title: Active learning for computational chemogenomics.
abstract: Computational chemogenomics models the compound-protein interaction space, typically for drug discovery, where existing methods predominantly either incorporate increasing numbers of bioactivity samples or focus on specific subfamilies of proteins and ligands. As an alternative to modeling entire large datasets at once, active learning adaptively incorporates a minimum of informative examples for modeling, yielding compact but high quality models. Results/methodology: We assessed active learning for protein/target family-wide chemogenomic modeling by replicate experiment. Results demonstrate that small yet highly predictive models can be extracted from only 10-25% of large bioactivity datasets, irrespective of molecule descriptors used.
  
  
  
  Chemogenomic active learning identifies small subsets of ligand-target interactions in a large screening database that lead to knowledge discovery and highly predictive models.
authors.affiliation: Computer-Assisted Drug Design, Institute of Pharmaceutical Sciences, Department of Chemistry & Applied Biosciences, Swiss Federal Institute of Technology (ETH Zurich), Vladimir-Prelog-Weg 1-5/10, 8093 Zurich, Switzerland.|Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, 500 Main St, Cambridge, MA 02139, USA.
authors.forename: Daniel
authors.initials: D
authors.lastname: Reker
authors.affiliation: Computer-Assisted Drug Design, Institute of Pharmaceutical Sciences, Department of Chemistry & Applied Biosciences, Swiss Federal Institute of Technology (ETH Zurich), Vladimir-Prelog-Weg 1-5/10, 8093 Zurich, Switzerland.|inSili.com GmbH, Segantinisteig 3, 8049 Zurich, Switzerland.
authors.forename: Petra
authors.initials: P
authors.lastname: Schneider
authors.affiliation: Computer-Assisted Drug Design, Institute of Pharmaceutical Sciences, Department of Chemistry & Applied Biosciences, Swiss Federal Institute of Technology (ETH Zurich), Vladimir-Prelog-Weg 1-5/10, 8093 Zurich, Switzerland.
authors.forename: Gisbert
authors.initials: G
authors.lastname: Schneider
authors.affiliation: Kyoto University Graduate School of Medicine, Center for Medical Education, Life Science Informatics Research Unit, Kyoto 606-8501, Japan.
authors.forename: J B
authors.initials: JB
authors.lastname: Brown
mesh_terms: D001665:Binding Sites; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D062126:Databases, Chemical; D055808:Drug Discovery / Q000379:methods*; D023281:Genomics; D008024:Ligands; D000069550:Machine Learning; D008956:Models, Chemical; D011506:Proteins / Q000378:metabolism*
chemical_list: D008024:Ligands; D011506:Proteins
keywords: chemogenomics; computational chemistry and modeling; virtual screening