Binding Site Prediction in Protein !
The interaction between proteins and other molecules is fundamental to all biological functions. In this section we include tools that can assist in prediction of interaction sites on protein surface and tools for predicting the structure of the intermolecular complex formed between two or more molecules (docking).
Pockets Identification
Automatic Identification of pockets and cavities in proteins structure, and quantitation of their volumes using Delaunay triangulation. Available also as PyMOL plugin
Automatic identification of pockets and cavities in proteins structure, and quantitation of their volumes.
Grid-based technique for the analysis of protein pockets. PocketPicker available as a plugin for PyMOL
Binding Site Prediction
Identification of functional regions in proteins by surface-mapping of phylogenetic information
Identification protein interaction sites. It uses sequence conservation patterns in homologous proteins to distinguish between residues that are conserved due to structural restraints from those due to functional restraints.
Ligand Binding Sites
The server utilizes protein-structure prediction to provide structural models of the binding site. Ligands bound to structures are superimposed onto the model and use to predict the binding site.
A threading-based method for ligand-binding site prediction and functional annotation based on binding-site similarity across superimposed groups of threading templates.
Prediction of binding site by pocket identification using the Connolly surface and degree of conservation
metaPocketA meta server for ligand-binding site prediction. metaPocket use LIGSITEcsc, PASS, Q-SiteFinder and SURFNET
