Journal ArticleDOI
Network analysis of protein structures identifies functional residues.
Gil Amitai,Arye Shemesh,Einat Sitbon,Maxim Shklar,Dvir Netanely,Ilya Venger,Shmuel Pietrokovski +6 more
TLDR
This work 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, and found that active site, ligand-binding and evolutionary conserved residues, typically have high closeness values.About:
This article is published in Journal of Molecular Biology.The article was published on 2004-12-03. It has received 463 citations till now. The article focuses on the topics: Protein structure & Active site.read more
Citations
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Protein-water hydrogen-bond networks of G protein-coupled receptors: Graph-based analyses of static structures and molecular dynamics.
TL;DR: This work implemented here a set of graph-based algorithms, and applied these algorithms to static GPCR structures from structural biology, and from molecular dynamics simulations of two opioid receptors, finding that all static structures included in analyses have a core hydrogen-bond network which extends to comprise most of the interior of an inactive receptor.
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A graph-based approach identifies dynamic H-bond communication networks in spike protein S of SARS-CoV-2.
Konstantina Karathanou,Michalis Lazaratos,Éva Bertalan,Malte Siemers,Krzysztof Buzar,Gebhard F. X. Schertler,Coral del Val,Ana-Nicoleta Bondar +7 more
TL;DR: This work presents a methodology that relies upon graph and centrality analyses, augmented by bioinformatics, to identify and characterize large H-bond clusters in protein structures and finds that, in the closed conformation, the three protomers of protein S bring the same contribution to an extensive central network of H- bonds.
Journal ArticleDOI
CPred: a web server for predicting viable circular permutations in proteins
TL;DR: A comprehensive method for predicting viable CP cleavage sites in proteins is implemented into an efficient and user-friendly web server named CPred (CP site predictor), which is supposed to be helpful to promote fundamental researches and biotechnological applications of CP.
Journal ArticleDOI
Variation in structural location and amino acid conservation of functional sites in protein domain families
TL;DR: The analysis presented here has investigated the conservation of location and type of amino acids at functional sites, and compared the behaviour of functional sites between different protein domains.
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Structural models and binding site prediction of the C-terminal domain of human Hsp90: a new target for anticancer drugs.
TL;DR: This work investigated the structure and the dynamic behaviour of the C‐terminal domain of human heat shock protein 90 with and without the small‐middle domain, using homology modelling and molecular dynamics simulations and secondary structure predictions and peptide folding simulations.
References
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Collective dynamics of small-world networks
TL;DR: Simple models of networks that can be tuned through this middle ground: regular networks ‘rewired’ to introduce increasing amounts of disorder are explored, finding that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs.
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The Protein Data Bank
Helen M. Berman,John D. Westbrook,Zukang Feng,Gary L. Gilliland,Talapady N. Bhat,Helge Weissig,Ilya N. Shindyalov,Philip E. Bourne +7 more
TL;DR: The goals of the PDB are described, the systems in place for data deposition and access, how to obtain further information and plans for the future development of the resource are described.
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Emergence of Scaling in Random Networks
TL;DR: A model based on these two ingredients reproduces the observed stationary scale-free distributions, which indicates that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.
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Statistical mechanics of complex networks
TL;DR: In this paper, a simple model based on the power-law degree distribution of real networks was proposed, which was able to reproduce the power law degree distribution in real networks and to capture the evolution of networks, not just their static topology.
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Centrality in social networks conceptual clarification
TL;DR: In this article, three distinct intuitive notions of centrality are uncovered and existing measures are refined to embody these conceptions, and the implications of these measures for the experimental study of small groups are examined.