key: cord-0687437-04viwind authors: Al-Sehemi, Abdullah G.; Pannipara, Mehboobali; Parulekar, Rishikesh S.; Kilbile, Jaydeo T.; Choudhari, Prafulla B.; Shaikh, Mubarak H. title: In Silico Exploration of Binding Potentials of Anti SARS-CoV-1 Phytochemicals against Main Protease of SARS-CoV-2 date: 2022-03-11 journal: Journal of Saudi Chemical Society DOI: 10.1016/j.jscs.2022.101453 sha: 193fe881e0d692139730d4ca6ed9f2ec04eaa2bd doc_id: 687437 cord_uid: 04viwind The phytochemicals can play complementary medicine compared to synthetic drugs considering their natural origin, safety, and low cost. Phytochemicals hold a key position for the expansion of drug development against corona viruses and need better consideration to the agents that have already been shown to display effective activity against various strains of corona viruses. In this study, we performed molecular docking studies on potential forty seven phytochemicals which are SARS-CoV-1 Mpro inhibitors to identify potential candidate against the main proteins of SARS-CoV-2. In Silico Molecular docking studies revealed that phytochemicals 16 (Broussoflavan A), 22 (Dieckol), 31 (Hygromycin B), 45 (Sinigrin) and 46 (Theaflavin-3,3’-digallate) exhibited excellent SARS-CoV-2 Mpro inhibitors. Furthermore, supported by Molecular dynamics (MD) simulation analysis such as Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF), Radius of gyration (Rg) and H-bond interaction analysis. We expect that our findings will provide designing principles for new corona virus strains and establish important frameworks for the future development of antiviral drugs. Current high outline, global outbreaks of viral diseases from the coronavirus family have been caused by enveloped viruses. Acute respiratory tract inflammation caused by SARS-CoV-2 is an infectious disease, often fatal, that is characterized by the rapid and unexpected spread. Worldwide, the COVID-19 pandemic has recorded, as of 1 st March 2022, 437 million cases, 369 million recovered cases with 5.97 million deaths, and the numbers continue to increase progressively [1] (https://covid19.who.int/). Furthermore, patients with pre-existing kidney dysfunction, immune-compromised persons, pulmonary disease and diabetes are the most susceptible community with higher mortality rates from SARS-CoV-2 infection. Coronavirus families are able to cause a number of diseases, such as hepatitis, gastroenteritis, bronchitis, systemic diseases, and even death in birds, humans, and other animals [2] . The contagion effect of such epidemic could possibly bring key challenges to worldwide health systems and have farreaching significances on the global economy if it is not controlled effectively. The SARS coronavirus is the viable microorganism accountable for the worldwide outburst of a severe disease that caused several deaths [3] . To design the anti-SARS drug, the coronavirus main protease (M pro ), recognized as the utmost attractive target due to its crucial role in facilitating viral transcription and replication [4] . Near about 30,000 nucleotides comprised in the SARS-CoV-2 genome: the gene of SARS-CoV-2 namely, replicase encodes pp1a and pp1ab two overlapping polyproteins which are essential for viral replication and transcription [5] . Polyproteins excreted the functional polypeptides by extensive proteolytic processing, mostly by the 33.8-kDa M pro (also known as 3C-like protease). Polyprotein digested by M pro at least 11 conserved sites, initially the autolytic cleavage of this enzyme itself from pp1a and pp1ab [6] . In the viral life cycle M pro plays functional importance, shared with the absence of closely associated homologues in humans, recognize M pro as an attractive target for the design of antiviral drugs [7] . Herein we describe the in silico molecular docking results that intended quickly discovery of lead compounds for clinical use, by assimilation structure-assisted drug design, virtual drug screening. This in silico study focused on identifying drug leads that target main protease (M pro ) of SARS-CoV-2. Jin and co-worker identified a mechanism-based inhibitor by computer-aided drug design, and then determined the crystal structure of M pro of SARS-CoV-2 [8] . We have screened 47 SARS-CoV-1 M pro active phytochemicals for high binding affinity and interaction to the conserved residues of the substrate-binding pocket of SARS-CoV-2 M pro using molecular docking-based virtual screening. Our results demonstrated the efficacy of our screening strategy, which can lead to the rapid discovery of drug leads with clinical potential in response to new infectious diseases for which no specific drugs or vaccines are available. Molecular docking study was performed to explore the binding potential of the selected phytochemicals against the M pro of SARS-CoV-2. Structure of the M pro of SARS-CoV-2 (PDB ID: 6W63) [9] was downloaded from the free protein database www.rcsb.org. The phytochemical analyzed in this work are showed profound activity against SARS-CoV-1 and their possible mode of action is via inhibition of the main protease. SARS-CoV-2 is mutated from of the main protease of SARS-CoV-1 and has up to 96% similarity [10, 11] . Table- 1 shows structures of phytochemicals utilized in current study. In virtue of all these reports, we thought virtual analysis of the molecules with profound activity on the SARS-CoV-1 on main protease of SARS-CoV-2 will be an attractive strategy for identification and development of potent inhibitors against viruses. Thus, phytochemicals with reported activity against SARS-CoV-1 were selected for the docking analysis [12] [13] [14] . Grip based docking simulation was performed and best molecules were analyzed on the basis of docking score and binding interactions with M pro of SARS-CoV-2. The molecular docking study revealed the most promising phytochemical inhibitor Radius of gyration helps to investigate the changes observed in the conformation of SARS-CoV-2 M pro in terms of compactness after binding of different inhibitor (phytochemical) molecules [18] [19] . By meaning, Rg