The recent pandemic outbreak of COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), raised global health and economic concerns. Phylogenetically, SARS-CoV-2 is closely related to SARS-CoV, and both encode the enzyme main protease (Mpro/3CLpro), which can be a potential target inhibiting viral replication. Through this work, we have compiled the structural aspects of Mpro conformational changes, with molecular modeling and 1-μs MD simulations. Long-scale MD simulation resolves the mechanism role of crucial amino acids involved in protein stability, followed by ensemble docking which provides potential compounds from the Traditional Chinese Medicine (TCM) database. These lead compounds directly interact with active site residues (His41, Gly143, and Cys145) of Mpro, which plays a crucial role in the enzymatic activity. Through the binding mode analysis in the S1, S1', S2, and S4 binding subsites, screened compounds may be functional for the distortion of the oxyanion hole in the reaction mechanism, and it may lead to the inhibition of Mpro in SARS-CoV-2. The hit compounds are naturally occurring compounds; they provide a sustainable and readily available option for medical treatment in humans infected by SARS-CoV-2. Henceforth, extensive analysis through molecular modeling approaches explained that the proposed molecules might be promising SARS-CoV-2 inhibitors for the inhibition of COVID-19, subjected to experimental validation.

Computer Aided Drug Design and Molecular Modeling Lab Department of Bioinformatics Alagappa University Karaikudi India

Corrosion and Materials Protection Division Council of Scientific and Industrial Research Central Electrochemical Research Institute Karaikudi India

School of Biochemical Engineering Indian Institute of Technology Varanasi India

Section of Molecular Biology and Biochemistry Institute of Organic Chemistry and Biochemistry AS CR v v i Prague Czechia

See more in PubMed

Aldeghi M., Heifetz A., Bodkin M. J., Knapp S., Biggin P. C. (2017). Predictions of ligand selectivity from absolute binding free energy calculations. J. Am. Chem. Soc. 139, 946–957. 10.1021/jacs.6b11467 PubMed DOI PMC

Amaro R. E., Baudry J., Chodera J., Demir O., Mccammon J. A., Miao Y., et al. . (2018). Ensemble docking in drug discovery. Biophys. J. 114, 2271–2278. 10.1016/j.bpj.2018.02.038 PubMed DOI PMC

Ayres J. S. (2020). A metabolic handbook for the COVID-19 pandemic. Nat Metab. 2, 572–585. 10.1038/s42255-020-0237-2 PubMed DOI PMC

Battisti V., Wieder O., Garon A., Seidel T., Urban E., Langer T. (2020). A Computational approach to identify potential novel inhibitors against the coronavirus SARS-CoV-2. Mol. Inform. 39:e2000090. 10.1002/minf.202000090 PubMed DOI PMC

Bzowka M., Mitusinska K., Raczynska A., Samol A., Tuszynski J. A., Gora A. (2020). Structural and evolutionary analysis indicate that the SARS-CoV-2 mpro is a challenging target for small-molecule inhibitor design. Int. J. Mol. Sci. 21:3099. 10.3390/ijms21093099 PubMed DOI PMC

Cavasotto C. N., Di Filippo J. I. (2020). In silico drug repurposing for COVID-19: targeting SARS-CoV-2 proteins through docking and consensus ranking. Mol. Inform. 10.1002/minf.202000115 PubMed DOI

Chen C. Y. (2011). TCM Database@Taiwan: the world's largest traditional Chinese medicine database for drug screening in silico. PLoS ONE 6:e15939. 10.1371/journal.pone.0015939 PubMed DOI PMC

Childers M. C., Daggett V. (2018). Validating molecular dynamics simulations against experimental observables in light of underlying conformational ensembles. J. Phys. Chem. B 122, 6673–6689. 10.1021/acs.jpcb.8b02144 PubMed DOI PMC

Chinnasamy S., Selvaraj G., Kaushik A. C., Kaliamurthi S., Chandrabose S., Singh S. K., et al. . (2020a). Molecular docking and molecular dynamics simulation studies to identify potent AURKA inhibitors: assessing the performance of density functional theory, MM-GBSA and mass action kinetics calculations. J. Biomol. Struct. Dyn. 38, 4325–4335. 10.1080/07391102.2019.1674695 PubMed DOI

