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STRUCTURE-ACTIVITY RELATIONSHIP APPROACHES AND APPLICATIONS

机译：结构-活动关系的方法和应用

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摘要

New techniques and software have enabled ubiquitous use of structure―activity relationships (SARs) in the pharmaceutical industry and toxicological sciences. We review the status of SAR technology by using examples to underscore the advances as well as the unique technical challenges. Applying SAR involves two steps: Characterization of the chemicals under investigation, and application of chemometric approaches to explore data patterns or to establish the relationships between structure and activity. We describe generally but not exhaustively the SAR methodologies popular use in toxicology, including representation of chemical structure, and chemometric techniques where models are both unsupervised and supervised. The utility of SAR technology is most evident when supervised methods are used to predict toxicity of untested chemicals based only on chemical structure. Such models can predict on both an ordinal scale (e.g., active vs inactive) or a continuous scale (e.g., median lethal dose [LD50] dose). The reader is also referred to a companion paper in this issue that discusses quantitative structure―activity relationship (QSAR) methods that have advanced markedly over the past decade.
机译：新技术和软件已使制药业和毒理学界普遍使用结构-活性关系（SAR）。我们通过示例来强调SAR的进步以及独特的技术挑战，从而回顾SAR技术的现状。 SAR的应用包括两个步骤：表征所研究的化学物质，以及应用化学计量学方法探索数据模式或建立结构与活性之间的关系。我们一般但不详尽地描述毒理学中普遍使用的SAR方法，包括化学结构的表示以及模型均不受监督和监督的化学计量技术。当仅使用化学结构的监督方法来预测未经测试的化学药品的毒性时，SAR技术的效用最为明显。这样的模型可以在顺序量表（例如，活动与不活动）或连续量表（例如，中值致死剂量[LD50]剂量）上进行预测。读者还可以参考本期的随行论文，该论文讨论了在过去十年中显着发展的定量结构-活性关系（QSAR）方法。

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