De novo designed inhibitor has high affinity to four variants of the RBD of S-glycoprotein of SARS-CoV-2 - an in silico study

References

• Abraham, M. J., Murtola, T., Schulz, R., Páll, S., Smith, J. C., Hess, B., & Lindahl, E. (2015). GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX, 1–2, 19–25. https://doi.org/10.1016/j.softx.2015.06.001
   Google Scholar
• Andricopulo, A. D., Salum, L. B., & Abraham, D. J. (2009). Structure-based drug design strategies in medicinal chemistry. Current Topics in Medicinal Chemistry, 9(9), 771–790. https://doi.org/10.2174/156802609789207127
   PubMed Web of Science ®Google Scholar
• Bardiot, D., Vangeel, L., Koukni, M., Arzel, P., Zwaagstra, M., Lyoo, H., Wanningen, P., Ahmad, S., Zhang, L., Sun, X., Delpal, A., Eydoux, C., Guillemot, J.-C., Lescrinier, E., Klaassen, H., Leyssen, P., Jochmans, D., Castermans, K., Hilgenfeld, R., … Marchand, A. (2022). Synthesis, structure-activity relationships, and antiviral profiling of 1-heteroaryl-2-alkoxyphenyl analogs as inhibitors of SARS-CoV-2 replication. Molecules (Basel, Switzerland), 27(3), 1052. https://doi.org/10.3390/molecules27031052
   PubMed Web of Science ®Google Scholar
• Berman, H. M., Battistuz, T., Bhat, T. N., Bluhm, W. F., Bourne, P. E., Burkhardt, K., Feng, Z., Gilliland, G. L., Iype, L., Jain, S., Fagan, P., Marvin, J., Padilla, D., Ravichandran, V., Schneider, B., Thanki, N., Weissig, H., Westbrook, J. D., & Zardecki, C. (2002). The protein data bank. Acta Crystallographica. Section D, Biological Crystallography, 58(Pt 6 No 1), 899–907. https://doi.org/10.1107/s0907444902003451
   PubMedGoogle Scholar
• Bickerton, G. R., Paolini, G. V., Besnard, J., Muresan, S., & Hopkins, A. L. (2012). Quantifying the chemical beauty of drugs. Nature Chemistry, 4(2), 90–98. https://doi.org/10.1038/nchem.1243
   PubMed Web of Science ®Google Scholar
• Bittermann, K., & Goss, K. U. (2017). Predicting apparent passive permeability of Caco-2 and MDCK cell-monolayers: A mechanistic model. PloS One, 12(12), e0190319. https://doi.org/10.1371/journal.pone.0190319
   PubMed Web of Science ®Google Scholar
• Borisevich, S. S., Khamitov, E. M., Gureev, M. A., Yarovaya, O. I., Rudometova, N. B., Zybkina, A. V., Mordvinova, E. D., Shcherbakov, D. N., Maksyutov, R. A., & Salakhutdinov, N. F. (2022). Simulation of molecular dynamics of SARS-CoV-2 S-protein in the presence of multiple arbidol molecules: Interactions and binding mode insights. Viruses, 14(1), 119. https://doi.org/10.3390/v14010119
   PubMed Web of Science ®Google Scholar
• Caohuy, H., Eidelman, O., Chen, T., Liu, S., Yang, Q., Bera, A., Walton, N. I., Wang, T. T., & Pollard, H. B. (2021). Common cardiac medications potently inhibit ACE2 binding to the SARS-CoV-2 Spike, and block virus penetration and infectivity in human lung cells. Scientific Reports, 11(1), 22195. https://doi.org/10.1038/s41598-021-01690-9
   PubMed Web of Science ®Google Scholar
• Chan-Yeung, M., & Xu, R. H. (2003). SARS: Epidemiology. Respirology (Carlton, Vic.), 8(s1), S9–S14. https://doi.org/10.1046/j.1440-1843.2003.00518.x
   PubMedGoogle Scholar
• DeLano, W. L. (2002). The PyMOL molecular graphics system on World Wide Web. http://www.pymol.org
   Google Scholar
• Dong, E., Du, H., & Gardner, L. (2020). An interactive web-based dashboard to track COVID-19 in real time. The Lancet. Infectious Diseases, 20(5), 533–534. https://doi.org/10.1016/S1473-3099(20)30120-1
   PubMed Web of Science ®Google Scholar
