指纹(计算)
虚拟筛选
药效团
化学空间
相似性(几何)
背景(考古学)
计算机科学
生物信息学
计算生物学
化学相似性
最近邻搜索
化学
化学信息学
数据挖掘
人工智能
情报检索
机器学习
药物发现
结构相似性
生物信息学
生物
遗传学
图像(数学)
基因
古生物学
作者
Ingo Muegge,Prasenjit Mukherjee
标识
DOI:10.1517/17460441.2016.1117070
摘要
INTRODUCTION: A central premise of medicinal chemistry is that structurally similar molecules exhibit similar biological activities. Molecular fingerprints encode properties of small molecules and assess their similarities computationally through bit string comparisons. Based on the similarity to a biologically active template, molecular fingerprint methods allow for identifying additional compounds with a higher chance of displaying similar biological activities against the same target - a process commonly referred to as virtual screening (VS). AREAS COVERED: This article focuses on fingerprint similarity searches in the context of compound selection for enhancing hit sets, comparing compound decks, and VS. In addition, the authors discuss the application of fingerprints in predictive modeling. EXPERT OPINION: Fingerprint similarity search methods are especially useful in VS if only a few unrelated ligands are known for a given target and therefore more complex and information rich methods such as pharmacophore searches or structure-based design are not applicable. In addition, fingerprint methods are used in characterizing properties of compound collections such as chemical diversity, density in chemical space, and content of biologically active molecules (biodiversity). Such assessments are important for deciding what compounds to experimentally screen, to purchase, or to assemble in a virtual compound deck for in silico screening or de novo design.
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