Multi-dimensional computational pipeline for large-scale deep screening of compound effect assessment: an in silico case study on ageing-related compounds

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. The ability to study the precise effect of chemical compounds on specific molecular entities plays a crucial role in understanding their safety and efficacy landscapes. Towards this goal, an international team of researchers led by Lionel Breton and Hiroaki Kitano proposed an innovative multi-dimensional computation pipeline for large-scale assessment of chemical compounds. The pipeline harnesses the benefits of both structural and network biology together to cluster chemicals on their network effects across pathways and molecular interaction maps. Further, the pipeline was applied to screen a set of anti-ageing-related compounds on fundamental metabolic/molecular pathways associated with the cell vitality. The results highlight the importance of network-based multi-dimensional screens in capturing emergent properties of compounds which may not be apparent from a single-dimensional analysis such as molecular docking or chemical similarity.