• Duan, L., Liu, X., & Zhang, J. Z. (2016). Interaction entropy: A new paradigm for highly efficient and reliable computation of protein-ligand binding free energy. Journal of the American Chemical Society, 138(17), 5722–5728. https://doi.org/10.1021/jacs.6b02682
   PubMed Web of Science ®Google Scholar
• Ertl, P., & Schuffenhauer, A. (2009). Estimation of synthetic accessibility score of drug-like molecules based on molecular complexity and fragment contributions. Journal of Cheminformatics, 1(1), 8. https://doi.org/10.1186/1758-2946-1-8
   PubMed Web of Science ®Google Scholar
• Hanwell, M., Curtis, D., Lonie, D., Vandermeersch, T., Zurek, E., & Hutchison, G. (2012). Avogadro: An advanced semantic chemical editor, visualization, and analysis platform. Journal of Cheminformatics, 4(1), 17. https://doi.org/10.1186/1758-2946-4-17
   PubMed Web of Science ®Google Scholar
• Huang, J., Rauscher, S., Nawrocki, G., Ran, T., Feig, M., de Groot, B. L., Grubmüller, H., & MacKerell, A. D. Jr(2017). CHARMM36m: An improved force field for folded and intrinsically disordered proteins. Nature Methods, 14(1), 71–73. https://doi.org/10.1038/nmeth.4067
   PubMed Web of Science ®Google Scholar
• Jo, S., Kim, T., Iyer, V. G., & Im, W. (2008). CHARMM-GUI: A web-based graphical user interface for CHARMM. Journal of Computational Chemistry, 29(11), 1859–1865. https://doi.org/10.1002/jcc.20945
   PubMed Web of Science ®Google Scholar
• Karthic, A., Kesarwani, V., Singh, R. K., Yadav, P. K., Chaturvedi, N., Chauhan, P., Yadav, B. S., & Kushwaha, S. K. (2022). Computational analysis reveals monomethylated triazolopyrimidine as a novel inhibitor of SARS-CoV-2 RNA-dependent RNA polymerase (RdRp). Molecules (Basel, Switzerland), 27(3), 801. https://doi.org/10.3390/molecules27030801
   PubMed Web of Science ®Google Scholar
• Kumar, S., Dutta, D., Ravichandiran, V., & Sukla, S. (2022). Monoclonal antibodies: A remedial approach to prevent SARS-CoV-2 infection. 3 Biotech, 12(9), 227. https://doi.org/10.1007/s13205-022-03281-5
   PubMedGoogle Scholar
• Lazniewski, M., Dermawan, D., Hidayat, S., Muchtaridi, M., Dawson, W. K., & Plewczynski, D. (2022). Drug repurposing for identification of potential spike inhibitors for SARS-CoV-2 using molecular docking and molecular dynamics simulations. Methods (San Diego, Calif.), 203, 498–510. https://doi.org/10.1016/j.ymeth.2022.02.004
   PubMed Web of Science ®Google Scholar
• Lipinski, C. A. (2000). Drug-like properties and the causes of poor solubility and poor permeability. Journal of Pharmacological and Toxicological Methods, 44(1), 235–249. https://doi.org/10.1016/S1056-8719(00)00107-6
   PubMed Web of Science ®Google Scholar
• Markopoulos, C., Thoenen, F., Preisig, D., Symillides, M., Vertzoni, M., Parrott, N., Reppas, C., & Imanidis, G. (2014). Biorelevant media for transport experiments in the Caco-2 model to evaluate drug absorption in the fasted and the fed state and their usefulness. European Journal of Pharmaceutics and Biopharmaceutics : Official Journal of Arbeitsgemeinschaft Fur Pharmazeutische Verfahrenstechnik e.V, 86(3), 438–448. https://doi.org/10.1016/j.ejpb.2013.10.017
   PubMed Web of Science ®Google Scholar
• Onufriev, A., Bashford, D., & Case, D. A. (2004). Exploring protein native states and large-scale conformational changes with a modified generalized born model. Proteins, 55(2), 383–394. https://doi.org/10.1002/prot.20033
   PubMed Web of Science ®Google Scholar
• Pekka, M., & Lennart, N. (2001). Structure and dynamics of the TIP3P, SPC, and SPC/E water models at 298 K. The Journal of Physical Chemistry A, 105(43), 9954–9960. https://doi.org/10.1021/jp003020w
   Google Scholar
