key: cord-0894306-8cisz2dl
authors: Azam, Faizul; Eid, Eltayeb E M; Almutairi, Abdulkarim
title: Targeting SARS-CoV-2 main protease by teicoplanin: a mechanistic insight by docking, MM/GBSA and molecular dynamics simulation
date: 2021-07-18
journal: J Mol Struct
DOI: 10.1016/j.molstruc.2021.131124
sha: 1003849ed527cb6260c97972d398a5eaf66dd4ca
doc_id: 894306
cord_uid: 8cisz2dl

First emerged in late December 2019, the outbreak of novel severe acute respiratory syndrome corona virus-2 (SARS-CoV-2) pandemic has instigated public-health emergency around the globe. Till date there is no specific therapeutic agent for this disease and hence, the world is craving to identify potential antiviral agents against SARS-CoV-2. The main protease (M(Pro)) is considered as an attractive drug target for rational drug design against SARS-CoV-2 as it is known to play a crucial role in the viral replication and transcription. Teicoplanin is a glycopeptide class of antibiotic which is regularly used for treating Gram-positive bacterial infections, has shown potential therapeutic efficacy against SARS-CoV-2 in vitro. Therefore, in this study, a mechanistic insight of intermolecular interactions between teicoplanin and SARS-CoV-2 main protease (M(Pro)) has been scrutinized by molecular docking. Both monomeric and dimeric forms of M(Pro) was used in docking involving blind as well as defined binding site based on the known inhibitor. Binding energies of teicoplanin-M(Pro) complex were estimated by Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) computations from docking and simulated trajectories. The dynamic and thermodynamics constraints of docked drug in complex with target proteins under specific physiological conditions was ascertained by all-atom molecular dynamics simulation of 100 ns trajectory. Root mean square deviation and fluctuation of carbon α chain justified the stability of the bound complex in biological environments. The outcomes of current study are supposed to be fruitful in rational design of antiviral drugs against SARS-CoV-2.

The novel coronavirus disease 2019 , caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is the third outbreak of human corona viruses which has rapidly engulfed the globe resulting in pandemic situation and widespread public concern [1, 2] . Like previously reported severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV), SARS-CoV-2 is one amongst the β-coronavirus family [3] . COVID-19 is highly contagious and easily transmitted through human-to-human contact with clinical manifestation of fever and pulmonary symptoms. Severely ill patients may suffer from severe acute respiratory syndrome, pneumonia, renal failure, and even death [4] . The disease may exacerbate in case of underlying comorbidities like diabetes, hypertension and other cardiovascular complications which often correlate with detrimental outcomes and poor survival [5] . Till date, there is no specific therapeutic regimen for the treatment of this devastating SARS-CoV-2 infection.

Although available medications can only alleviate few symptoms like difficulty in breathing, the world is craving to identify potential antiviral agents or vaccines against SARS-CoV-2 [6] .

However, continuing researches on SARS-CoV-2 have certainly provided an understanding of structural information of the key proteins involved in viral life cycle which has accelerated the structure-based drug design approaches aimed at suitable therapeutic development for COVID-19 [7] . Particularly, main protease (M Pro ), also called as 3C-like protease or 3CL pro , is an important proteolytic enzyme belonging to cysteine protease family and one of the structurally well-characterized proteins of SARS-CoV-2 [8, 9] . Hampering the functional role of M Pro by small molecule or other peptidomimetic inhibitors has attracted much attention because the enzyme is specifically involved in cleaving polyproteins leading to release of a set of functional non-structural proteins, such as nsp4-nsp16 [9, 10] . In addition, targeting M Pro by selected inhibitors seems to be non-toxic in COVID-19 infected patients because no human proteases have been identified having similarity with SARS-CoV-2 specified proteolytic cleavage [7] . Currently, several antivirals, antimalarials, anti-parasitic, and antibacterial agents are in clinical investigations for the treatment of COVID-19 [11] . In particular, teicoplanin (Fig. 1) , a widely available FDA-approved glycopeptide type of antibiotic is known to possess low toxicity profile in humans, is molecule of interest as possible COVID-19 medication. It is routinely used in clinical practice for the treatment of bacterial infections. Interestingly, it has shown antiviral activity against strains of SARS-CoV, MERS-CoV and Ebola viruses [12] .

