Using Heterogeneous Information Sources for Understanding the Mode of Action of Compounds

化合物在生物系统中的作用模式可以在不同的水平上描述，例如在配体-蛋白质相互作用水平上(例如，与靶结合、抑制酶等)，以及在生物系统中的作用水平(例如，使用基因组或蛋白质组读数、细胞形态读数等)。所有这些观点都是同样有效的，因此，整合不同类型的信息以得出关于化合物在生物系统中的作用模式的综合观点是非常可取的。这就是当前项目旨在向前迈出的一步。我们将汇编一个化合物数据集，将分子结构与生物活性和生物效应联系起来，在不同的水平上，例如(但不限于)以上。随后，将采用数据挖掘算法，目的是在不同程度的化学和生物影响之间建立联系，即了解与哪些生物目标的哪些相互作用将导致特定的下游(通常是可观察到的)影响。在这些链接中，下一步是识别模式，即能够概括出哪种类型的相互作用，与哪种蛋白质(或信号级联等)。将导致一种特定的效应，然后可以被翻译到其他相关的生物系统(如信令网络)。这项工作将在公共和专有数据上进行，这将使我们能够以适当的方式发布我们的发现，以及在特定感兴趣的领域与公司赞助商阿斯利康进行预期验证。

The mode of action of a compound in a biological system can be described on different levels, such as on the ligand-protein interaction level (e.g. binding to a target, inhibiting an enzyme etc.), as well as the effect level in a biological system (e.g. using genomic or proteomic readouts, cellular morphology readouts etc.). All of those viewpoints are equally valid, and hence an integration of different types of information to arrive at an integrated view on the mode of action of compounds in a biological system is highly desirable. This is where the current project aims to make a step forward. We will compile a compound data set which links molecular structure to bioactivites, and biological effects, on different levels, such as (but not limited to) the above. Subsequently, data mining algorithms will be employed that aim to establish links between the different levels of chemical and biological effects, i.e. to understand which interaction with which biological targets will lead to a particular downstream (often observable) effect. Within those links the next step is then to identify patterns, i.e. to be able to generalize which type of interaction, with which protein (or signalling cascade, etc.) will lead to a particular effect, which can then be translated to other, related biological systems (such as signalling networks). This work will be performed on both public and proprietary data, which will enable us to both publish our findings in a suitable manner, as well as to perform prospective validations with the company sponsor, AstraZeneca, in particular areas of interest.