Chinnasamy S., Selvaraj G., Selvaraj C., Kaushik A. C., Kaliamurthi S., Khan A., et al. . (2020b). Combining in silico and in vitro approaches to identification of potent inhibitor against phospholipase A2 (PLA2). Int. J. Biol. Macromol. 144, 53–66. 10.1016/j.ijbiomac.2019.12.091 PubMed DOI

Culletta G., Gulott M. R., Perricone U., Zappal M., Almerico A. M., Tutone M. (2020). Exploring the SARS-CoV-2 Proteome in the search of potential inhibitors via structure-based pharmacophore modeling/docking approach. Computation 8:77 10.3390/computation8030077 DOI

Dai W., Zhang B., Jiang X. M., Su H., Li J., Zhao Y., et al. . (2020). Structure-based design of antiviral drug candidates targeting the SARS-CoV-2 main protease. Science 368, 1331–1335. 10.1126/science.abb4489 PubMed DOI PMC

Eleftheriou P., Amanatidou D., Petrou A., Geronikaki A. (2020). In silico evaluation of the effectivity of approved protease inhibitors against the main protease of the novel SARS-CoV-2 virus. Molecules 25:2529. 10.3390/molecules25112529 PubMed DOI PMC

Evangelista Falcon W., Ellingson S. R., Smith J. C., Baudry J. (2019). Ensemble docking in drug discovery: how many protein configurations from molecular dynamics simulations are needed to reproduce known ligand binding? J. Phys. Chem. B 123, 5189–5195. 10.1021/acs.jpcb.8b11491 PubMed DOI

Fang S. G., Shen H., Wang J., Tay F. P., Liu D. X. (2008). Proteolytic processing of polyproteins 1a and 1ab between non-structural proteins 10 and 11/12 of Coronavirus infectious bronchitis virus is dispensable for viral replication in cultured cells. Virology 379, 175–180. 10.1016/j.virol.2008.06.038 PubMed DOI PMC

Ferraz W. R., Gomes R. A., Al S. N., Goulart Trossini G. H. (2020). Ligand and structure-based virtual screening applied to the SARS-CoV-2 main protease: an in silico repurposing study. Future Med. Chem. 12, 1815–1828. 10.4155/fmc-2020-0165 PubMed DOI PMC

Frances-Monerris A., Hognon C., Miclot T., Garcia-Iriepa C., Iriepa I., Terenzi A., et al. . (2020). Molecular basis of SARS-CoV-2 infection and rational design of potential antiviral agents: modeling and simulation approaches. J. Proteome Res. 19, 4291–4315. 10.1021/acs.jproteome.0c00779 PubMed DOI

Friesner R. A., Murphy R. B., Repasky M. P., Frye L. L., Greenwood J. R., Halgren T. A., et al. . (2006). Extra precision glide: docking and scoring incorporating a model of hydrophobic enclosure for protein-ligand complexes. J. Med. Chem. 49, 6177–6196. 10.1021/jm051256o PubMed DOI

Gahlawat A., Kumar N., Kumar R., Sandhu H., Singh I. P., Singh S., et al. . (2020). Structure-based virtual screening to discover potential lead molecules for the SARS-CoV-2 main protease. J. Chem. Inf. Model. 4;acs.jcim.0c00546. 10.1021/acs.jcim.0c00546 PubMed DOI

Gani O. A., Narayanan D., Engh R. A. (2013). Evaluating the predictivity of virtual screening for ABL kinase inhibitors to hinder drug resistance. Chem. Biol. Drug Des. 82, 506–519. 10.1111/cbdd.12170 PubMed DOI PMC

Gao J., Zhang L., Liu X., Li F., Ma R., Zhu Z., et al. . (2020). Repurposing low-molecular-weight drugs against the main protease of severe acute respiratory syndrome coronavirus 2. J. Phys. Chem. Lett. 11, 7267–7272. 10.1021/acs.jpclett.0c01894 PubMed DOI

Gil C., Ginex T., Maestro I., Nozal V., Barrado-Gil L., Cuesta-Geijo M. A., et al. . (2020). COVID-19: drug targets and potential treatments. J. Med. Chem. 10.1021/acs.jmedchem.0c00606 PubMed DOI

Goyal B., Goyal D. (2020). Targeting the dimerization of the main protease of coronaviruses: a potential broad-spectrum therapeutic strategy. ACS Comb. Sci. 22, 297–305. 10.1021/acscombsci.0c00058 PubMed DOI

