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Applications of graph theory in studying protein structure, dynamics, and interactions

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Abstract

Being a core tool, graph theory, as a mathematical formalism in mathematical chemistry, has become an essential approach for studying the complex behavior and interactions in protein systems. Here, we review recent advances in the field, particularly in our group, including the methods developed to access protein functions and their applications in disease biology. First, we provide the necessary background and definitions of graph-based structures and network centralities, and methodologies developed at the node-, subgraph- and pathway-levels. We then review the applications of how to use these algorithms to gain new biological insights, ranging from protein structures to protein dynamics, and interactions for linking genotypes and phenotypes. Furthermore, we discuss immediate challenges in the multilayer network, which is more realistic in the biological world, and hope to draw increasing attention from mathematicians, especially graph theorists, to reveal the basic principles of “networks of networks”.

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Funding

This work was supported by the National Natural Science Foundation of China (32271292, 31872723), and a Project Funded by the Priority Academic Program Development (PAPD) of Jiangsu Higher Education Institutions.

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  1. Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou, 215123, China

    Ziyun Zhou & Guang Hu

  2. Jiangsu Province Engineering Research Center of Precision Diagnostics and Therapeutics Development, Soochow University, Suzhou, 215123, China

    Ziyun Zhou & Guang Hu

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ZZ and GH: wrote the main manuscript text and prepared all figures. Both authors reviewed the manuscript.

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Zhou, Z., Hu, G. Applications of graph theory in studying protein structure, dynamics, and interactions. J Math Chem (2023). https://doi.org/10.1007/s10910-023-01511-6

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