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74
The protein folding network
- J. Mol. Biol
, 2004
"... The conformation space of a 20 residue antiparallel b-sheet peptide, sampled by molecular dynamics simulations, is mapped to a network. Snapshots saved along the trajectory are grouped according to secondary structure into nodes of the network and the transitions between them are links. The conforma ..."
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Cited by 55 (10 self)
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The conformation space of a 20 residue antiparallel b-sheet peptide, sampled by molecular dynamics simulations, is mapped to a network. Snapshots saved along the trajectory are grouped according to secondary structure into nodes of the network and the transitions between them are links. The conformation space network describes the significant free energy minima and their dynamic connectivity without requiring arbitrarily chosen reaction coordinates. As previously found for the Internet and the World-Wide Web as well as for social and biological networks, the conformation space network is scale-free and contains highly connected hubs like the native state which is the most populated free energy basin. Furthermore, the native basin exhibits a hierarchical organization, which is not found for a random heteropolymer lacking a predominant free-energy minimum. The network topology is used to identify conformations in the folding transition state (TS) ensemble, and provides a basis for understanding the heterogeneity of the TS and denatured state ensemble as well as the existence of multiple pathways.
Structure and dynamics of molecular networks: A novel paradigm of drug discovery -- A . . .
- PHARMACOLOGY THERAPEUTICS
, 2013
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Network analysis of protein structures identifies functional residues
- J. Mol. Biol
, 2004
"... Identifying active site residues strictly from protein three-dimensional structure is a difficult task, especially for proteins that have few or no homologues. We transformed protein structures into residue interaction graphs (RIGs), where amino acid residues are graph nodes and their interactions w ..."
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Cited by 44 (0 self)
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Identifying active site residues strictly from protein three-dimensional structure is a difficult task, especially for proteins that have few or no homologues. We transformed protein structures into residue interaction graphs (RIGs), where amino acid residues are graph nodes and their interactions with each other are the graph edges. We found that active site, ligand-binding and evolutionary conserved residues, typically have high closeness values. Residues with high closeness values interact directly or by a few intermediates with all other residues of the protein. Combining closeness and surface accessibility identified active site residues in 70 % of 178 representative structures. Detailed structural analysis of specific enzymes also located other types of functional residues. These include the substrate binding sites of acetylcholinesterases and subtilisin, and the regions whose structural changes activate MAP kinase and glycogen phosphorylase. Our approach uses single protein structures, and does not rely on sequence conservation, comparison to other similar structures or any prior knowledge. Residue closeness is distinct from various sequence and structure measures and can thus complement them in identifying key protein residues. Closeness integrates the effect of the entire protein on single residues. Such natural structural design may be evolutionary maintained to preserve interaction redundancy and contribute to optimal setting of functional sites.
Small-world network approach to identify key residues in protein–protein interaction
- Proteins
, 2005
"... Small world network approach to identify key residues in protein folding ..."
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Cited by 35 (0 self)
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Small world network approach to identify key residues in protein folding
Disordered proteins and network disorder in network representations of protein structure, dynamics and function. Hypotheses and a comprehensive review
, 2012
"... Abstract: During the last decade, network approaches became a powerful tool to describe protein structure and dynamics. Here we review the links between disordered proteins and the associated networks, and describe the consequences of local, mesoscopic and global network disorder on changes in prote ..."
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Cited by 13 (4 self)
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Abstract: During the last decade, network approaches became a powerful tool to describe protein structure and dynamics. Here we review the links between disordered proteins and the associated networks, and describe the consequences of local, mesoscopic and global network disorder on changes in protein structure and dynamics. We introduce a new classification of protein networks into ‘cumulus-type’, i.e., those similar to puffy (white) clouds, and ‘stratus-type’, i.e., those similar to flat, dense (dark) low-lying clouds, and relate these network types to protein disorder dynamics and to differences in energy transmission processes. In the first class, there is limited overlap between the modules, which implies higher rigidity of the individual units; there the conformational changes can be described by an ‘energy transfer ’ mechanism. In the second class, the topology presents a compact structure with significant overlap between the modules; there the conformational changes can be described by ‘multi-trajectories’; that is, multiple highly populated pathways. We further propose that disordered protein regions evolved to help other protein segments reach ‘rarely visited ’ but functionally-related states. We also show the role of disorder in ‘spatial games ’ of amino acids; highlight the effects of intrinsically disordered proteins
Universality in protein residue networks
- Biophys. J
"... wo le ract ff v lmo net lex rks trog olog sponding to key residues were observed to play the role of Concerning the representation of proteins as networks, da nonredundant protein structures and have shown that the C in which the small-world concept is based, are not useful*Correspondence: ..."
