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Research Articles

PheroxyPyrabenz and Carbopyrropyridin against major proteins of SARS CoV-2: a comprehensive in-silico molecular docking and dynamics simulation studies

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Pages 9121-9133 | Received 08 Aug 2022, Accepted 19 Oct 2022, Published online: 01 Nov 2022

References

  • Ahmad, S., Bano, N., Qazi, S., Yadav, M. K., Ahmad, N., & Raza, K. (2022a). Multitargeted molecular dynamic understanding of butoxypheser against SARS-CoV-2: An in silico study. Natural Product Communications, 17(7), 1934578X2211154. https://doi.org/10.1177/1934578X221115499
  • Ahmad, S., Chitkara, P., Khan, F. N., Kishan, A., Alok, V., Ramlal, A., & Mehta, S. (2021). Mobile technology solution for COVID-19: Surveillance and prevention, in Computational intelligence methods in COVID-19: Surveillance, prevention, prediction and diagnosis (pp. 79–108). Springer.
  • Ahmad, S., et al. (2022b). Molecular dynamics simulation and docking analysis of NF-κB protein binding with sulindac acid. Bioinformation, 18(3), 170–179. https://doi.org/10.6026/97320630018170
  • Ahmad, S., Pasha Km, M., Raza, K., Rafeeq, M. M., Habib, A. H., Eswaran, M., & Yadav, M. K. (2022c). Reporting dinaciclib and theodrenaline as a multitargeted inhibitor against SARS-CoV-2: An in-silico study. Journal of Biomolecular Structure and Dynamics, 1–11. https://doi.org/10.1080/07391102.2022.2060308
  • Alghamdi, Y. S., Mashraqi, M. M., Alzamami, A., Alturki, N. A., Ahmad, S., Alharthi, A. A., Alshamrani, S., & Asiri, S. A. (2022). Unveiling the multitargeted potential of N-(4-Aminobutanoyl)-S-(4-methoxybenzyl)-L-cysteinylglycine (NSL-CG) against SARS CoV-2: A virtual screening and molecular dynamics simulation study. Journal of Biomolecular Structure and Dynamics, 1–10. https://doi.org/10.1080/07391102.2022.2110158
  • Alturki, N. A., Mashraqi, M. M., Alzamami, A., Alghamdi, Y. S., Alharthi, A. A., Asiri, S. A., Ahmad, S., & Alshamrani, S. (2022). In-silico screening and molecular dynamics simulation of drug bank experimental compounds against SARS-CoV-2. Molecules, 27(14), 4391. https://doi.org/10.3390/molecules27144391
  • Alzamami, A., Alturki, N. A., Alghamdi, Y. S., Ahmad, S., Alshamrani, S., Asiri, S. A., & Mashraqi, M. M. (2022). Hemi-babim and fenoterol as potential inhibitors of MPro and papain-like protease against SARS-CoV-2: An in-silico study. Medicina, 58(4), 515. https://doi.org/10.3390/medicina58040515
  • Amanat, F., & Krammer, F. (2020). SARS-CoV-2 vaccines: Status report. Immunity, 52(4), 583–589. https://doi.org/10.1016/j.immuni.2020.03.007
  • Barh, D., et al. (2022). SARS-CoV-2 variants show a gradual declining pathogenicity and pro-inflammatory cytokine stimulation and an increasing antigenic and anti-inflammatory cytokine induction. bioRxiv.
  • Biodesign, A. (2022). Retrieved April 05, from http://www.asinex.com
  • Bowers, K. J., et al. (2006). Scalable algorithms for molecular dynamics simulations on commodity clusters. SC'06: Proceedings of the 2006 ACM/IEEE Conference on Supercomputing. IEEE.
  • Chen, X., Li, H., Tian, L., Li, Q., Luo, J., & Zhang, Y. (2020). Analysis of the physicochemical properties of acaricides based on Lipinski’s rule of five. Journal of Computational Biology, 27(9), 1397–1406. https://doi.org/10.1089/cmb.2019.0323
  • Echeverría-Esnal, D., Martin-Ontiyuelo, C., Navarrete-Rouco, M. E., De-Antonio Cuscó, M., Ferrández, O., Horcajada, J. P., & Grau, S. (2021). Azithromycin in the treatment of COVID-19: A review. Expert Review of Anti-Infective Therapy, 19(2), 147–163. https://doi.org/10.1080/14787210.2020.1813024
