Journal ArticleDOI
Aminonet-a tool to construct and visualize amino acid networks, and to calculate topological parameters
TLDR
AMINONET is a Java-based software tool to construct different protein contact networks (unweighted and weighted; long range, short range and any range; hydrophobic, hydrophilic, charged or all-amino-acid networks).Abstract:
AMINONET is a Java-based software tool to construct different protein contact networks (unweighted and weighted; long range, short range and any range; hydrophobic, hydrophilic, charged or all-amino-acid networks). The networks thus constructed can be visualized. The software will also help in the calculation of the values of the different topological parameters of the constructed networks. The user can either provide a PDB ID or upload a structure file in PDB format as input. If necessary, the user can also do the same for a large number of proteins, uploading a batch file as input (details described in the document available online).read more
Citations
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The self-assembly, aggregation and phase transitions of food protein systems in one, two and three dimensions
Raffaele Mezzenga,Peter Fischer +1 more
TL;DR: This review will tackle the current understanding of protein aggregation in the framework of foods, which is possibly one of the broadest contexts, yet is of tremendous daily relevance.
Journal ArticleDOI
NAPS: Network Analysis of Protein Structures.
Broto Chakrabarty,Nita Parekh +1 more
TL;DR: A web server for network based analysis of protein structures, NAPS, that facilitates quantitative and qualitative analysis of residue–residue interactions in single chains, protein complex, modelled protein structures and trajectories and provides insights into structure-function relationship.
Journal ArticleDOI
Role of long- and short-range hydrophobic, hydrophilic and charged residues contact network in protein's structural organization.
Dhriti Sengupta,Sudip Kundu +1 more
TL;DR: An extensive analysis of protein contact subnetworks based on the London van der Waals interactions of amino acids at different length scales is presented and is able to capture several known properties of protein structure as well as can unravel several new features.
Journal ArticleDOI
Inferring Ancestral Pueblo Social Networks from Simulation in the Central Mesa Verde
TL;DR: In this article, the authors use computer simulation to explore the extent to which food-sharing practices would have been instrumental for the survival of Ancestral Pueblo people across the patchy landscape of the Prehispanic American Southwest and suggest that we can see direct evidence of exchange through the aggregation of households into clustered settlements.
Journal ArticleDOI
The Topology and Dynamics of Protein Complexes: Insights from Intra– Molecular Network Theory
TL;DR: This work reviews the recent advances in the use of network theory to study the topology and dynamics of protein- ligand and protein-nucleic acid complexes and describes some web-based resources for protein complexes.
References
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Gil Amitai,Arye Shemesh,Einat Sitbon,Maxim Shklar,Dvir Netanely,Ilya Venger,Shmuel Pietrokovski +6 more
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Small-world view of the amino acids that play a key role in protein folding.
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Topological determinants of protein folding
TL;DR: A macroscopic measure of the protein contact network topology, the average graph connectivity, is used by constructing graphs that are based on the geometry of protein conformations and it is found that the average connectivity is higher for conformations with a high folding probability than for those with ahigh probability to unfold.
Journal ArticleDOI
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TL;DR: Recognising that proteins are networks provides a means of rationalising the robustness in the overall three-dimensional fold of a protein against random mutations and suggests an alternative avenue to investigate the determinants of protein structure, function and folding.
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Identification of side-chain clusters in protein structures by a graph spectral method.
TL;DR: A novel method to detect side-chain clusters in protein three-dimensional structures using a graph spectral approach and identify the residue which makes the largest number of interactions among the residues forming the cluster (cluster centers).