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Open AccessJournal ArticleDOI

NAPS: Network Analysis of Protein Structures.

TLDR
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.
Abstract
Traditionally, protein structures have been analysed by the secondary structure architecture and fold arrangement. An alternative approach that has shown promise is modelling proteins as a network of non-covalent interactions between amino acid residues. The network representation of proteins provide a systems approach to topological analysis of complex three-dimensional structures irrespective of secondary structure and fold type and provide insights into structure-function relationship. We have developed a web server for network based analysis of protein structures, NAPS, that facilitates quantitative and qualitative (visual) analysis of residue-residue interactions in: single chains, protein complex, modelled protein structures and trajectories (e.g. from molecular dynamics simulations). The user can specify atom type for network construction, distance range (in A) and minimal amino acid separation along the sequence. NAPS provides users selection of node(s) and its neighbourhood based on centrality measures, physicochemical properties of amino acids or cluster of well-connected residues (k-cliques) for further analysis. Visual analysis of interacting domains and protein chains, and shortest path lengths between pair of residues are additional features that aid in functional analysis. NAPS support various analyses and visualization views for identifying functional residues, provide insight into mechanisms of protein folding, domain-domain and protein-protein interactions for understanding communication within and between proteins. URL:http://bioinf.iiit.ac.in/NAPS/.

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The Bio3D packages for structural bioinformatics

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LARMD: integration of bioinformatic resources to profile ligand-driven protein dynamics with a case on the activation of estrogen receptor.

TL;DR: LARMD provides a user-friendly online protocol to study the dynamic property of protein and to design new ligand or site-directed mutagenesis, which plays a vital role in the treatment of inflammatory diseases and many types of cancers in clinical practice.
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Visualization and analysis of non-covalent contacts using the Protein Contacts Atlas

TL;DR: This work developed multiple representations for visualization and analysis of non-covalent contacts at different scales of organization: atoms, residues, secondary structure, subunits, and entire complexes from over 100,000 PDB crystal structures.
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Systems Bioinformatics: increasing precision of computational diagnostics and therapeutics through network-based approaches.

TL;DR: Evidence on how Systems Bioinformatics enhances computational therapeutics and diagnostics, hence paving the way to precision medicine is provided.
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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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Journal ArticleDOI

Network analysis of protein structures identifies functional residues.

TL;DR: 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.
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