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Nucleic Acids Res. 2018 Jan 04;46:D1137-D1143. doi: 10.1093/nar/gkx1088.

SuperDRUG2: a one stop resource for approved/marketed drugs.

Nucleic acids research

Vishal B Siramshetty, Oliver Andreas Eckert, Björn-Oliver Gohlke, Andrean Goede, Qiaofeng Chen, Prashanth Devarakonda, Saskia Preissner, Robert Preissner

Affiliations

  1. Structural Bioinformatics Group, Experimental and Clinical Research Center (ECRC), Charité - University Medicine Berlin, Berlin, Germany.
  2. German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany.
  3. BB3R - Berlin Brandenburg 3R Graduate School, Freie Universitaät Berlin, Berlin, Germany.
  4. Structural Bioinformatics Group, Institute for Physiology, Charité - University Medicine Berlin, Berlin, Germany.
  5. China Scholarship Council (CSC), China.

PMID: 29140469 PMCID: PMC5753395 DOI: 10.1093/nar/gkx1088

Abstract

Regular monitoring of drug regulatory agency web sites and similar resources for information on new drug approvals and changes to legal status of marketed drugs is impractical. It requires navigation through several resources to find complete information about a drug as none of the publicly accessible drug databases provide all features essential to complement in silico drug discovery. Here, we propose SuperDRUG2 (http://cheminfo.charite.de/superdrug2) as a comprehensive knowledge-base of approved and marketed drugs. We provide the largest collection of drugs (containing 4587 active pharmaceutical ingredients) which include small molecules, biological products and other drugs. The database is intended to serve as a one-stop resource providing data on: chemical structures, regulatory details, indications, drug targets, side-effects, physicochemical properties, pharmacokinetics and drug-drug interactions. We provide a 3D-superposition feature that facilitates estimation of the fit of a drug in the active site of a target with a known ligand bound to it. Apart from multiple other search options, we introduced pharmacokinetics simulation as a unique feature that allows users to visualise the 'plasma concentration versus time' profile for a given dose of drug with few other adjustable parameters to simulate the kinetics in a healthy individual and poor or extensive metabolisers.

© The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

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