Abstract：
Drug-induced liver injury (DILI) is the principal reason for failure in developing drug candidates. It is the most common reason to withdraw from the market after a drug has been approved for clinical use. In this context, data from animal models, liver function tests, and chemical properties could complement each other to understand DILI events better and prevent them. Since the chemical space concept improves decision-making drug design related to the prediction of structure-property relationships, side effects, and polypharmacology drug activity (uniquely mentioning the most recent advances), it is an attractive approach to combining different phenomena influencing DILI events (e.g., individual \"chemical spaces\") and exploring all events simultaneously in an integrated analysis of the DILI-relevant chemical space. However, currently, no systematic methods allow the fusion of a collection of different chemical spaces to collect different types of data on a unique chemical space representation, namely \"consensus chemical space.\" This study is the first report that implements data fusion to consider different criteria simultaneously to facilitate the analysis of DILI-related events. In particular, the study highlights the importance of analyzing together in vitro and chemical data (e.g., topology, bond order, atom types, presence of rings, ring sizes, and aromaticity of compounds encoded on RDKit fingerprints). These properties could be aimed at improving the understanding of DILI events.
摘要：
药物诱导的肝损伤（DILI）是开发候选药物失败的主要原因。在药物被批准用于临床使用后，退出市场是最常见的原因。在这种情况下，来自动物模型的数据，肝功能检查,和化学性质可以相互补充，以更好地理解DILI事件并防止它们。由于化学空间概念改善了与结构-性质关系预测相关的决策药物设计，副作用,和多药理学药物活性(唯一提到的最新进展)，这是一种有吸引力的方法来组合影响DILI事件的不同现象(例如，个体“化学空间”)，并在DILI相关化学空间的综合分析中同时探索所有事件。然而,目前,没有系统的方法允许融合不同化学空间的集合，以收集关于独特化学空间表示的不同类型的数据，即“共识化学空间”。“这项研究是第一份实现数据融合以同时考虑不同标准的报告，以促进对DILI相关事件的分析。特别是,这项研究强调了将体外和化学数据一起分析的重要性(例如，拓扑,债券订单，原子类型,戒指的存在，戒指尺寸,和RDKit指纹上编码的化合物的芳香性)。这些性质可以旨在提高对DILI事件的理解。
