1The Systems Biology Institute, Tokyo, Japan.
L'Oréal Research and Innovation, Aulnay-sous-Bois, France.
NPJ Syst Biol Appl. 2019 Nov 26;5:42. doi: 10.1038/s41540-019-0119-y. eCollection 2019.
Designing alternative approaches to efficiently screen chemicals on the efficacy landscape is a challenging yet indispensable task in the current compound profiling methods. Particularly, increasing regulatory restrictions underscore the need to develop advanced computational pipelines for efficacy assessment of chemical compounds as alternative means to reduce and/or replace in vivo experiments. Here, we present an innovative computational pipeline for large-scale assessment of chemical compounds by analysing and clustering chemical compounds on the basis of multiple dimensions-structural similarity, binding profiles and their network effects across pathways and molecular interaction maps-to generate testable hypotheses on the pharmacological landscapes as well as identify potential mechanisms of efficacy on phenomenological processes. Further, we elucidate the application of the pipeline on a screen of anti-ageing-related compounds to cluster the candidates based on their structure, docking profile and network effects on fundamental metabolic/molecular pathways associated with the cell vitality, highlighting emergent insights on compounds activities based on the multi-dimensional deep screen pipeline.
设计替代方法来有效地在功效景观上筛选化学物质是当前化合物分析方法中具有挑战性但不可或缺的任务。特别是，不断增加的监管限制强调需要开发先进的计算管道，以对化学化合物的功效进行评估，作为减少和/或替代体内实验的替代手段。在这里，我们提出了一种创新的计算管道，通过基于多个维度（结构相似性、结合谱及其在途径和分子相互作用图谱中的网络效应）对化学物质进行分析和聚类，来大规模评估化学物质，以生成关于药理学景观的可测试假说，并确定在表型过程中的潜在功效机制。此外，我们阐述了该管道在抗衰老相关化合物筛选中的应用，根据化合物的结构、对接谱和对与细胞活力相关的基本代谢/分子途径的网络效应进行聚类，突出了基于多维深度筛选管道的化合物活性的新见解。
