@TOME-2 is a web pipeline dedicated to protein structure modeling and small-ligand docking based on comparative analyses. Fold-recognition, template selection, structural alignment editing, structure comparisons, 3D-model building and evaluation are possible with @TOME-2 for inputted protein sequences.
This page contains various resources for comparative protein structure modelling and analysis from the Sali Lab at University of California at San Francisco (UCSF).
Cascade PSI-BLAST detects distant protein similarities using a cascade search protocol where PSI-BLAST searches are carried out on each hit, until no new hits are found in the selected database (SwissProt, SCOP, or Pfam).
CATH is a manually curated classification of protein domain structures. Each protein has been chopped into structural domains and assigned into homologous superfamilies (groups of domains that are related by evolution). This classification procedure uses a combination of automated and manual techniques which include computational algorithms, empirical and statistical evidence, literature review and expert analysis.
The Classification of Protein Structures (COPS) web server is a workbench for visualizing and examining proteins in fold space. Access is given to all known protein structures and protein structural domains. Structures and domains may be compared in fold space.
Cologne University Protein Stability Analysis Tool (CUPSAT) is a tool to analyse and predict protein stability changes upon point mutations (single amino acid mutations) for known protein structures.
The Disulfide Bonding Connectivity Pattern (DBCP) web server tool provides prediction of disulphide bonding connectivity patterns without the prior knowledge of the bonding states of cysteines. Useful in locating disulphide bridges and helping to solve protein folding.
DIAL (Domain Identification Algorithm) is a web server for the automatic identification of structural domains given the three-dimensional coordinates of a protein.
eF-seek predicts protein functional sites by searching for similar electrostatic potential and molecular surface shapes against eF-site, a database of electrostatic surfaces for representative ligand binding sites.