TiPs

HELP


General description

TiPs has been developed with the aim of facilitating the identification of potential therapeutical targets in more than 150 organisms responsible for human infections. We performed a large-scale analysis to systematically identify candidate targets in the proteome of pathogen organisms. Predictions are made using the available information on drug-target three-dimensional (3D) complexes and by exploiting the homology relationships of known drug targets with pathogen proteins. Predicted pathogen targets are further annotated with sequence, structural and functional information. Users can quickly prioritise drug-target pairs by running simple queries (by organism, protein family or function, or UniProt ID), getting a list of candidate drug targets, and analysing the pattern of interactions between the pathogen proteins and the drugs predicted to target them.
 

Result table

The output of any type of search is a table reporting exhaustive information about the known drug-target pairs and the predicted ones. The table has the following column headers:
  • Drug name It is linked to the drug page (see below)
  • Organism The name of the organism on which the drug is known to be effective
  • Known target Uniprot ID of the known molecular target of the drug. It is linked to the protein page (see below)
  • Predicted organism Name of the organism on which the drug is predicted to be effective
  • Taxonomy ID Taxonomy identifier of the pathogen organism. It is linked to Taxonomy database
  • Predicted target Uniprot ID of the predicted pathogen target. It is linked to the protein page (see below)
  • Protein name Protein name of the predicted target
  • BSI BLAST global Sequence Identity between known and predicted targets
  • BSSI is the Binding Site Sequence Identity between known and predicted target binding sites calculated as the precentage of identical residues over the aligned residues in the binding site
  • BS RMSD Binding Site RMSD calculated after local superposition of the C-alpha atoms of known and predicted binding site residues. When the structure of the predicted target is experimentally solved, the best resolution one is used for the superposition.
  • Clashes indicates the presence/absence of atomic clashes beetween drug and protein atoms. Clashes can involve side chain atoms (s.c.) or main chain atoms (m.c.)
  • Indels indicates the presence/absence of indels within 5 Angstroms from any atom of the drug
  • 3D complex It is linked to the structure page (see below) where the user can analyse and/or download the structure of the predicted drug-target complex. When the drug-target complex has experimantally solved structure(s) it provides a link to the PDB page
The table allows several options for user interaction control (setting the number of entries per page, on-the-fly filtering, multi-column sorting). The user can save the page in several format (Text only, Excel, CSV, PDF) or can display a printer-friendly version of the page.

Drug page

The page provides specific information on the drug, including physicochemical properties, drug indication(s), drug category and side effects. It also supplies a link to the predicted pathogen target(s) and information on the known target(s)

Protein page

The page provides both sequence (UniProt) annotation and structural information on the protein as well as information on its known and predicted drug(s).

Structure page

Structural annotation is provided and the predicted 3D complex is displayed in a Jmol interactive panel. The user can also visualise the known 3D complex and compare it to the predicted one. The two-dimensional diagrams of interactions (LIGPLOT) are also provided for both complexes. In the initial Jmol session, the drug is represented in red balls-and-sticks and the target in ribbon. Both known and predicted complexes can be downloaded in PDB format. Please ensure that JAVA is installed and working on your computer and your browser configured accordingly. For any problem please refer to http://jmol.sourceforge.net.
 
TiPs - March 2013 © Biocomputing.it