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PMID: 11045811 Published · ppublish English Journal Article

Drug-like index: a new approach to measure drug-like compounds and their diversity.

Journal of chemical information and computer sciences ·Vol. 40 ·No. 5 ·2000-00-00 ·Pages 1177-87

Xu J, Stevenson J

Abstract

Combinatorial organic synthesis (combinatorial chemistry or CC) and ultrahigh-throughput screening (UHTS) are speeding up drug discovery by increasing capacity for making and screening large numbers of compounds. However, a key problem is to select the smaller set of "representative" compounds from a virtual library to make or screen. Our approach is to select drug-like as well as structurally diverse compounds. The compounds, which are not very drug-like, are less taken into account or excluded even if they contribute to the diversity of the collection. Hence, the first step in the compound selection is to rank compounds in drug-like "degree". To quantify the drug-like "degree", drug-like index (DLI) is introduced in this paper. A compound's DLI is calculated based upon the knowledge derived from known drugs selected from Comprehensive Medicinal Chemistry (CMC) database. The paper describes the way of this knowledge base is formed and the procedure for selecting drug-like compounds.

MeSH Terms
Algorithms Combinatorial Chemistry Techniques Databases, Factual Drug Design Models, Molecular
Authors & Affiliations
2 authors, click to expand affiliations / ORCID
Xu J
Research & Development Center, Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, Connecticut 06877-0368, USA.
Stevenson J
Article Info
Journal
Journal of chemical information and computer sciences
Abbr.
J Chem Inf Comput Sci
ISSN
0095-2338
Published
2000-00-00
Pages
1177-87
Language
English
Region
United States
NLM ID
7505012
Subset
IM
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