化学信息学
计算机科学
高通量筛选
虚拟筛选
钥匙(锁)
选择(遗传算法)
数据挖掘
数据提取
机器学习
情报检索
数据科学
药物发现
化学
生物信息学
梅德林
生物
生物化学
计算机安全
作者
Monika Wawer,Jürgen Bajorath
标识
DOI:10.2174/092986709789378189
摘要
The wealth of biological screening data that is generated poses substantial problems to medicinal chemistry. A key question becomes how to best prioritize and select hits for further evaluation from the many weakly active compounds that are typically identified in HTS campaigns. Such decisions can be substantially supported if it is possible to evaluate preliminary structure-activity relationship (SAR) information that might be contained in screening data. If SAR information can be extracted from screening data, one can attempt to estimate the chemical optimization potential of hits. We will discuss different types of approaches that have been developed to facilitate HTS data analysis, with special emphasis on recent methods to explore SAR information contained in screening sets. Keywords: High-throughput screening, structure-activity relationships, active compounds, hit selection, hit-to-lead optimization, chemoinformatics, molecular networks, SAR analysis functions, SAR pathways
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