corresponds to mass weighted root mean square distance of a collection of atoms from their common center of mass. Therefore the overall conformation of the protein could be analyzed by calculating the Rg values. Figure 8C indicates the Rg values of control and different M pro -inhibitor docked complexes over entire simulation period. The Rg values for control and different M pro -inhibitor complexes were found to be in the range of 2.2 nm to 2.26 nm ( Figure 8C ). From this it is apparent that there is no change in the conformation of the M pro protein after binding of different phytochemical inhibitors and also the compactness of M pro structure was found to be similar in presence of experimental inhibitor X77 and computationally identified phytochemical inhibitors (Figure 8C) . The structure of the M pro protein of SARS-CoV-2 (PDB ID: 6W63) [9] was downloaded from the free protein structure database RCSB (www.rcsb.org) with resolution of 2.1 Å. The downloaded protein structure was prepared for the docking analysis using V life MDS 4.6 via addition of missing hydrogen atoms. This prepared protein structure was utilized for the docking analysis. The structures of the phytochemical compounds were drawn by using molecule builder module of the V life MDS 4.6 and converted into the 3D structures. These developed structures were then optimized via energy minimization using merck molecular force field (MMFF). These optimized structures of phytochemical compounds were utilized for docking analysis. The molecular docking study of the phytochemical compounds with receptor SARS-CoV-2 M pro protein was performed using biopredicta module. Redocking was performed using native ligand X77 of SARS-CoV-2 M pro , to ascertain the docking protocol applied [15] [16] [17] . all atom force field [21] , whereas topology files of all inhibitor molecules was generated using PRODRG server [22] . After generating topology of each complex, further each complex was centered in the system of cubic box by keeping periodic distance of 1 nm between complex and edge of the box. All complexes were then solvated with SPC216 water molecules to fill the defined box for each complex. The solvated systems were neutralized by addition of suitable number of Na + ions to maintain electro-neutrality of the system. The Particle-Mesh-Ewald (PME) method [23] was used for calculation of long-range electrostatic interactions of all the systems. A 50,000step energy minimization was performed with the steepest descent (SD) method at 300 K by applying periodic boundary conditions (PBC) in all directions. Berendsen thermostat temperature coupling and Parrinello-Rahman pressure coupling for each 500-ps run were used to keep all the systems in equilibrated environment 300 K and 1 bar, respectively. The leap-frog algorithm was used for integrating Newton's equation in molecular dynamics (MD) simulation of all the systems. All the bond lengths were constrained using the LINCS algorithm [24] , and the time step was set to 0.002 ps. Finally, a 20-ns MD simulation was carried out for all eight systems. The simulation trajectories obtained after 20 ns MD simulations were analyzed using gmx_rms, gmx_rmsf, gmx_gyrate and gmx_hbond tools from the GROMACS 2018.3 package [20] and visualized using UCSF Chimera molecular visualizing software [25] . In the present study, we extensively analyzed the binding potential and mechanism of inhibition of phytochemical towards the SARS-CoV-2 M pro having profound inhibition towards WHO Health Emergency Dashboard WHO (COVID-19) Homepage Understanding the Latest Human Coronavirus Threat Sars study group, Coronavirus as a possible cause of severe acute respiratory syndrome Coronavirus main proteinase (3CLpro) structure: basis for design of anti-SARS drugs A pneumonia outbreak associated with a new coronavirus of probable bat origin A new coronavirus associated with human respiratory disease in China Conservation of substrate specificities among coronavirus main proteases An Overview of Severe Acute Respiratory Syndrome-Coronavirus (SARS-CoV) 3CL Protease Inhibitors: Peptidomimetics and Small Molecule Chemotherapy Structure of Mpro from SARS-CoV-2 and discovery of its inhibitors Coronavirus genomics and bioinformatics analysis Probable pangolin origin of SARS-CoV-2 associated with the COVID-19 outbreak Natural products and their derivatives against coronavirus: A review of the non-clinical and pre-clinical data Structural basis of SARS-CoV-2 3CLpro and anti-COVID-19 drug discovery from medicinal plants Antiviral effect of phytochemicals from medicinal plants: Applications and drug delivery strategies Potential of NO donor furoxan as SARS-CoV-2 main protease (M pro ) inhibitors: in silico analysis Design and in silico investigation of novel Maraviroc analogues as dual inhibition of CCR-5/SARS-CoV-2 M pro In silico evaluation of NO donor heterocyclic vasodilators as SARS-CoV-2 M pro protein inhibitor Molecular modeling studies to explore the binding affinity of virtually screened inhibitor toward different aminoglycoside kinases from diverse MDR strains Insights into the antibiotic resistance and inhibition mechanism of aminoglycoside phosphotransferase from Bacillus cereus: In silico and in vitro perspective GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers Evaluation and Reparametrization of the OPLS-AA Force Field for Proteins via Comparison with Accurate Quantum Chemical Calculations on Peptides PRODRG, a program for generating molecular topologies and unique molecular descriptors from coordinates of small molecules A smooth particle mesh Ewald method LINCS: A linear constraint solver for molecular simulations UCSF Chimera-A Visualization System for Exploratory Research and Analysis The authors are thankful to the Institute of research and consulting studies at King Khalid University for funding this research through grant number 3-N-20/21. Authors are also thankful to Dr. Yasinalli Tamboli for valuable suggestions during preparation of manuscript. The authors declare no conflict of interest, financial or otherwise.