Halgren T. A., Murphy R. B., Friesner R. A., Beard H. S., Frye L. L., Pollard W. T., et al. . (2004). Glide: a new approach for rapid, accurate docking and scoring. 2. Enrichment factors in database screening. J. Med. Chem. 47, 1750–1759. 10.1021/jm030644s PubMed DOI

Hanney S. R., Wooding S., Sussex J., Grant J. (2020). From COVID-19 research to vaccine application: why might it take 17 months not 17 years and what are the wider lessons? Health Res. Policy Syst. 18:61. 10.1186/s12961-020-00571-3 PubMed DOI PMC

Hilgenfeld R. (2014). From SARS to MERS: crystallographic studies on coronaviral proteases enable antiviral drug design. FEBS J. 281, 4085–4096. 10.1111/febs.12936 PubMed DOI PMC

Jeong G. U., Song H., Yoon G. Y., Kim D., Kwon Y. C. (2020). Therapeutic strategies against COVID-19 and structural characterization of SARS-CoV-2: a review. Front. Microbiol. 11:1723. 10.3389/fmicb.2020.01723 PubMed DOI PMC

Jin Z., Du X., Xu Y., Deng Y., Liu M., Zhao Y., et al. . (2020). Structure of M(pro) from SARS-CoV-2 and discovery of its inhibitors. Nature 582, 289–293. 10.1038/s41586-020-2223-y PubMed DOI

Kalyaanamoorthy S., Chen Y. P. (2014). A steered molecular dynamics mediated hit discovery for histone deacetylases. Phys. Chem. Chem. Phys. 16, 3777–3791. 10.1039/c3cp53511h PubMed DOI

Klimovich P. V., Mobley D. L. (2015). A Python tool to set up relative free energy calculations in GROMACS. J. Comput. Aided Mol. Des. 29, 1007–1014. 10.1007/s10822-015-9873-0 PubMed DOI PMC

Lai C. C., Shih T. P., Ko W. C., Tang H. J., Hsueh P. R. (2020). Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and coronavirus disease-2019 (COVID-19): the epidemic and the challenges. Int. J. Antimicrob. Agents 55:105924. 10.1016/j.ijantimicag.2020.105924 PubMed DOI PMC

Li H., Liu S. M., Yu X. H., Tang S. L., Tang C. K. (2020). Coronavirus disease 2019 (COVID-19): current status and future perspectives. Int. J. Antimicrob. Agents 55:105951. 10.1016/j.ijantimicag.2020.105951 PubMed DOI PMC

Lorber D. M., Shoichet B. K. (1998). Flexible ligand docking using conformational ensembles. Protein Sci. 7, 938–950. 10.1002/pro.5560070411 PubMed DOI PMC

Luan B., Huynh T., Cheng X., Lan G., Wang H. R. (2020). Targeting proteases for treating COVID-19. J. Proteome Res. 19, 4316–4326. 10.1021/acs.jproteome.0c00430 PubMed DOI

Meyer-Almes F. J. (2020). Repurposing approved drugs as potential inhibitors of 3CL-protease of SARS-CoV-2: virtual screening and structure based drug design. Comput. Biol. Chem. 88:107351. 10.1016/j.compbiolchem.2020.107351 PubMed DOI PMC

Mizutani M. Y., Takamatsu Y., Ichinose T., Nakamura K., Itai A. (2006). Effective handling of induced-fit motion in flexible docking. Proteins 63, 878–891. 10.1002/prot.20931 PubMed DOI

Mohammadi E., Benfeitas R., Turkez H., Boren J., Nielsen J., Uhlen M., et al. . (2020). Applications of genome-wide screening and systems biology approaches in drug repositioning. Cancers 12:2694. 10.3390/cancers12092694 PubMed DOI PMC

Pal M., Berhanu G., Desalegn C., Kandi V. (2020). Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2): an update. Cureus 12:e7423. 10.7759/cureus.7423 PubMed DOI PMC

Perez-Regidor L., Zarioh M., Ortega L., Martin-Santamaria S. (2016). Virtual screening approaches towards the discovery of toll-like receptor modulators. Int. J. Mol. Sci. 17:1508. 10.3390/ijms17091508 PubMed DOI PMC