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Cited by 7 (1 self)
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wo le ract ff v lmo net lex rks trog olog sponding to key residues were observed to play the role of Concerning the representation of proteins as networks, da nonredundant protein structures and have shown that the C in which the small-world concept is based, are not useful*Correspondence:
Graphlet Kernels for Prediction of Functional Residues in Protein Structures
"... In this study we introduce a novel graph‐based kernel method for annotating functional residues in protein structures. A structure is first modeled as a protein contact graph, where nodes correspond to residues and edges connect spatially neighboring residues. Each vertex in the protein contact grap ..."
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Cited by 7 (2 self)
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In this study we introduce a novel graph‐based kernel method for annotating functional residues in protein structures. A structure is first modeled as a protein contact graph, where nodes correspond to residues and edges connect spatially neighboring residues. Each vertex in the protein contact graph is then represented as a vector of counts of labeled non‐isomorphic subgraphs (called graph‐ lets), centered on the vertex of interest. A similarity measure between two vertices is expressed as the inner product of their respective count vectors and is used in a supervised learning framework to classify protein residues. We evaluated our method on two function prediction problems: identi‐ fication of catalytic residues in proteins, which is a well‐studied problem suitable for benchmark‐ ing, and a much less explored problem of predicting phosphorylation sites in protein structures. We compared the graphlet kernel approach against two alternative methods, a sequence‐based predic‐ tor and our implementation of the FEATURE framework. On both function prediction tasks the graphlet kernel performed favorably compared to the alternatives; however, the margin of differ‐ ence was considerably higher on the problem of phosphorylation site prediction. While there is both computational and experimental evidence that phosphorylation sites are preferentially posi‐
Allo-Network Drugs: Extension of the Allosteric Drug Concept to Protein- Protein Interaction and Signaling Networks
"... Abstract: Allosteric drugs are usually more specific and have fewer side effects than orthosteric drugs targeting the same protein. Here, we overview the current knowledge on allosteric signal transmission from the network point of view, and show that most intra-protein conformational changes may be ..."
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Cited by 4 (1 self)
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Abstract: Allosteric drugs are usually more specific and have fewer side effects than orthosteric drugs targeting the same protein. Here, we overview the current knowledge on allosteric signal transmission from the network point of view, and show that most intra-protein conformational changes may be dynamically transmitted across protein-protein interaction and signaling networks of the cell. Allo-network drugs influence the pharmacological target protein indirectly using specific inter-protein network pathways. We show that allo-network drugs may have a higher efficiency to change the networks of human cells than those of other organisms, and can be designed to have specific effects on cells in a diseased state. Finally, we summarize possible methods to identify allo-network drug targets and sites, which may develop to a promising new area of systems-based drug design.
Interaction energy based protein structure networks
- Biophys J 2010
"... ne rk b tein nvo ENs he he e spanning across a system), clusters, hubs, cliques, and in tracking changes in the dynamical properties from an a wealth of information can be extracted by incorporating energy networks (PENs)) with realistic edge-weights ob-from equilibrium ensembles (obtained using MD ..."
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Cited by 4 (0 self)
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ne rk b tein nvo ENs he he e spanning across a system), clusters, hubs, cliques, and in tracking changes in the dynamical properties from an a wealth of information can be extracted by incorporating energy networks (PENs)) with realistic edge-weights ob-from equilibrium ensembles (obtained using MD simula-tions) to account for the structural plasticity, crucial to