  • Gao, Y., Yan, L., Huang, Y., Liu, F., Zhao, Y., Cao, L., Wang, T., Sun, Q., Ming, Z., Zhang, L., Ge, J., Zheng, L., Zhang, Y., Wang, H., Zhu, Y., Zhu, C., Hu, T., Hua, T., Zhang, B., … Rao, Z. (2020). Structure of the RNA-dependent RNA polymerase from COVID-19 virus. Science (New York, N.Y.), 368(6492), 779–782. https://doi.org/10.1126/science.abb7498
  • Genheden, S., & Ryde, U. (2015). The MM/PBSA and MM/GBSA methods to estimate ligand-binding affinities. Expert Opinion on Drug Discovery, 10(5), 449–461. https://doi.org/10.1517/17460441.2015.1032936
  • Hou, J., Bhat, A. M., Ahmad, S., Raza, K., & Qazi, S. (2022). In silico analysis of ACE2 receptor to find potential herbal drugs in COVID-19 associated neurological dysfunctions. Natural Product Communications, 17(8), 1934578X2211185. https://doi.org/10.1177/1934578X221118549
  • Hunter, J. D. (2007). Matplotlib: A 2D graphics environment. Computing in Science & Engineering, 9(3), 90–95. https://doi.org/10.1109/MCSE.2007.55
  • Ioakimidis, L., Thoukydidis, L., Mirza, A., Naeem, S., & Reynisson, J. (2008). Benchmarking the reliability of QikProp. Correlation between experimental and predicted values. QSAR & Combinatorial Science, 27(4), 445–456. https://doi.org/10.1002/qsar.200730051
  • Jacobson, M. P., Pincus, D. L., Rapp, C. S., Day, T. J. F., Honig, B., Shaw, D. E., & Friesner, R. A. (2004). A hierarchical approach to all‐atom protein loop prediction. Proteins, 55(2), 351–367. https://doi.org/10.1002/prot.10613
  • Jin, Z., Du, X., Xu, Y., Deng, Y., Liu, M., Zhao, Y., Zhang, B., Li, X., Zhang, L., Peng, C., Duan, Y., Yu, J., Wang, L., Yang, K., Liu, F., Jiang, R., Yang, X., You, T., Liu, X., … Yang, H. (2020). Structure of Mpro from SARS-CoV-2 and discovery of its inhibitors. Nature, 582(7811), 289–293. https://doi.org/10.1038/s41586-020-2223-y
  • Karwasra, R., Ahmad, S., Bano, N., Qazi, S., Raza, K., Singh, S., & Varma, S. (2022a). Macrophage-targeted punicalagin nanoengineering to alleviate Methotrexate-Induced Neutropenia: A molecular docking, DFT, and MD simulation analysis. Molecules, 27(18), 6034. https://doi.org/10.3390/molecules27186034
  • Karwasra, R., et al. (2022b). The incipient role of computational intelligence in oncology: Drug designing, discovery, and development, in computational intelligence in oncology (pp. 369–384). Springer.
  • Kaul, T., Eswaran, M., Ahmad, S., Thangaraj, A., Jain, R., Kaul, R., Raman, N. M., & Bharti, J. (2020). Probing the effect of a plus 1bp frameshift mutation in protein-DNA interface of domestication gene, NAMB1, in wheat. Journal of Biomolecular Structure & Dynamics, 38(12), 3633–3647. https://doi.org/10.1080/07391102.2019.1680435
  • Khan, F. N., et al. (2021). A review on predictive systems and data models for covid-19. In Computational intelligence methods in COVID-19: Surveillance, prevention, prediction and diagnosis (pp. 123–164). Springer.
  • Khuntia, B. K., Sharma, V., Wadhawan, M., Chhabra, V., Kidambi, B., Rathore, S., Agarwal, A., Ram, A., Qazi, S., Ahmad, S., Raza, K., & Sharma, G. (2022). Antiviral potential of Indian medicinal plants against influenza and SARS-CoV: A systematic review. Natural Product Communications, 17(3), 1934578X2210869. https://doi.org/10.1177/1934578X221086988
  • Kim, Y., Jedrzejczak, R., Maltseva, N. I., Wilamowski, M., Endres, M., Godzik, A., Michalska, K., & Joachimiak, A. (2020). Crystal structure of Nsp15 endoribonuclease NendoU from SARS‐CoV‐2. Protein Science, 29(7), 1596–1605. https://doi.org/10.1002/pro.3873
  • Krammer, F. (2020). SARS-CoV-2 vaccines in development. Nature, 586(7830), 516–527. https://doi.org/10.1038/s41586-020-2798-3
  • Lagzian, M., Qasemi, A., Kaviani, P., & Mohammadi, M. (2019). Identification of new promising plant-based lead compounds for inhibition of prokaryotic replicative DNA polymerases: Combination of in silico and in vitro studies. Journal of Biomolecular Structure and Dynamics, 37(16), 4222–4237. https://doi.org/10.1080/07391102.2018.1545701
