In Silico target fishing: addressing a "Big Data" problem by ligand-based similarity rankings with data fusion.

ABSTRACT:

Background

Ligand-based in silico target fishing can be used to identify the potential interacting target of bioactive ligands, which is useful for understanding the polypharmacology and safety profile of existing drugs. The underlying principle of the approach is that known bioactive ligands can be used as reference to predict the targets for a new compound.

Results

We tested a pipeline enabling large-scale target fishing and drug repositioning, based on simple fingerprint similarity rankings with data fusion. A large library containing 533 drug relevant targets with 179,807 active ligands was compiled, where each target was defined by its ligand set. For a given query molecule, its target profile is generated by similarity searching against the ligand sets assigned to each

SUBMITTER: Liu X 

PROVIDER: S-EPMC4068908 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature