Mapping of SARS-CoV-2 variants using cellular automaton imaging

0
  • John Hopkins University. John Hopkins Coronavirus Resource Center (2021). Available online: https://coronavirus.jhu.edu/map.html. Accessed September 4, 2021.

  • Tooz, A. Shutdown – How Covid shook the global economy (Penguin Random House, 2021).

    Google Scholar

  • World Health Organization. WHO Timeline-COVID-19. https://www.who.int/emergencies/diseases/novel-coronavirus-2019/interactive-timeline?gclid=CjwKCAiA7dKMBhBCEiwAO_crFAhknuq4kc_PZRW1qx3v_bMHTvAmmEewQ2vyKtZ47HyUy7DLGlZxoCkC4QAvD_BwE#event-115 (2020). Accessed November 17, 2021.

  • Machhi, J. et al. The natural history, pathobiology, and clinical manifestations of SARS-CoV-2 infection. J. Neuroimmune Pharmacol. fifteen, 359-386. https://doi.org/10.1007/s11481-020-09944-5 (2020).

    Article PubMed PubMed CentralGoogle Scholar

  • gene bank. National Center for Information on Biotechnology (2021).

  • UniProt. The Universal Protein Resource (2021).

  • Chen, C., Huang, H. & Wu, CH Databases and resources for protein bioinformatics. Methods Mol. biol. 1558, 3-39. https://doi.org/10.1007/978-1-4939-6783-4_1 (2017).

    CAS article PubMed PubMed Central Google Scholar

  • NIH – National Library of Medicine. NCBI SARs-CoV-2 Resources (2021).

  • Wu, F et al. A new coronavirus linked to human respiratory disease in China. Nature 579, 1–8. https://doi.org/10.1038/s41586-020-2008-3 (2020).

    CAS article Google Scholar

  • Khan, MT et al. Structures of SARS-CoV-2 RNA-binding proteins and therapeutic targets. intervirology 64, 1–14. https://doi.org/10.1159/000513686 (2021).

    CAS article Google Scholar

  • Chou, KC, Wei, DQ & Zhong, WZ Binding mechanism of the major coronavirus proteinase with ligands and its implications for drug design against SARS. biochem. biophys. Resolution Municipal. 308, 148-151. https://doi.org/10.1016/S0006-291X(03)01342-1 (2003).

    CAS article PubMed PubMed Central Google Scholar

  • Chou, KC, Wei, DQ, Du, QS, Sirois, S. & Zhong, WZ Advances in the computational approach to drug development against SARS. act. Med. Chem. 13, 3263-3670. https://doi.org/10.2174/092986706778773077 (2006).

    CAS article PubMed Google Scholar

  • Moret, MA & Zebende, GF Amino acid hydrophobicity and accessible surface. physics Rev. E Stat. Nonlinear Soft Matter Phys. 75011920. https://doi.org/10.1103/PhysRevE.75.011920 (2007).

    ADS-CAS Article Google Scholar

  • Phillips, JC Scaling and Self-Assembled Criticality in Proteins I. Proc. Natl. Academic Science. 106, 3107-3112. https://doi.org/10.1073/pnas.0811262106 (2009).

    ADS article PubMed PubMed Central Google Scholar

  • Phillips, JC Synchronized binding and the Darwinian evolution of the CoV-1 and CoV-2 coronaviruses. Physics A Stat. mechanical appl. 581126202. https://doi.org/10.1016/j.physa.2021.126202 (2021).

    MathSciNet CAS article Google Scholar

  • Li, S., Cai, C., Gong, J., Liu, X. & Li, H. A rapid protein binding site comparison algorithm for proteome-wide prediction of protein function and drug repurposing. proteins structure. funct. bioinform. 89, 1541–1556. https://doi.org/10.1002/prot.26176 (2021).

    CAS article Google Scholar

  • Moret, MA, Miranda, JGV, Nogueira, E., Santana, MC & Zebende, GF Self-similarity and protein chains. physics Rev. E Stat. Nonlinear Soft Matter Phys. 71012901. https://doi.org/10.1103/PhysRevE.71.012901 (2005).

    CAS article Google Scholar

  • Moret, MA, Santana, MC, Nogueira, E. & Zebende, GF Protein chain packing and percolation threshold. Physics A Stat. mechanical appl. 361250-254 (2006).

    ADS-CAS Article Google Scholar

  • Moret, MA Self-Assembled Critical Model for Protein Folding. Physics A Stat. mechanical appl. 390, 3055-3059. https://doi.org/10.1016/j.physa.2011.04.008 (2011).

    ADS-CAS Article Google Scholar

  • Xu, XL, Shi, JX, Wang, J. & Li, W. Long-distance correlation and critical fluctuations in coevolution networks of protein sequences. Physics A Stat. mechanical appl. 562125339. https://doi.org/10.1016/j.physa.2020.125339 (2021).

    CAS article Google Scholar

  • Nelson, ED & Onuchic, JN Proposed mechanism for the stability of proteins to evolutionary mutations. Proc. Natl. Academic Science. 95, 10682-10686. https://doi.org/10.1073/pnas.95.18.10682 (1998).

    ADS CAS article PubMed PubMed Central Google Scholar

  • Toffoli, T. & Margolus, N. Cellular Automata: A New Environment for Modeling (MIT Press in Scientific Computation, 1987).

