Network Re-Wiring During Allostery and Protein-Protein Interactions: A Graph Spectral Approach

Gadiyaram, Vasundhara; Dighe, Anasuya; Ghosh, Sambit; Vishveshwara, Saraswathi

doi:10.1007/978-1-0716-1154-8_7

Cited by 8 publications

(6 citation statements)

References 42 publications

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“…In this case, the network analysis methods “translate” protein structures to the “graph language” that, when compared between different states, is believed to better describe the allosteric regulation. A typical example is the comparison of the partition of communities (or parameters defined based on the partition) between two networks. , One opinion suggests that the “translation” into communities can help get global changes from subtle changes of the conformation . We argue that this statement is overly optimistic and neglects the alternative possibility that the “translation” may amplify errors.…”

Section: Computational Methods For Mapping Allosteric Communication P...mentioning

confidence: 99%

“…A typical example is the comparison of the partition of communities (or parameters defined based on the partition) between two networks. 38,39 One opinion suggests that the "translation" into communities can help get global changes from subtle changes of the conformation. 39 We argue that this statement is overly optimistic and neglects the alternative possibility that the "translation" may amplify errors.…”

Section: Computational Methods For Mappingmentioning

confidence: 99%

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From Distinct to Differential Conformational Dynamics to Map Allosteric Communication Pathways in Proteins

Yao

Hamelberg

2022

J. Phys. Chem. B

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Initiation of biological processes involving protein–ligand binding, transient protein–protein interactions, or amino acid modifications alters the conformational dynamics of proteins. Accompanying these biological processes are ensuing coupled atomic level conformational changes within the proteins. These conformational changes collectively connect multiple amino acid residues at distal allosteric, binding, and/or active sites. Local changes due to, for example, binding of a regulatory ligand at an allosteric site initiate the allosteric regulation. The allosteric signal propagates throughout the protein structure, causing changes at distal sites, activating, deactivating, or modifying the function of the protein. Hence, dynamical responses within protein structures to stimuli contain critical information on protein function. In this Perspective, we examine the description of allosteric regulation from protein dynamical responses and associated alternative and emerging computational approaches to map allosteric communication pathways between distal sites in proteins at the atomic level.

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Section: Computational Methods For Mapping Allosteric Communication P...mentioning

confidence: 99%

Section: Computational Methods For Mappingmentioning

confidence: 99%

From Distinct to Differential Conformational Dynamics to Map Allosteric Communication Pathways in Proteins

Yao

Hamelberg

2022

J. Phys. Chem. B

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Section: Information Fluxes Across Networkmentioning

confidence: 99%

“…In PCNs, the shortest paths passing by the network edges mediate concerted motions and energy transmission upon stimulation of allosteric site ( Di Paola and Giuliani, 2015 ; Gadiyaram et al, 2021 ). The topological metrics of shortest paths (minimum number of links separating two residues) is thus the actual metrics for signaling ( Gadiyaram et al, 2021 ). The discrimination between relevant signals to be transmitted at distance without loss of information and non-informative perturbations to be dissipated without relevant changes in the 3D structure, relies upon two very important mesoscopic network descriptors: “Guimera and Amaral’ z and P indexes ( Guimera and Nunes Amaral, 2005 ).…”

Section: Information Fluxes Across Networkmentioning

confidence: 99%

Networks of Networks: An Essay on Multi-Level Biological Organization

Uversky

Giuliani

2021

Front. Genet.

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The multi-level organization of nature is self-evident: proteins do interact among them to give rise to an organized metabolism, while in the same time each protein (a single node of such interaction network) is itself a network of interacting amino-acid residues allowing coordinated motion of the macromolecule and systemic effect as allosteric behavior. Similar pictures can be drawn for structure and function of cells, organs, tissues, and ecological systems. The majority of biologists are used to think that causally relevant events originate from the lower level (the molecular one) in the form of perturbations, that “climb up” the hierarchy reaching the ultimate layer of macroscopic behavior (e.g., causing a specific disease). Such causative model, stemming from the usual genotype-phenotype distinction, is not the only one. As a matter of fact, one can observe top-down, bottom-up, as well as middle-out perturbation/control trajectories. The recent complex network studies allow to go further the pure qualitative observation of the existence of both non-linear and non-bottom-up processes and to uncover the deep nature of multi-level organization. Here, taking as paradigm protein structural and interaction networks, we review some of the most relevant results dealing with between networks communication shedding light on the basic principles of complex system control and dynamics and offering a more realistic frame of causation in biology.

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“…Graph Spectral Studies on Beta-2 Adrenergic Receptor. Here we focus on elucidating the spectral features 44 of ligand-induced conformational changes at side-chain levels on G-protein+ agonist (POG) bound (β 2 AR), an active conformation (PDB ID: 3SN6, hereafter referred to as β 2 AR-G s ) 42 and antagonist alprenolol-bound inactive state of β 2 AR, (PDB ID: 3NYA, hereafter referred to as β 2 AR-anta). 43 The spectral decomposition of the Laplacian of weighted side-chain networks were carried out and the Fiedler vectors revealed the difference in clustering profiles of both the systems.…”

Section: Journal Of Chemical Information and Modelingmentioning

confidence: 99%

From Quantum Chemistry to Networks in Biology: A Graph Spectral Approach to Protein Structure Analyses

Gadiyaram

Vishveshwara

2019

J. Chem. Inf. Model.

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In this perspective article, we present a multidisciplinary approach for characterizing protein structure networks. We first place our approach in its historical context and describe the manner in which it synthesizes concepts from quantum chemistry, biology of polymer conformations, matrix mathematics, and percolation theory. We then explicitly provide the method for constructing the protein structure network in terms of non-covalently interacting amino acid side chains and show how a mine of information can be obtained from the graph spectra of these networks. Employing suitable mathematical approaches, such as the use of a weighted, Laplacian matrix to generate the spectra, enables us to develop rigorous methods for network comparison and to identify crucial nodes responsible for the network integrity through a perturbation approach. Our scoring methods have several applications in structural biology that are elusive to conventional methods of analyses. Here, we discuss the instances of: (a) Protein structure comparison that include the details of side chain connectivity, (b) The contribution to node clustering as a function of bound ligand, explaining the global effect of local changes in phenomena such as allostery and (c) The identification of crucial amino acids for structural integrity, derived purely from the spectra of the graph. We demonstrate how our method enables us to obtain valuable information on key proteins involved in cellular functions and diseases such as GPCR and HIV protease, and discuss the biological implications. We then briefly describe how concepts from percolation theory further augment our analyses. In our concluding perspective for future developments, we suggest a further unifying approach to protein structure analyses and a judicious choice of questions to employ our methods for larger, more complex networks, such as metabolic and disease networks.

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Network Re-Wiring During Allostery and Protein-Protein Interactions: A Graph Spectral Approach

Cited by 8 publications

References 42 publications

From Distinct to Differential Conformational Dynamics to Map Allosteric Communication Pathways in Proteins

From Distinct to Differential Conformational Dynamics to Map Allosteric Communication Pathways in Proteins

Networks of Networks: An Essay on Multi-Level Biological Organization

From Quantum Chemistry to Networks in Biology: A Graph Spectral Approach to Protein Structure Analyses

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