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Allows users to access and preprocess structural data for all kinds of life science research, and gives an immediate visual impression of the overall protein structure and contained ligand molecules. ProteinPlus contains a server for special interest to life scientists with an occasional need to work with protein structures thanks to six services addressing the most important tasks at the beginning of structure analysis (Protoss; PoseView; EDIA; SIENA; DoGSiteScorer; HyPPI). Users can choose an application service of interest, set additional tool configurations and start the calculation.
Identifies ligand binding sites on protein surface. metaPocket is a consensus method in which the predicted pocket sites from eight methods (LIGSITECS, PASS, Q-SiteFinder, SURFNET, Fpocket, GHECOM, ConCavity and POCASA) are combined together to improve the prediction success rate. Each of eight single methods is treated as a plug-in in metaPocket. This plug-in pattern makes the server automatically detect the failed methods and the algorithm is only applied to those results from successful methods.
LISE / Ligand Interacting Site Enriched
Predicts protein’s ligand-binding sites. LISE is a LBSP method derived from 3D motifs of protein–ligand interactions that achieves significantly better success rates, especially in predicting the top-ranked sites, than a number of previously reported methods on two benchmark datasets. Benchmark predictions using the same set of structural data and the same evaluation criteria showed that, in cases where comparisons were made, LISE outperforms other methods on the whole, often with a significantly better accuracy for the first predicted site.
A computational pipeline for functional annotation of proteins at the level of binding sites. PocketAnnotate integrates three in-house algorithms for site-based function annotation: (i) PocketDepth, for prediction of binding sites in protein structures; (ii) PocketMatch, for rapid comparison of binding sites and (iii) PocketAlign, to obtain detailed alignment between pair of binding sites. It would be a valuable tool for the scientific community and contribute towards structure-based functional inference.
SiMMap / Site-Moiety-Map
Provides analysis of Site-Moiety Map. The SiMMap server statistically derives site-moiety map with several anchors, which describe the relationship between the moiety preferences and physico-chemical properties of the binding site, from the interaction profiles between query target protein and its docked compounds. Each anchor includes three basic elements: (i) a binding pocket with conserved interacting residues, (ii) the moiety composition of query compounds, and (iii) pocket-moiety interaction type (electrostatic, hydrogen-bonding, or van der Waals).
Predicts pocket druggability, efficient on both; estimated pockets guided by the ligand proximity (extracted by proximity to a ligand from a holo protein structure using several thresholds) and estimated pockets not guided by the ligand proximity (based on amino atoms that form the surface of potential binding cavities). PockDrug-Server provides consistent druggability results using different pocket estimation methods. It is robust with respect to pocket boundary and estimation uncertainties, thus efficient using apo pockets that are challenging to estimate. It clearly distinguishes druggable from less druggable pockets using different estimation methods and outperformed recent druggability models for apo pockets.
Identifies and ranks subfamily-specific binding sites in proteins by functional significance. pocketZebra is a web-server that can be used to annotate functional and regulatory (allosteric) sites in protein families. It permits to design novel selective inhibitors/effectors. The server provides on-site visualization of the results as well as off-line version of the output in annotated text format and as PyMol sessions ready for structural analysis. It also can be used to study structure-function relationship and regulation in large protein superfamilies, classify functionally important binding sites and annotate proteins with unknown function.
TRAPP webserver
Studies the dynamics of a known binding pocket or any other protein cavity of interest, identifies and characterises transient sub-pockets. TRAPP webserver is an online method to provide the user with an automated workflow to invoke a toolbox of methods to explore pocket flexibility arising from protein conformational changes on a wide range of temporal and spatial scales. This web site offers a choice of several methods to efficiently generate conformational ensembles representing binding pocket dynamics, in addition to the option of uploading conformational ensembles, e.g., crystal structures or molecular dynamic (MD) trajectories, generated by other tools.
Implements a ligand-specific method for small ligand (including metal and acid radical ions) binding site prediction. Starting from given sequences or structures of the query proteins, IonCom performs a composite binding-site prediction that combines ab initio training and template-based transferals. To enhance specificity and sensitivity, the server focuses on binding site prediction of thirteen most important small ligand molecules, including nine metal ions (Zn2+, Cu2+, Fe2+, Fe3+, Ca2+, Mg2+, Mn2+, Na+, K+) and four acid radical ions (CO32-, NO2-, SO42-, PO43-). IonCom is freely available online or can be downloaded for local use.
