药品
药物发现
组合化学
秩(图论)
计算机科学
选择(遗传算法)
虚拟筛选
集合(抽象数据类型)
化学
数学
药理学
医学
人工智能
组合数学
生物化学
程序设计语言
作者
Jun Xu,James Stevenson
出处
期刊:Journal of Chemical Information and Computer Sciences
[American Chemical Society]
日期:2000-09-01
卷期号:40 (5): 1177-1187
被引量:132
摘要
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.
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