Pillaiyar T., Manickam M., Namasivayam V., Hayashi Y., Jung S. H. (2016). An overview of severe acute respiratory syndrome-coronavirus (SARS-CoV) 3CL protease inhibitors: peptidomimetics and small molecule chemotherapy. J. Med. Chem. 59, 6595–6628. 10.1021/acs.jmedchem.5b01461 PubMed DOI PMC

Pronk S., Pall S., Schulz R., Larsson P., Bjelkmar P., Apostolov R., et al. . (2013). GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit. Bioinformatics 29, 845–854. 10.1093/bioinformatics/btt055 PubMed DOI PMC

Rabi F. A., Al Zoubi M. S., Kasasbeh G. A., Salameh D. M., Al-Nasser A. D. (2020). SARS-CoV-2 and coronavirus disease 2019: what we know so far. Pathogens 9:231. 10.3390/pathogens9030231 PubMed DOI PMC

Salmaso V., Moro S. (2018). Bridging molecular docking to molecular dynamics in exploring ligand-protein recognition process: an overview. Front. Pharmacol. 9:923. 10.3389/fphar.2018.00923 PubMed DOI PMC

Sastry G. M., Adzhigirey M., Day T., Annabhimoju R., Sherman W. (2013). Protein and ligand preparation: parameters, protocols, and influence on virtual screening enrichments. J. Comput. Aided Mol. Des. 27, 221–234. 10.1007/s10822-013-9644-8 PubMed DOI

Saul S., Einav S. (2020). Old drugs for a new virus: repurposed approaches for combating COVID-19. ACS Infect Dis. 6, 2304–2318. 10.1021/acsinfecdis.0c00343 PubMed DOI

Seifert M. H., Kraus J., Kramer B. (2007). Virtual high-throughput screening of molecular databases. Curr. Opin. Drug Discov. Dev. 10, 298–307 PubMed

Selvaraj C., Dinesh D. C., Panwar U., Boura E., Singh S. K. (2020b). High-throughput screening and quantum mechanics for identifying potent inhibitors against Mac1 Domain of SARS-CoV-2 Nsp3. Chem. Biol. 11, 1445–1453. 10.1016/j.chembiol.2004.08.011 PubMed DOI PMC

Selvaraj C., Sakkiah S., Tong W., Hong H. (2018). Molecular dynamics simulations and applications in computational toxicology and nanotoxicology. Food Chem. Toxicol. 112, 495–506. 10.1016/j.fct.2017.08.028 PubMed DOI

Selvaraj C., Dinesh D. C., Panwar U., Abhirami R., Boura E., Singh S. K. (2020a). Structure-based virtual screening and molecular dynamics simulation of SARS-CoV-2 Guanine-N7 methyltransferase (nsp14) for identifying antiviral inhibitors against COVID-19. J. Biomol. Struct. Dyn. 1-12. 10.1080/07391102.2020.1778535 PubMed DOI PMC

Shyr Z. A., Gorshkov K., Chen C. Z., Zheng W. (2020). Drug discovery strategies for SARS-CoV-2. J. Pharmacol. Exp. Ther. 375, 127–138. 10.1124/jpet.120.000123 PubMed DOI PMC

Singh T. U., Parida S., Lingaraju M. C., Kesavan M., Kumar D., Singh R. K. (2020). Drug repurposing approach to fight COVID-19. Pharmacol. Rep. 5, 1–30. 10.1007/s43440-020-00155-6 PubMed DOI PMC

Tharappel A. M., Samrat S. K., Li Z., Li H. (2020). Targeting crucial host factors of SARS-CoV-2. ACS Infect Dis. 6, 2844–2865. 10.1021/acsinfecdis.0c00456 PubMed DOI PMC

Touret F., Gilles M., Barral K., Nougairede A., Van Helden J., Decroly E., et al. . (2020). In vitro screening of a FDA approved chemical library reveals potential inhibitors of SARS-CoV-2 replication. Sci. Rep. 10:13093. 10.1038/s41598-020-70143-6 PubMed DOI PMC

Tripathi S. K., Singh S. K., Singh P., Chellaperumal P., Reddy K. K., Selvaraj C. (2012). Exploring the selectivity of a ligand complex with CDK2/CDK1: a molecular dynamics simulation approach. J. Mol. Recognit. 25, 504–512. 10.1002/jmr.2216 PubMed DOI

Ullrich S., Nitsche C. (2020). The SARS-CoV-2 main protease as drug target. Bioorg. Med. Chem. Lett. 30:127377. 10.1016/j.bmcl.2020.127377 PubMed DOI PMC