Very recently, same research group has disclosed that teicoplanin can prevent the cellular entry of SARS-CoV-2 at 1.66 μM concentration [13, 14] .

Computer-aided drug design techniques are routinely employed in drug design and discovery projects owing to several advantages such as rapid development process and reduced cost [15] [16] [17] In particular, molecular docking coupled with molecular dynamics simulation studies are intended to decipher the mechanism of binding interactions at the molecular levels. Rapid mechanistic insight is vital for understanding structure-activity relationship and lead optimization for the design and discovery of potential molecules [18] [19] [20] . In this study, several computational techniques such as molecular docking, Molecular Mechanics-Generalized Born Surface Area (MM-GBSA) and molecular dynamics simulation were exploited to inspect the binding interactions between teicoplanin and SARS-CoV-2 main protease. The study is envisioned to assist in finding potential leads and accelerate drug development process for the treatment of novel coronavirus, COVID-19.

Three-dimensional X-ray crystal structure of monomeric form of SARS-CoV-2 main protease in complex with an inhibitor N-[(5-methylisoxazol-3-yl)carbonyl]alanyl-L-valyl-N~1~-((1R,2Z)-4-(benzyloxy)-4-oxo-1-{[(3R)-2-oxopyrrolidin-3-yl]methyl}but-2-enyl)-lleucinamide (N3; PDB ID: 6LU7) and dimeric M Pro (PDB ID: 6WTM) were retrieved from Protein Data Bank. [9, 21] Initial processing of the protein structures was performed in Biovia Discovery Studio 2020 and PyMOL 1.7.4 for removing the solvent and the co-crystallized molecules. Two-dimensional structure of the teicoplanin was obtained from PubChem database in sdf format (Pubchem ID: 133065662; CAS number: 61036-62-2) and converted to its three-dimensional coordinate by using Open Babel program. [22] Jaguar v10.9 of Schrodinger Suites 2020-3 [23] was used for geometry optimization. The density functional theory (DFT) computation was performed by the hybrid density functional method B3LYP with the 6-311G basis set [24] . The optimized structure of teicoplanin has been presented as An outline of the adopted methodology in this study.

AutoGrid 4.2 was employed to calculate numerous grids around both monomeric and dimeric forms of M Pro for both blind and defined dockings having a grid spacing of 0.375 Å. All the parameters of grid points and grid center have been presented as Table S1 in supplementary information. A distance-dependent function for dielectric constant was applied for the computation of energetic maps. Applying the active site information pertaining to the native co-crystallized ligand, N3, a grid box center for defined docking was established in both monomeric and dimeric forms of M Pro . However, in both proteins, entire macromolecule was considered as the searching site for blind dockings. AutoDock 4.2 was used for docking simulations involving 100 independent runs by Lamarckian genetic algorithm methodology, adjusting default settings for all other parameters. [25] At the end of each docking, ten best poses were individually analyzed for intermolecular interactions using Biovia Discovery Studio Visualizer 2020, and PyMol 1.7.4 programs. [20, 26] and further subjected to MM/GBSA computations in the next step.

