Macrolactin A, DCCM and PCA were performed. The DCCM and PCA showed better conformational stability in the catalytic site of SARS-CoV-2 main protease M pro during Macrolactin A bound state. Overall, Macrolactin A was the most promising compound to be used against SARS-CoV-2. This compound is produced by soil bacteria Bacillus amylolique faciens and was first isolated in 1989 [66] . This could make producing this compound on an industrial scale very easy and cost-effective due to the ease of culturing bacillus species. It has been previously reported to possess strong antifungal [86] and antibacterial activity even against vancomycin-resistant enterococci and methicillin-resistant Staphylococcus aureus [87] . It is important to note that this is the first study to illustrate the potential of Macrolactin A for SARS-CoV-2 treatment and we hope the current research work will expedite the further biochemical study of the reported molecule. It has also been fully synthesized which make it even more accessible to the world [88] .

Supplementary Information The online version contains supplementary material available at https://doi.org/ 10.1007/s12010-021-03608-7.

Author Contribution Conceptualization, KKB, TS, MKP, and SP; methodology, KKB, AG, BR, and DB; formal analysis, TS, KKB, BR, and AG; investigation SP, TS, KKB, and MKP; writing-original draft preparation, KKB, SP, HIS, BPD, and BRN; writing-review and editing, DB,AG, AJ, and HAE. All authors have read and agreed to the published version of the manuscript.

Data Availability The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Ethics Approval and Consent to Participate Not applicable. The manuscript does not contain data collected from humans or animals.

Competing Interests The authors declare no competing interests.

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