MOST: most-similar ligand based approach to target prediction.

ABSTRACT:

Background

Many computational approaches have been used for target prediction, including machine learning, reverse docking, bioactivity spectra analysis, and chemical similarity searching. Recent studies have suggested that chemical similarity searching may be driven by the most-similar ligand. However, the extent of bioactivity of most-similar ligands has been oversimplified or even neglected in these studies, and this has impaired the prediction power.

Results

Here we propose the MOst-Similar ligand-based Target inference approach, namely MOST, which uses fingerprint similarity and explicit bioactivity of the most-similar ligands to predict targets of the query compound. Performance of MOST was evaluated by using combinations of different fingerprint schemes, machine learn

SUBMITTER: Huang T 

PROVIDER: S-EPMC5346209 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature