QuartataWeb
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What is the QuartataWeb Server?
Data on protein-drug and protein-chemical interactions are rapidly accumulating in databases such as DrugBank and STITCH. These data usually reflect observed interactions, while the lack of data for a given protein-drug/chemical pair does not necessarily mean the lack of interaction. Indeed, recent studies, both computational and experimental, highlighted the promiscuity of both proteins and small molecules: many drugs have side effects i.e. they target proteins other than those known in public databases; and many proteins bind chemicals other than those known, opening the way to design repurposable drugs, new chemicals, or polypharmacological treatments. There is a need for efficiently identifying such interactions and disseminating them. The QuartataWeb server is designed to address this need by learning probabilistic latent factor models for protein-drug/chemical interactions and enabling users to efficiently mine known interactions and predict new ones. In addition, QuartataWeb links targets to KEGG pathways and Gene Ontology (GO) terms, thus completing the bridge between drugs/chemicals and pathways.

Data source: DrugBank STITCH help

Drug group in DrugBank: Approved drugs All drugs

Input type: Chemical and/or target A list of chemicals, targets or chemical combinations

Input at least one chemical and/or one target

Query type: chemical-target interaction chemical-chemical similarity target-target similarity

Drug 1:
DrugBank drug ID or common drug name (e.g. "Loxapine" or "DB01224").

Target 1:
UniProt AC or entry name, gene name or protein name (e.g. "P28566" or "ADA2A").

Drug 2:
DrugBank drug ID or common drug name (e.g. "Asenapine" or "DB01142").

Target 2:
UniProt AC or entry name, gene name or protein name (e.g. "P34969" or "5HT7R").

No. of predictions (1 to 100):

Display secondary Interactions: No Yes

No. of 2nd predictions (1 to 20):


Load examples: 
         



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The QuartataWeb server is maintained by Dr. Hongchun Li in the Bahar Lab at the Department of Computational & Systems Biology at the University of Pittsburgh, School of Medicine, and sponsored by the NIH awards P41 GM103712, P30 DA035778, U19 AI068021, and P01 DK096990.

For questions and comments please contact Hongchun Li.