Analysis of Amino Acids Network Based on Nucleotide of DNA
DOI:
https://doi.org/10.26713/cma.v14i2.2140Keywords:
Codon, Amino acids, Distance matrixAbstract
The sequence of amino acids in protein synthesis is determined by the order of monomers of DNA. A study on the physicochemical aspect of nucleotide of DNA gives us valuable characteristics related to amino acids and protein functions. We considered six different parameters for four nucleotide of DNA and weighing each of them we constructed a distance matrix for twenty amino acids and subsequently, an amino acids network. In this network, we looked into evolutionary pattern of amino acids based on nucleotide of DNA and how it plays significant roles in the function of protein stability and membrane proteins. Lastly, we investigate several centrality metrics and explored correlation coefficients to assess the network’s assortativity for a comparative analysis of amino acids. We have also examined the clustering coefficient, degree distribution, and skewness as network parameters.
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M. Aftabuddin and S. Kundu, AMINONET - a tool to construct and visualize amino acid networks, and to calculate topological parameters, Journal of Applied Crystallography 43 (2010), 367 – 369, DOI: 10.1107/S002188981000110X.
A. Akhtar and T. Ali, Analysis of unweighted amino acids network, International Scholarly Research Notices 2014 (2014), Article ID 350276, DOI: 10.1155/2014/350276.
T. Ali and C. Borah, Analysis of amino acids network based on mutation and base positions, Gene Reports 24 (2021), 101291, DOI: 10.1016/j.genrep.2021.101291.
T. Ali, A. Akhtar and N. Gohain, Analysis of amino acids network based on distance matrix, Physica A: Statistical Mechanics and its Applications 452 (2016), 69 – 78, DOI: 10.1016/j.physa.2016.01.074.
J. D. Bashford and P. D. Jarvis, The genetic code as a periodic table: algebraic aspects, Biosystems 57(3) (2000), 147 – 161, DOI: 10.1016/s0303-2647(00)00097-6.
P. K. Bora, P. Hazarika and A. K. Baruah, Distance based amino acids network analysis, Gene Reports 21 (100933), DOI: 10.1016/j.genrep.2020.100933.
B. Chakrabarty and N. Parekh, Graph centrality analysis of structural Ankyrin repeats, International Journal of Computer Information Systems and Industrial Management Applications 6 (2014), 305 – 314, URL: https://www.mirlabs.net/ijcisim/regular_papers_2014/IJCISIM_28.pdf.
S. Chang, X. Jiao, X.-Q. Gong, C.-H. Li, W.-Z. Chen and C.-X. Wang, Evolving model of amino acid networks, Physical Review E 77 (2008), 061920, DOI: 10.1103/PhysRevE.77.061920.
L. C. Freeman, Centrality in social networks conceptual clarification, Social Networks 1(3) (1978-1979), 215 – 239, DOI: 10.1016/0378-8733(78)90021-7.
P. Godfrey-Smith and S. Kim, Biological information, The Stanford Encyclopedia of Philosophy, Summer 2016 Edition, E. N. Zalta (editor), (2016), URL: https://plato.stanford.edu/archives/sum2016/entries/information-biological/.
D. Koschützki and F. Schreiber, Centrality analysis methods for biological networks and their application to gene regulatory networks, Gene Regulation and Systems Biology 2 (2008), 193 – 201, DOI: 10.4137/grsb.s702.
D. Koschützki and F. Schreiber, Comparison of centralities for biological networks, German Conference on Bioinformatics 2004 (GCB 2004), Gesellschaft für Informatik, Bonn, 199 – 206 (2004), URL: https://dl.gi.de/handle/20.500.12116/28667.
J. Lehmann, Physico-chemical constraints connected with the coding properties of the genetic system, Journal of Theoretical Biology 202(2) (2000), 129 – 144, DOI: 10.1006/jtbi.1999.1045.
L. Li, I. Vorobyov and T. W. Allen, The different interactions of lysine and arginine side chains with lipid membranes, Journal of Physical Chemistry B 117(40) (2013), 11906 – 11920, DOI: 10.1021/jp405418y.
R. Sanchez, Symmetric group of the genetic-code cubes. Effect of the genetic–code architecture on the evolutionary process, MATCH Communications in Mathematical and in Computer Chemistry 79(3) (2018), 527 – 560, URL: https://match.pmf.kg.ac.rs/electronic_versions/Match79/n3/match79n3_527-560.pdf.
R. Sanchez, E. Morgado and R. Grau, Gene algebra from a genetic code algebraic structure, Journal of Mathematical Biology 51 (2005), 431 – 457, DOI: 10.1007/s00285-005-0332-8.
R. Sanchez, E. Morgado and R. Grau, The genetic code boolean lattice, MATCH Communications in Mathematical and in Computer Chemistry 52 (2004), 29 – 46, URL: https://match.pmf.kg.ac.rs/electronic_versions/Match52/match52_29-46.pdf.
D. J. Watts and S. H. Strogatz, Collective dynamics of ‘small-world’ networks, Nature 393 (1998), 440 – 442, URL: https://www.nature.com/articles/30918.
W. Yan, J. Zhou, M. Sun, J. Chen, G. Hu and B. Shen, The construction of an amino acid network for understanding protein structure and function, Amino Acids 46 (2014), 1419 – 1439, DOI: 10.1007/s00726-014-1710-6.
W. Yan, M. Sun, G. Hu, J. Zhou, W. Zhang, J. Chen, B. Chen and B. Shen, Amino acid contact energy networks impact protein structure and evolution, Journal of Theoretical Biology 355 (2014), 95 – 104, DOI: 10.1016/j.jtbi.2014.03.032.
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