• Ramírez, D., & Caballero, J. (2018). Is it reliable to take the molecular docking top scoring position as the best solution without considering available structural data? Molecules (Basel, Switzerland), 23(5), 1038. https://doi.org/10.3390/molecules23051038
   PubMed Web of Science ®Google Scholar
• Rampogu, S., Lee, G., Park, J. S., Lee, K. W., & Kim, M. O. (2022). Molecular docking and molecular dynamics simulations discover curcumin analogue as a plausible dual inhibitor for SARS-CoV-2. International Journal of Molecular Sciences, 23(3), 1771. https://doi.org/10.3390/ijms23031771
   PubMed Web of Science ®Google Scholar
• Rossetti, G. G., Ossorio, M. A., Rempel, S., Kratzel, A., Dionellis, V. S., Barriot, S., Tropia, L., Gorgulla, C., Arthanari, H., Thiel, V., Mohr, P., Gamboni, R., & Halazonetis, T. D. (2022). Non-covalent SARS-CoV-2 Mpro inhibitors developed from in silico screen hits. Scientific Reports, 12(1), 2505. https://doi.org/10.1038/s41598-022-06306-4[PMC][35169179]
   PubMed Web of Science ®Google Scholar
• Saadi, F., Pal, D., & Sarma, J. D. (2021). Spike glycoprotein is central to coronavirus pathogenesis-parallel between m-CoV and SARS-CoV-2. Annals of Neurosciences, 28(3–4), 201–218. https://doi.org/10.1177/09727531211023755
   PubMed Web of Science ®Google Scholar
• Sanyaolu, A., Okorie, C., Marinkovic, A., Haider, N., Abbasi, A. F., Jaferi, U., Prakash, S., & Balendra, V. (2021). The emerging SARS-CoV-2 variants of concern. Therapeutic Advances in Infectious Disease, 8, 20499361211024372. https://doi.org/10.1177/20499361211024372
   Web of Science ®Google Scholar
• Seeliger, D., & de Groot, B. L. (2010). Conformational transitions upon ligand binding: Holo-structure prediction from apo conformations. PLoS Computational Biology, 6(1), e1000634. https://doi.org/10.1371/journal.pcbi.1000634
   PubMed Web of Science ®Google Scholar
• Syed, A., Khan, A., Gosai, F., Asif, A., & Dhillon, S. (2020). Gastrointestinal pathophysiology of SARS-CoV2 - a literature review. Journal of Community Hospital Internal Medicine Perspectives, 10(6), 523–528. https://doi.org/10.1080/20009666.2020.1811556
   PubMed Web of Science ®Google Scholar
• Turner, P. J. (2005). XMGRACE, Version 5.1. 19. Center for Coastal and Land-Margin Research, Oregon Graduate Institute of Science and Technology.
   Google Scholar
• Valdés-Tresanco, M. S., Valdés-Tresanco, M. E., Valiente, P. A., & Moreno, E. (2021). gmx_MMPBSA: A new tool to perform end-state free energy calculations with GROMACS. Journal of Chemical Theory and Computation, 17(10), 6281–6291. https://doi.org/10.1021/acs.jctc.1c00645
   PubMed Web of Science ®Google Scholar
• Wei, W., Cherukupalli, S., Jing, L., Liu, X., & Zhan, P. (2020). Fsp3: A new parameter for drug-likeness. Drug Discovery Today, 25(10), 1839–1845. https://doi.org/10.1016/j.drudis.2020.07.017
   PubMed Web of Science ®Google Scholar
• Xiong, G., Wu, Z., Yi, J., Fu, L., Yang, Z., Hsieh, C., Yin, M., Zeng, X., Wu, C., Lu, A., Chen, X., Hou, T., & Cao, D. (2021). ADMETlab 2.0: An integrated online platform for accurate and comprehensive predictions of ADMET properties. Nucleic Acids Research, 49(W1), W5–W14. https://doi.org/10.1093/nar/gkab255
   PubMed Web of Science ®Google Scholar
• Zaremba, A. A., Zaremba, P. Y., Muchnyk, F. V., Baranova, G. V., & Zahorodnia, S. D. (2022). In silico identification of a viral surface glycoprotein site suitable for the development of low molecular weight inhibitors for various variants of the SARS-CoV-2. Mikrobiolohichnyi Zhurnal, 84(1), 39–48. https://doi.org/10.15407/microbiolj84.01.034
   Google Scholar