Connecting the dots: A practical evaluation of web-tools for describing protein dynamics as networks

Petrizzelli, Francesco; Biagini, Tommaso; Bianco, Salvatore Daniele; Liorni, Niccolò; Napoli, Alessandro; Castellana, Stefano; Mazza, Tommaso

doi:10.3389/fbinf.2022.1045368

Cited by 4 publications

(2 citation statements)

References 51 publications

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“…It is worth mentioning that residue interaction network can be created from various features such as residue contacts in a static structure, mutational effects on functional activity, amino acid sequence conservation, or conformational dynamics in different timescales (73)(74)(75)(76). Each of these approaches will reveal distinct network features associated with different functional properties.…”

Section: Discussionmentioning

confidence: 99%

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: Discussionmentioning

confidence: 99%

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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“…Structural ensemble analysis is one of the main applications of RING. It is commonly used to analyze molecular dynamics simulations by calculating probabilistic contact networks ( 12 , 13 ), and to analyze protein stability and perform virtual screening ( 14 , 15 ).…”

Section: Introductionmentioning

confidence: 99%

RING 4.0: faster residue interaction networks with novel interaction types across over 35,000 different chemical structures

Del Conte,

Camagni,

Clementel

et al. 2024

Nucleic Acids Research

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Residue interaction networks (RINs) are a valuable approach for representing contacts in protein structures. RINs have been widely used in various research areas, including the analysis of mutation effects, domain-domain communication, catalytic activity, and molecular dynamics simulations. The RING server is a powerful tool to calculate non-covalent molecular interactions based on geometrical parameters, providing high-quality and reliable results. Here, we introduce RING 4.0, which includes significant enhancements for identifying both covalent and non-covalent bonds in protein structures. It now encompasses seven different interaction types, with the addition of π-hydrogen, halogen bonds and metal ion coordination sites. The definitions of all available bond types have also been refined and RING can now process the complete PDB chemical component dictionary (over 35000 different molecules) which provides atom names and covalent connectivity information for all known ligands. Optimization of the software has improved execution time by an order of magnitude. The RING web server has been redesigned to provide a more engaging and interactive user experience, incorporating new visualization tools. Users can now visualize all types of interactions simultaneously in the structure viewer and network component. The web server, including extensive help and tutorials, is available from URL: https://ring.biocomputingup.it/.

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Bayesian network models identify cooperative GPCR:G protein interactions that contribute to G protein coupling

Mukhaleva,

Ma,

van der Velden

et al. 2024

Journal of Biological Chemistry

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Connecting the dots: A practical evaluation of web-tools for describing protein dynamics as networks

Cited by 4 publications

References 51 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

RING 4.0: faster residue interaction networks with novel interaction types across over 35,000 different chemical structures

Bayesian network models identify cooperative GPCR:G protein interactions that contribute to G protein coupling

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