MM/GBSA technique was exploited as a post-docking validation protocol. The binding energy computed by Prime MM-GBSA of Schrödinger Suite 2020-3 [27, 28] demonstrates an adequate estimation of binding affinity. The MM-GBSA protocol implemented in Prime combines OPLS molecular mechanics energies, a VSGB solvation model for polar solvation (G SGB ), and a nonpolar solvation expression (G NP ) involving nonpolar solvent-accessible surface area (SASA) and van der Waals interactions. [29] For each docked teicoplanin-main protease complex, Prime MM-GBSA estimated the binding free energy (ΔG bind ) of teicoplanin according to the equation [30] ΔG bind = ΔE MM + ΔG solv + ΔG SA Where, ΔE MM is the difference in energy between the complex structure and the sum of the energies of the protein with and without teicoplanin, ΔG solv is the difference in the GBSA solvation energy of the teicoplanin-protein complex and the sum of the solvation energies for the teicoplanin-bound and unbound protein, and ΔG SA is the difference in the energy of surface area for the teicoplanin-main protease complex and the sum of the surface area energies for the ligand and un-complexed protein.

The best ranked conformation of teicoplanin furnished by each category of docking experiments in complex with SARS-CoV-2 main protease was further examined for assessing their thermodynamic behavior and stability by using MD simulation studies employing Desmond 6.1 program. [31, 32] In total, six individual systems were simulated which also includes both monomeric and dimeric forms of apo M Pro . System setup protocol was used for placing the ligand-protein complex or apo protein into an orthorhombic box having 10Å buffer region between protein atoms and box sides and filled with appropriate number of water molecules (see Table S4 in Supplementary Information). Simple point charge (SPC) model and OPLS3e force field was adopted for the MD computations [33] . The system was neutralized using appropriate numbers of counter ions (Na+ and Cl−) with fixed salt concentration of 0.15M that represents the physiological concentration of monovalent ions.

Isothermal-isobaric (NPT) ensemble was employed with temperature and pressure adjusted to 300 K and 1.01325 bar, respectively. A simulation time of 100 ns was adjusted whereas trajectories were saved at every 100 ps. A cut-off radius of 9.0 Å was used for short-range van der Waals and Coulomb interactions. Nose-Hoover thermostat [34] and Martyna-Tobias-Klein [35] methods were employed for maintaining the system temperature and pressure, respectively. Reference system propagator algorithm (RESPA) integrator was used to integrate the equations of motion, with an inner time step of 2.0 fs for bonded as well as non-bonded interactions within the short-range cut-off [36] . Particle Mesh Ewald method was used for accurate and efficient evaluation of electrostatic interactions [37] . The system was minimized and equilibrated with the default protocols of the Desmond. Simulation event analysis, simulation quality analysis and simulation interaction diagram protocols of the Desmond package was exercised to analyze the trajectory files.

Post-simulation MM-GBSA analysis was performed by using the thermal_MMGBSA.py script of the Prime/Desmond module of the Schrodinger suite 2020-3. [27, 28] From each MD trajectory, every 10th frame was extracted from the last 50 ns of simulated trajectories, averaging over 50 frames, for binding free energy calculations of teicoplanin. The Prime MM-GBSA method uses rule of additivity wherein total binding free energy (Kcal/mol) represents a summation of individual energy modules like coulombic, covalent, hydrogen bond, van der Waals, self-contact, lipophilic, solvation, and π-π stackings of ligand and protein. [38] 

Validation of the implemented docking protocol in AutoDock 4.2 was performed by redocking of native co-crystallized ligand, N3 in the binding pocket of SARS-CoV-2 main protease. The root-mean square deviation (RMSD) of the best docked conformation of N3 and X-ray crystal structure was within 2Å in this study, confirming the reliability of the implemented scoring function (data not shown). According to the reported protocols, it is evident that for a successful docking, the RMSD should fall within ≤2.0 Å [39, 40] .

Therefore, adopted methodology of the molecular docking used in current study, can be relied to predict the molecular interaction of teicoplanin with the SARS-CoV-2 main protease.

