The concept of chemical space is a cornerstone in chemoinformatics, and it has broad conceptual and practical applicability in many areas of chemistry, including drug design and discovery. One of the most considerable impacts is in the study of structure–property relationships where the property can be a biological activity or any other characteristic of interest to a particular chemistry discipline. The chemical space is highly dependent on the molecular representation that is also a cornerstone concept in computational chemistry. Herein, we discuss the recent progress on chemoinformatic tools developed to expand and characterize the chemical space of compound data sets using different types of molecular representations, generate visual representations of such spaces, and explore structure–property relationships in the context of chemical spaces. We emphasize the development of methods and freely available tools focusing on drug discovery applications. We also comment on the general advantages and shortcomings of using freely available and easy-to-use tools and discuss the value of using such open resources for research, education, and scientific dissemination.

化学空间的概念是化学信息学的基石，在许多化学领域（包括药物设计和发现）中具有广泛的概念和实际适用性。最重要的影响之一是结构-性质关系的研究，其中性质可以是生物活动或特定化学学科感兴趣的任何其他特征。化学空间高度依赖于分子表示，这也是计算化学中的基石概念。在此，我们讨论了化学信息学工具的最新进展，这些工具开发用于使用不同类型的分子表示扩展和表征化合物数据集的化学空间，生成此类空间的视觉表示，并探索化学空间背景下的结构-性质关系。我们强调专注于药物发现应用的方法和免费工具的开发。我们还评论了使用免费提供和易于使用的工具的一般优点和缺点，并讨论了使用此类开放资源进行研究、教育和科学传播的价值。