LIBRA / LIgand Binding site Recognition Application
A software tool that, given a protein’s structural model, predicts the presence and identity of active sites and/or ligand binding sites. The algorithm implemented by LIBRA is based on a graph theory approach to find the largest subset of similar residues between an input protein and a collection of known functional sites. The algorithm makes use of two predefined databases for active sites and ligand binding sites, respectively derived from the Catalytic Site Atlas and the Protein Data Bank. Tests indicate that LIBRA is able to identify the correct binding/active site in ~90% of the cases analyzed, 90% of which feature the identified site as ranking first.
LIBRA-WA / Ligand Binding site Recognition Web Application
Allows users to predict active sites and/or ligand binding. LIBRA provides a platform able to perform ligand clustering and to determine binding sites hosted at the interface between different subunits. The application permits to manage multiple recognitions, three-dimensional alignments and ligand clusters from a personal account. Moreover, files generated by the program can be exported in LIBRA+'s format for further experiments.
A computational tool for predicting the location of cryptic binding sites in proteins and protein complexes. CryptoSite accurately localizes over 96% of cryptic binding sites, outperforming other computational methods. It increases the size of the potentially “druggable” human proteome from 40% to 78% of disease-associated proteins. This method can also be applied to low-resolution atomic structures and comparative models, in addition to high-resolution X-ray structures, without a large loss of accuracy.
Screen2 / Surface Cavity REcognition and EvaluatioN
Identifies protein cavities and computing cavity attributes that can be applied for classification and analysis. Screen2 defines surface cavities geometrically in terms of the empty space between the protein’s molecular surface and an envelope surface constructed by rolling an intermediate size spherical probe. The accurate detection, characterization, and classification of protein surface cavities afforded by SCREEN should help elucidate structural signatures that are diagnostic of certain protein function and thus aid in structure based function prediction.
A method for the prediction of ligand-binding sites in proteins of known structure. AutoLigand makes predictions based strictly on the properties of the receptor, identifying the optimal ligand volume, shape, and atom types. The strength of the contiguous envelope technique comes from the fact that it allows regions of high affinity to be linked through the regions of low affinity as long as the total affinity of the volume is optimized. AutoLigand is included with the AutoDockTools package.
A toolkit for identifying pockets, cavities and channels of protein structures. The toolkit was developed in PERL programming language and includes “PoreID” for pore identification, “PoreTrace” for pore axes determination and “GateOpen” for opening the gate between neighboring pores. “PoreID” is a grid-based method that avoids orientation dependency of the results. It targets all kinds of pores (pockets, cavities and channels) and is automatic so that only the PDB file of the target protein has to be specified by the user.
Provar / Probability of variation
A method for probabalistic scoring of pocket predictions across large sets of related protein structures. These scores are the overall probabilities of particular atoms or residues being found to be lining a pocket in the set of structures. Scores output in PDB format files can be readily visualized through simple colour-coding atoms or residues. The approach can help compare pockets across multiple conformations of a protein such as those generated by tCONCOORD or any other simulation method. By supplying a suitable sequence alignment it is also possible to visualize pocket conservation across a set of homologous structures. We enable the input of results from several pocket programs, which allows for comparison between those programs.
Resolves the cavity ceiling ambiguity. GaussianFinder recognizes cavities on the protein surface. It combines two Gaussian surfaces of a given protein, called inner and outer surfaces, as a way of finding cavities as clusters of voxels located between those two surfaces. This tool collects all voxels inside atom-centered spheres and then discards voxels inside each solvent sphere centered. It is able to avoid possible geometric ambiguities inherent to the use of grid-based methods.
GIRAF / Geometric Indexing and Refined Alignment Finder
Achieves search of similar structures of ligand binding sites of proteins by exploiting database indexing of structural features of local coordinate frames. GIRAF produces refined atom-wise alignments by iterative applications of the Hungarian method to the bipartite graph defined for a pair of superimposed structures. Since the first version, the GIRAF method has been subject to many significant improvements, which include the design of its back-end database, structural features for geometric indexing, and the alignment algorithm
BSR / Binding Site Refinement
Refines ligand-binding regions in protein models using remotely related templates identified by threading. BSR uses a Support Vector Regression (SVR) model that selects correct binding site geometries in a large ensemble of multiple receptor conformations. It performs satisfactorily even when no closely related templates are used. The tool employs several scoring functions that impose geometrical restraints on the Cα positions, account for a specific chemical environment within a binding site and optimize the interactions with putative ligands.
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Recognizes ligand binding sites for virtual screening and allows de novo drug design. Q-SiteFinder can realize prediction of ligand binding sites by investigating clusters of energetically favorable methyl binding site. It employs the interaction energy between the protein and a simple van der Waals probe to proceed. This tool classifies clustered energetically favorable probe sites according to the sum of interaction energies for sites within each cluster.
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