Umesh Kundu D., Selvaraj C., Singh S. K., Dubey V. K. (2020). Identification of new anti-nCoV drug chemical compounds from Indian spices exploiting SARS-CoV-2 main protease as target. J. Biomol. Struct. Dyn. 1–9. 10.1080/07391102.2020.1763202 PubMed DOI PMC

Van Aalten D. M., Bywater R., Findlay J. B., Hendlich M., Hooft R. W., Vriend G. (1996). PRODRG, a program for generating molecular topologies and unique molecular descriptors from coordinates of small molecules. J. Comput. Aided Mol. Des. 10, 255–262. 10.1007/BF00355047 PubMed DOI

Van Der Spoel D., Lindahl E., Hess B., Groenhof G., Mark A. E., Berendsen H. J. (2005). GROMACS: fast, flexible, and free. J. Comput. Chem. 26, 1701–1718. 10.1002/jcc.20291 PubMed DOI

Vannabouathong C., Devji T., Ekhtiari S., Chang Y., Phillips S. A., Zhu M., et al. . (2020). Novel coronavirus COVID-19: current evidence and evolving strategies. J. Bone Joint Surg. Am 102, 734–744. 10.2106/JBJS.20.00396 PubMed DOI PMC

Wahba L., Jain N., Fire A. Z., Shoura M. J., Artiles K. L., Mccoy M. J., et al. . (2020). An Extensive meta-metagenomic search identifies sars-cov-2-homologous sequences in pangolin lung viromes. mSphere 5, e00160–20. 10.1128/mSphere.00160-20 PubMed DOI PMC

Wang J. (2020). Fast identification of possible drug treatment of coronavirus disease-19 (covid-19) through computational drug repurposing study. J. Chem. Inf. Model. 60, 3277–3286. 10.1021/acs.jcim.0c00179 PubMed DOI PMC

Xu H. Y., Zhang Y. Q., Liu Z. M., Chen T., Lv C. Y., Tang S. H., et al. . (2019). ETCM: an encyclopaedia of traditional Chinese medicine. Nucleic Acids Res. 47, D976–D982. 10.1093/nar/gky987 PubMed DOI PMC

Yoshino R., Yasuo N., Sekijima M. (2020). Identification of key interactions between SARS-CoV-2 main protease and inhibitor drug candidates. Sci. Rep. 10:12493. 10.1038/s41598-020-69337-9 PubMed DOI PMC

Yuan H., Ma Q., Ye L., Piao G. (2016). The traditional medicine and modern medicine from natural products. Molecules 21:559. 10.3390/molecules21050559 PubMed DOI PMC

Zeng L., Guan M., Jin H., Liu Z., Zhang L. (2015). Integrating pharmacophore into membrane molecular dynamics simulations to improve homology modeling of G protein-coupled receptors with ligand selectivity: A2A adenosine receptor as an example. Chem. Biol. Drug Des 86, 1438–1450. 10.1111/cbdd.12607 PubMed DOI

Zhang L., Lin D., Sun X., Curth U., Drosten C., Sauerhering L., et al. . (2020). Crystal structure of SARS-CoV-2 main protease provides a basis for design of improved alpha-ketoamide inhibitors. Science 368, 409–412. 10.1126/science.abb3405 PubMed DOI PMC

Zhao J., Cui W., Tian B. P. (2020). The potential intermediate hosts for SARS-CoV-2. Front. Microbiol. 11:580137 10.3389/fmicb.2020.580137 PubMed DOI PMC

Zheng J. (2020). SARS-CoV-2: an emerging coronavirus that causes a global threat. Int. J. Biol. Sci. 16, 1678–1685. 10.7150/ijbs.45053 PubMed DOI PMC

Zhu Z., Lian X., Su X., Wu W., Marraro G. A., Zeng Y. (2020). From SARS and MERS to COVID-19: a brief summary and comparison of severe acute respiratory infections caused by three highly pathogenic human coronaviruses. Respir. Res. 21:224. 10.1186/s12931-020-01479-w PubMed DOI PMC

Zoete V., Irving M. B., Michielin O. (2010). MM-GBSA binding free energy decomposition and T cell receptor engineering. J. Mol. Recognit. 23, 142–152. 10.1002/jmr.1005 PubMed DOI