  • Lu, C., Wu, C., Ghoreishi, D., Chen, W., Wang, L., Damm, W., Ross, G. A., Dahlgren, M. K., Russell, E., Von Bargen, C. D., Abel, R., Friesner, R. A., & Harder, E. D. (2021). OPLS4: Improving force field accuracy on challenging regimes of chemical space. Journal of Chemical Theory and Computation, 17(7), 4291–4300. https://doi.org/10.1021/acs.jctc.1c00302
  • Maestro, S. (2020). Maestro. Schrödinger, LLC.
  • Ntie-Kang, F. (2013). An in silico evaluation of the ADMET profile of the StreptomeDB database. SpringerPlus, 2(1), 1–11. https://doi.org/10.1186/2193-1801-2-353
  • Osipiuk, J., et al. (2020). The crystal structure of papain-like protease of SARS CoV-2. RCSB PDB, 10.
  • Pollastri, M. P. (2010). Overview on the Rule of Five. Current Protocols in Pharmacology, 49(1), 9–12. https://doi.org/10.1002/0471141755.ph0912s49
  • Python, W. (2021). Python. Python Releases for Windows, 24.
  • Ramlal, A., et al. (2021). From molecules to patients: The clinical applications of biological databases and electronic health records, in Translational bioinformatics in healthcare and medicine (pp. 107–125). Academic Press.
  • Schrödinger Release. (2017). 2: LigPrep. Schrödinger, LLC.
  • Schrödinger Release. (2021). 2: Glide. Schrödinger, LLC.
  • Shang, J., Ye, G., Shi, K., Wan, Y., Luo, C., Aihara, H., Geng, Q., Auerbach, A., & Li, F. (2020). Structural basis of receptor recognition by SARS-CoV-2. Nature, 581(7807), 221–224. https://doi.org/10.1038/s41586-020-2179-y
  • Shelley, J. C., Cholleti, A., Frye, L. L., Greenwood, J. R., Timlin, M. R., & Uchimaya, M. (2007). Epik: A software program for pK a prediction and protonation state generation for drug-like molecules. Journal of Computer-Aided Molecular Design, 21(12), 681–691. https://doi.org/10.1007/s10822-007-9133-z
  • Singh, D., & Yi, S. V. (2021). On the origin and evolution of SARS-CoV-2. Experimental & Molecular Medicine, 53(4), 537–547. https://doi.org/10.1038/s12276-021-00604-z
  • Tarique, M., Ahmad, S., Malik, A., Ahmad, I., Saeed, M., Almatroudi, A., Qadah, T., Murad, M. A., Mashraqi, M., Alam, Q., & Al-Saleh, Y. (2021). Novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) and other coronaviruses: A genome-wide comparative annotation and analysis. Molecular and Cellular Biochemistry, 476(5), 2203–2217. https://doi.org/10.1007/s11010-020-04027-8
  • Tripathi, M. K., et al. (2022). Fundamentals of molecular modeling in drug design. In Computer Aided Drug Design (CADD): From ligand-based methods to structure-based approaches (pp. 125–155). Elsevier.
  • Walters, W. P. (2012). Going further than Lipinski’s rule in drug design. Expert Opinion on Drug Discovery, 7(2), 99–107. https://doi.org/10.1517/17460441.2012.648612
  • Wang, H., Li, X., Li, T., Zhang, S., Wang, L., Wu, X., & Liu, J. (2020). The genetic sequence, origin, and diagnosis of SARS-CoV-2. European Journal of Clinical Microbiology & Infectious Diseases, 39(9), 1629–1635. https://doi.org/10.1007/s10096-020-03899-4
  • Yadav, M. K., Ahmad, S., Raza, K., Kumar, S., Eswaran, M., & Pasha Km, M. (2022). Predictive modeling and therapeutic repurposing of natural compounds against the receptor-binding domain of SARS-CoV-2. Journal of Biomolecular Structure and Dynamics, 1–13. https://doi.org/10.1080/07391102.2021.2021993
  • Zarin, D. A., Tse, T., Williams, R. J., Califf, R. M., & Ide, N. C. (2011). The ClinicalTrials.gov results database—update and key issues. The New England Journal of Medicine, 364(9), 852–860. https://doi.org/10.1056/NEJMsa1012065

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