1 - 19 of 19 results

GenProBiS

Maps sequence variants to protein structures from the Protein Data Bank (PDB), and further to protein–protein, protein–nucleic acid, protein–compound, and protein–metal ion binding sites. GenProBiS enables detection of sequence variants within a protein binding site. It allows visual exploration of interactions, or loss of interactions, of a specific mis-sense mutation with a specific ligand. The tool permits focused laboratory experiments based on targeted hypotheses in several research fields including human, veterinary medicine, animal and plant breeding.

eMatchSite

Allows alignment and matching for ligand binding site. eMatchSite accurately identifies pairs of pockets that bind similar compounds even in proteins with different global structures. Furthermore, it tolerates structural distortions in protein models, thus experimentally solved structures are not required. This tool provides a calibrated significance score to identify those pockets capable of binding chemically similar ligands regardless of any global sequence and structure similarities between the target proteins.

SIENA

Creates protein-structural ensembles for the analysis of protein flexibility, molecular design efforts like docking or de novo design within seconds. SIENA is an online pipeline that permits to process the whole PDB in order to create a large collection of protein binding site ensembles. This app is specialized to the identification alternative and structurally consistent conformations of protein binding site. It is fast enough for generating large protein structure ensembles on the fly.

SuMo

A bioinformatic system for finding similarities in arbitrary 3D structures or substructures of proteins. SuMo is based on a unique representation of macromolecules using selected triplets of chemical groups having their own geometry and symmetry, regardless of the restrictive notions of main chain and lateral chains of amino acids. The heuristic for extracting similar sites was used to drive two major large-scale approaches. First, searching for ligand binding sites onto a query structure has been made possible by comparing the structure against each of the ligand binding sites found in the Protein Data Bank (PDB). Second, the reciprocal process, i.e. searching for a given 3D site of interest among the structures of the PDB is also possible and helps detect cross-reacting targets in drug design projects.

APoc / Alignment of Pockets

A computational method for the large-scale, sequence order-independent, structural comparison of protein pockets. A scoring function, the Pocket Similarity Score (PS-score), is derived to measure the level of similarity between pockets. Statistical models are used to estimate the significance of the PS-score based on millions of comparisons of randomly related pockets. APoc is a general robust method that may be applied to pockets identified by various approaches, such as ligand-binding sites as observed in experimental complex structures, or predicted pockets identified by a pocket-detection method.

PARIS / Pocket Alignment in Relation to Identification of Substrates

A method to measure the similarity between protein binding sites. In this method, binding pockets are described as clouds of points in the 3D space, each point corresponding to an atom. These points may bare additional labels representing various characteristics such as atom partial charges, atom types, or other atomic features. The proposed method showed good performance in the classification of binding pockets according to their respective ligands. It relies on the search for the best global superposition of clouds of atoms, which confers robustness with respect to binding site definition or variations in ligand conformation. This method may be used to compare any type of binding sites in the 3D space, even in absence of overall sequence or structure similarity between their corresponding proteins.

BSAlign / Binding Site Aligner

A method for rapid detection of potential binding site(s) in the target protein(s) that is/are similar to the query protein's ligand-binding site. We represent both the binding site and the protein structure as graphs, and employ a subgraph isomorphism algorithm to detect the similarities of the binding sites in a very time-efficient manner. The proposed method can be a useful contribution towards speed-critical applications such as drug discovery in which a large number of proteins are needed to be processed.

IsoCleft Finder

Obsolete
A web-based tool for the detection of local geometric and chemical similarities between potential small-molecule binding cavities and a non-redundant dataset of ligand-bound known small-molecule binding-sites. IsoCleft Finder offers a powerful web-interface to define clefts and to visualize and analyze the obtained results of binding-site similarities. IsoCleft Finder results are complementary to existing approaches for the prediction of protein function from structure, rational drug design and x-ray crystallography.