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J Comput Aided Mol Des. 2017 Mar;31(3):319-328. doi: 10.1007/s10822-016-9990-4. Epub 2016 Nov 9.

Empowering pharmacoinformatics by linked life science data.

Author information

1
Department of Pharmaceutical Chemistry, University of Vienna, Althanstraße 14, 1090, Vienna, Austria.
2
Department of Pharmaceutical Chemistry, University of Vienna, Althanstraße 14, 1090, Vienna, Austria. gerhard.f.ecker@univie.ac.at.

Abstract

With the public availability of large data sources such as ChEMBLdb and the Open PHACTS Discovery Platform, retrieval of data sets for certain protein targets of interest with consistent assay conditions is no longer a time consuming process. Especially the use of workflow engines such as KNIME or Pipeline Pilot allows complex queries and enables to simultaneously search for several targets. Data can then directly be used as input to various ligand- and structure-based studies. In this contribution, using in-house projects on P-gp inhibition, transporter selectivity, and TRPV1 modulation we outline how the incorporation of linked life science data in the daily execution of projects allowed to expand our approaches from conventional Hansch analysis to complex, integrated multilayer models.

KEYWORDS:

Computer-aided drug discovery; Data curation; Data extraction; Data integration; Pharmacophore modeling; QSAR; TRPV1

PMID:
27830428
PMCID:
PMC5385323
DOI:
10.1007/s10822-016-9990-4
[Indexed for MEDLINE]
Free PMC Article

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