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

Zhou, Ziyun; Hu, Guang

doi:10.1007/s10910-023-01511-6

Cited by 4 publications

(1 citation statement)

References 80 publications

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“…We also noted the high CB of NS1 are located at the interfaces between network communities, indicating their critical role in inter-community communications (Figs 6A and 6B) (63). Significantly, our NMR study showed that five of the top 10 high CB residues underwent significant changes in side-chain dynamics between 1918 and PR8 NS1s.…”

Section: Mutational Effects On Network Community Underpin Epistasis I...mentioning

confidence: 55%

Evolutionary rewiring of the dynamic network underpinning allosteric epistasis in NS1 of influenza A virus

Gonzales,

Kim,

Hwang

et al. 2024

Preprint

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Viral proteins frequently mutate to evade or antagonize host innate immune responses, yet the impact of these mutations on the molecular energy landscape remains unclear. Epistasis, the intramolecular communications between mutations, often renders the combined mutational effects unpredictable. Nonstructural protein 1 (NS1) is a major virulence factor of the influenza A virus (IAV) that activates host PI3K by binding to its p85β subunit. Here, we present the deep analysis for the impact of evolutionary mutations in NS1 that emerged between the 1918 pandemic IAV strain and its descendant PR8 strain. Our analysis reveal how the mutations rewired inter-residue communications which underlies long-range allosteric and epistatic networks in NS1. Our findings show that PR8 NS1 binds to p85β with approximately 10-fold greater affinity than 1918 NS1 due to allosteric mutational effects. Notably, these mutations also exhibited long-range epistatic effects. NMR chemical shift perturbation and methyl-axis order parameter analyses revealed that the mutations induced long-range structural and dynamic changes in PR8 NS1, enhancing its affinity to p85β. Complementary MD simulations and graph-based network analysis uncover how these mutations rewire dynamic residue interaction networks, which underlies the long-range epistasis and allosteric effects on p85β-binding affinity. Significantly, we find that conformational dynamics of residues with high betweenness centrality play a crucial role in communications between network communities and are highly conserved across influenza A virus evolution. These findings advance our mechanistic understanding of the allosteric and epistatic communications between distant residues and provides insight into their role in the molecular evolution of NS1.

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Section: Mutational Effects On Network Community Underpin Epistasis I...mentioning

confidence: 55%

Evolutionary rewiring of the dynamic network underpinning allosteric epistasis in NS1 of influenza A virus

Gonzales,

Kim,

Hwang

et al. 2024

Preprint

View full text Add to dashboard Cite

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Essential Protein Identification in Cancer: A Graph-Based Approach Integrating Topological and Biological Features in PPI Networks

Rout,

Mohapatra,

Kar

et al. 2024

SN COMPUT. SCI.

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Systems biology approaches to identify driver genes and drug combinations for treating COVID-19

Ebrahimi,

Roshani

2024

Sci Rep

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Corona virus 19 (Covid-19) has caused many problems in public health, economic, and even cultural and social fields since the beginning of the epidemic. However, in order to provide therapeutic solutions, many researches have been conducted and various omics data have been published. But there is still no early diagnosis method and comprehensive treatment solution. In this manuscript, by collecting important genes related to COVID-19 and using centrality and controllability analysis in PPI networks and signaling pathways related to the disease; hub and driver genes have been identified in the formation and progression of the disease. Next, by analyzing the expression data, the obtained genes have been evaluated. The results show that in addition to the significant difference in the expression of most of these genes, their expression correlation pattern is also different in the two groups of COVID-19 and control. Finally, based on the drug-gene interaction, drugs affecting the identified genes are presented in the form of a bipartite graph, which can be used as the potential drug combinations.

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

Cited by 4 publications

References 80 publications

Evolutionary rewiring of the dynamic network underpinning allosteric epistasis in NS1 of influenza A virus

Evolutionary rewiring of the dynamic network underpinning allosteric epistasis in NS1 of influenza A virus

Essential Protein Identification in Cancer: A Graph-Based Approach Integrating Topological and Biological Features in PPI Networks

Systems biology approaches to identify driver genes and drug combinations for treating COVID-19

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