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Hosts a database of output files obtained from running Gaussian network model (GNM) calculations on Protein Data Bank (PDB) files and the means for visualizing these files in both 2-D and 3-D. iGNM 2.0 covers more than 95% of the structures currently available in the PDB. Advanced search and visualization capabilities, both 2D and 3D, permit users to retrieve information on inter-residue and inter-domain cross-correlations, cooperative modes of motion, the location of hinge sites and energy localization spots. The ability of iGNM 2.0 to provide structural dynamics data on the large majority of PDB structures and, in particular, on their biological assemblies makes it a useful resource for establishing the bridge between structure, dynamics and function.
Contains simulations of representatives of essentially all known protein folds. The database provides an organizing framework, a repository, and a variety of access interfaces for the simulation and analysis data. Simulations of fold representatives are organized by their CDD definition. The SNP targets are further organized around the amino acid replacements involved and their related diseases. Coordinate and analysis data are loaded into the database and linked to their respective consensus domains.
CoDNaS / Conformational Diversity of Native State
A collection of redundant crystallographic structures for a given protein extensively linked with structural, biological and physicochemical information. CoDNaS offers a well curated database that is experimentally driven, thoroughly linked, and annotated. CoDNaS facilitates the extraction of key information on small structural differences based on protein movements. CoDNaS enables users to easily relate the degree of conformational diversity with physical, chemical and biological properties derived from experiments on protein structure and biological characteristics. The new version of CoDNaS includes ∼70% of all available protein structures, and new tools have been added that run sequence searches, display structural flexibility profiles and allow users to browse the database for different structural classes. These tools facilitate the exploration of protein conformational diversity and its role in protein function.
Explores the intrinsic flexibility of protein structures by analyzing structural variations between different depositions and chains in asymmetric unit of the same protein in PDB. PDBFlex allows to easily identify regions and types of structural flexibility present in a protein of interest. Structures of protein chains with identical sequences (sequence identity > 95%) were aligned, superimposed and clustered. Then global and local structural differences were calculated within these clusters. The PDBFlex contains tools and viewers enabling in-depth examination of structural variability including: 2D-scaling visualization of RMSD distances between structures of the same protein, graphs of average local RMSD in the aligned structures of protein chains, graphical presentation of differences in secondary structure and observed structural disorder (unresolved residues), difference distance maps between all sets of coordinates and 3D views of individual structures and simulated transitions between different conformations, the latter displayed using JSMol visualization software.
A database of proteins showing conformational diversity. For each protein, the database contains the redundant compilation of all the corresponding crystallographic structures obtained under different conditions. These structures could be considered as different instances of protein dynamism. As a measure of the conformational diversity we use the maximum RMSD obtained comparing the structures deposited for each domain. The redundant structures were extracted following CATH structural classification and cross linked with additional information. In this way it is possible to relate a given amount of conformational diversity with different levels of information, such as protein function, presence of ligands and mutations, structural classification, active site information and organism taxonomy among others.
Allows the application of energy-based network theory to the analysis of molecular dynamics trajectories of proteins. MDN can be used to analyze output from simulations performed with the GROMACS and NAMD packages. It employs a method that assigns network edge weights based on the strength of energetic interaction between residues. It provides an interface that allows the user to upload all the necessary data, as well as define the groups of residues that are to be considered in the analysis.
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