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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Journal ArticleDOI
Structure-based function prediction: approaches and applications
TL;DR: This review will cover both kinds of approaches to structure-based function prediction as well as their use in real-world cases and the assessment of the statistical significance of structural similarities and the extent to which these methods depend on the accuracy and availability of structural data.
Journal ArticleDOI
A Chemical Perspective on Allostery.
André Ribeiro,Vanessa Ortiz +1 more
TL;DR: This review summarizes recent advances in the analysis of mechanisms of allosteric communication in proteins, and combines this new knowledge to offer a perspective of allostery which is consistent with chemical views of molecular processes.
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The emergence of protein complexes: quaternary structure, dynamics and allostery
Tina Perica,Joseph A. Marsh,Filipa L. Sousa,Eviatar Natan,Lucy J. Colwell,Sebastian E. Ahnert,Sarah A. Teichmann +6 more
TL;DR: This paper discusses how protein function and stability benefit from oligomerization, as well as evolutionary pathways by which oligomers emerge, mostly from the perspective of homomers, and two analytical approaches increasingly being used to study protein structures as wellAs their interactions.
Journal ArticleDOI
Computational identification of binding energy hot spots in protein-RNA complexes using an ensemble approach.
TL;DR: A computational method is described that can effectively detect hot spot residues on protein-RNA binding interfaces using an ensemble of conceptually different machine learning classifiers, and achieves promising performances in 10-fold cross-validation.
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Improved prediction of critical residues for protein function based on network and phylogenetic analyses.
TL;DR: It is shown that network analysis can be used to improve the prediction of amino acids critical for protein function, when utilized in combination with phylogenetic approaches, and it is proposed that such improvement is due to the complementary nature of these approaches.
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.