title: Quantifying biogenic bias in screening libraries.
abstract: In lead discovery, libraries of 10(6) molecules are screened for biological activity. Given the over 10(60) drug-like molecules thought possible, such screens might never succeed. The fact that they do, even occasionally, implies a biased selection of library molecules. We have developed a method to quantify the bias in screening libraries toward biogenic molecules. With this approach, we consider what is missing from screening libraries and how they can be optimized.
authors.affiliation: Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, California, USA.
authors.forename: Jérôme
authors.initials: J
authors.lastname: Hert
authors.forename: John J
authors.initials: JJ
authors.lastname: Irwin
authors.forename: Christian
authors.initials: C
authors.lastname: Laggner
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Keiser
authors.forename: Brian K
authors.initials: BK
authors.lastname: Shoichet
mesh_terms: D001688:Biological Products / Q000737:chemistry*; D016208:Databases, Factual; D055808:Drug Discovery / Q000706:statistics & numerical data; D015394:Molecular Structure; D011506:Proteins / Q000737:chemistry*; D015983:Selection Bias; D054852:Small Molecule Libraries / Q000737:chemistry*; D013329:Structure-Activity Relationship
chemical_list: D001688:Biological Products; D011506:Proteins; D054852:Small Molecule Libraries