Bajorath Jürgen
Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Dahlmannstr. 2, D-53113, Bonn, Germany.
Methods Mol Biol. 2017;1526:231-245. doi: 10.1007/978-1-4939-6613-4_13.
The assessment of small molecule similarity is a central task in chemoinformatics and medicinal chemistry. A variety of molecular representations and metrics are applied to computationally evaluate and quantify molecular similarity. A critically important aspect of molecular similarity analysis in chemoinformatics and pharmaceutical research is that one is typically not interested in quantifying the degree of structural or chemical similarity between compounds per se, but rather in extrapolating from molecular similarity to property similarity. In other words, one assumes that there is a correlation between calculated similarity and specific properties of small molecules including, first and foremost, biological activities. Although similarity is a priori a subjective concept, and difficult to quantify, it must computationally be assessed in a formally consistent manner. Otherwise, there is little utility of similarity calculations. Consistent treatment requires approximations to be made and the consideration of alternative computational similarity concepts, as discussed herein.
小分子相似性评估是化学信息学和药物化学中的核心任务。多种分子表示法和指标被用于通过计算来评估和量化分子相似性。在化学信息学和药物研究中，分子相似性分析的一个至关重要的方面是，人们通常并不关心量化化合物本身之间的结构或化学相似程度，而是关心从分子相似性推断性质相似性。换句话说，人们假定计算出的相似性与小分子的特定性质之间存在相关性，其中首要的是生物活性。尽管相似性从先验角度来看是一个主观概念，且难以量化，但必须以形式上一致的方式通过计算进行评估。否则，相似性计算几乎没有用处。如本文所讨论的，一致的处理需要进行近似并考虑替代的计算相似性概念。