    Book Google Scholar

  • Sleit, A. & Madain, A. Protein folding in the two-dimensional hydrophobic polar model based on cellular automata and local rules. international J. Computer. network Info. Sure. 1648 (2016).

    Google Scholar

  • Varela, D. & Santos, J. Protein folding modeling with neural cellular automata using Rosetta. In GECCO ’16 Companion: Proceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion, GECCO ’16 Companion, 1307-1312 (Association for Computing Machinery, 2016).

  • Varela, D. & Santos, J. Protein folding modeling with neural cellular automata using the face-centered cubic model (2017). Published in IWINAC, June 19, 2017.

  • Varela, D. & Santos, J. Automatically obtaining a cellular automaton schema for modeling protein folding using the FCC model. nat. Calculation.https://doi.org/10.1007/s11047-018-9705-y (2019).

    MathSciNet Article Google Scholar

  • Wolfram, S. Cellular Automata as Complexity Models. Nature 311419-424 (1984).

    ADS article Google Scholar

  • Xiao, X. & Chou, K. Digital coding of amino acids based on the hydrophobic index. Protein Pept. Latvian. 14871-5 (2007).

    CAS article Google Scholar

  • Xiao, X., Wang, P. & Chou, KC Prediction of protein structure classes with pseudoamino acid composition: An approach using geometric moments of the cellular automaton picture. J. Theor. biol. 254, 691-6. https://doi.org/10.1016/j.jtbi.2008.06.016 (2008).

    ADS MathSciNet CAS article PubMed MATH Google Scholar

  • Kavianpour, H. & Vasighi, M. Structural classification of proteins using texture descriptors extracted from the cellular automaton image. amino acids 49, 261-271. https://doi.org/10.1007/s00726-016-2354-5 (2017).

    CAS article PubMed Google Scholar

  • Wang, M et al. A new nucleotide composition-based fingerprint of SARS-CoV with visualization analysis. Med. Chem.https://doi.org/10.2174/1573406053402505 (2005).

    Article PubMedGoogle Scholar

  • Gabler, F. et al. Protein sequence analysis using the MPI bioinformatics toolkit. act. Protocol Bioinform. 72, e108. https://doi.org/10.1002/cpbi.108 (2020).

    CAS article Google Scholar

  • Ghosh, S. & Chaudhuri, PP Cellular automaton model for proteomics and its application in cancer immunotherapy. in the Cellular Automata. ACRI 2018. Lecture Notes in Computer Science3-15 (Springer International Publishing, 2018).

  • Xiao, X., Shao, S., Ding, Y. & Chen, X. Digital coding for amino acids based on cellular automata. in the 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No. 04CH37583)Vol. 5, 4593-4598, https://doi.org/10.1109/ICSMC.2004.1401256 (2004).

  • Phillips, JC, Moret, MA, Zebende, GF & Chow, CC Phase transitions may explain why SARS-CoV-2 spreads so quickly and why new variants spread faster. Physics A 598127318. https://doi.org/10.1016/j.physa.2022.127318 (2022).

    CAS article PubMed PubMed Central Google Scholar

  • Xiao, X et al. Use of cellular automata to generate imaging representations of biological sequences. amino acids 28, 29-35. https://doi.org/10.1007/s00726-004-0154-9 (2005).

    CAS article PubMed PubMed Central Google Scholar

  • Hamming, RW Error Detection and Correction Codes. bell syst. Technology. J 29, 147-160. https://doi.org/10.1002/j.1538-7305.1950.tb00463.x (1950).

    MathSciNet article MATH Google Scholar

  • Mullen, JL et al. Outbreak. Information (2021). Accessed December 17, 2021.

  • European Center for Disease Prevention and Control. Effects of the emergence and spread of SARS-CoV-2 b.1.1. 529 Variant of Concern (Omicron) for EU/EEA. https://www.ecdc.europa.eu/en/publications-data/threat-assessment-brief-emergence-sars-cov-2-variant-b.1.1.529 (2021). Accessed December 17, 2021.

  • World Health Organization. Improving Readiness for Omicron (b.1.1.529): Technical Brief and Priority Actions for Member States. https://www.who.int/publications/m/item/enhancing-readiness-for-omicron-(b.1.1.529)-technical-brief-and-priority-actions-for-member-states (2021) . Accessed December 17, 2021.

  • Wu, ZC, Xiao, X. & Chou, KC 2D-MH: A web server for generating a graphical representation of protein sequences based on the physicochemical properties of their constituent amino acids. J. Theor. biol. 267, 29-34. https://doi.org/10.1016/j.jtbi.2010.08.007 (2010).

    ADS MathSciNet CAS article PubMed MATH Google Scholar

  • Rahman, MM, Biswas, BA & Bhuiyan, MI H. Protein similarity analysis by wavelet decomposition of cellular automata images. in the 2019 International Conference on Electrical, Computer and Communications Engineering (ECCE)1-6 (IEEE, 2019).

  • Saitou, N. & Nei, M. The neighbor joining method: A new method for reconstructing phylogenetic trees. Mol. biol. development 4, 406-442. https://doi.org/10.1093/oxfordjournals.molbev.a040454 (1987).

    CAS article PubMed Google Scholar

  • Edelman, GM & Gally, JA Degeneration and complexity in biological systems. Proc. Natl. Academic Science. 98, 13763-13768. https://doi.org/10.1073/pnas.231499798 (2001).

    ADS CAS article PubMed PubMed Central Google Scholar

  • Share.

    Comments are closed.