Molecular docking is a computer-based process of facilitating the early stages of drug discovery through unveiling the mode of binding interactions of chemical compounds as well as systematic pre-screening on the basis of their shape and energetic compatibility with the target proteins. [17, 41] After successful completion of the docking calculations, ten best poses of teicoplanin obtained from each docking run was visualized in Biovia Discovery Studio 2020 and PyMol 1.7.4 programs to study ligand-protein interactions. As demonstrated in Table 1 , docked teicoplanin had ample opportunity within the SARS-CoV-2 main protease to interact by means of both hydrophobic as well as hydrophilic interactions. Fig. 4 (A for blind and C for defined docking) clearly depicts the contribution of Leu141, Asn142 and Glu166 for affording H-bond interactions with teicoplanin at the S1 subsite. In addition, Gln189 residue also contributes hydrogen bond interaction, supporting the docked teicoplanin in the shallow subsite (S3-S5) of the binding cavity. However, Leu50, Cys145 and Met165 participated in hydrophobic contacts in the form of π-alkyl bonds. Furthermore, contribution of Tyr126 was noted in hydrophobic links in the form of π-π stacking interactions while amide-π stacked interactions were also noted with Ser123 and Gly124 residues. In case of dimeric protein, involvement of His41 of catalytic dyad was observed for establishing polar interaction with teicoplanin in defined docking (Fig. 5) . 

In computer-aided drug discovery projects, several docking programs are routinely employed for interpreting the binding mode and the affinity of a ligand relative to a protein. However, the binding energy predicted by docking algorithms cannot be relied and hence, it is imperative to employ post-docking analyses to avoid false negatives and false positives [44] Nowadays, MM-GBSA method is frequently used for predicting the accurate binding energy of a protein-ligand complex and the obtained results can be exploited more rationally in the design of drug candidates. [45, 46] Therefore, the top ten poses of SARS CoV-2 main protease-teicoplanin complexes obtained from hundred docking runs in each category were further analysed by MM-GBSA approach for prediction of more accurate binding energy. In addition, Coulomb binding free energy, hydrogen bonding free energy, the lipophilic binding free energy, the generalized Born solvation binding free energy, the van der Waals binding free energy, and ligand strain energy were also computed and presented as Table S2 in Supplementary Information. The binding energies of the single best pose selected from ten MM/GBSA-optimized conformations belonging to each category of teicoplanin-M Pro complexes are displayed in Table 2 . The MM/GBSA results of snapshots from the MD trajectories along with standard deviation calculated from the last 50 frames are also demonstrated in Table 2 .

Dynamic and thermodynamics parameters of living systems under specific conditions of physiological environments can be estimated by the application of molecular dynamics (MD) simulation, a widely employed computer-aided drug design technique. [17, 18, 47] Therefore, the best docked pose of teicoplanin in complex with SARS-CoV-2 main protease was subjected to MD simulation study in order to investigate the stability of the ligand-protein complex as well as main intermolecular interactions during the simulated trajectory. Each docking pose representing monomer-blind, monomer-defined, dimer-blind and dimer-defined was subjected to MD simulation study owing to the minimum binding energy in MM-GBSA analysis (see Table S2 of supplementary information). In addition, apo form of both monomeric and dimeric forms of M Pro were also simulated for comparative analysis.

Desmond software was employed for the MD simulation of 100 ns in explicit solvent system. 

No potential conflict of interest was reported by the authors.

Faizul Azam: Conceptualization, Methodology, Formal analysis, Software, Validation, Writing, Editing and Funding acquisition. Eltayeb Eid: Project administration, Funding acquisition and Revision Abdulkarim Almutairi: Visualization, Data curation and Writingfirst draft.

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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The authors gratefully acknowledge the financial support for this study from the Qassim University, Saudi Arabia, represented by the deanship of scientific research (grant no. phuc-2020-1-1-L-10063) during the academic year 1441 AH/2020 AD. Authors are thankful to Schrodinger India for providing the access to Schrodinger Suite 2020-3. Dr Prajwal Nandekar and Dr Sudharshan Pandiyan are kindly acknowledged for their help and support.