Abstract
Most candidate anti-bacterials are identified on the basis of their whole cell anti-bacterial activity. A critical bottleneck in the early discovery of novel anti-bacterials is tracking the structure activity relationship (SAR) of the novel compounds synthesized during the hit to lead and lead optimization stage. It is often very difficult for medicinal chemists to visualize if the novel compounds synthesized for understanding SAR of a particular scaffold have similar molecular mechanism of action (MoA) as that of the initial hit. The elucidation of the molecular MoA of bioactive inhibitors is critical. Here, a new strategy and routine assay for MoA de-convolution, using a microfluidic platform for transcriptional profiling of bacterial response to inhibitors with whole cell activity has been presented. First a reference transcriptome compendium of Mycobacterial response to various clinical and investigational drugs was built. Using feature reduction, it was demonstrated that subsets of biomarker genes representative of the whole genome are sufficient for MoA classification and deconvolution in a medium-throughput microfluidic format ultimately leading to a cost effective and rapid tool for routine antibacterial drug-discovery programs.
Highlights
Since the early 20th century, bioactive inhibitors used for antiinfective chemotherapy have been identified by phenotypic screens and further examined in complex biological systems [1]
Transcriptional profiling is applicable to any molecule that impairs bacterial growth, we evaluated the mechanism of action (MoA) of the natural product cyclomarin
There is an urgent need for new therapeutic approaches to antibiotic discovery as a result of the rapid emergence of multiresistance to existing drugs, which is further exacerbated by the current gap in the development of new molecules
Summary
Since the early 20th century, bioactive inhibitors used for antiinfective chemotherapy have been identified by phenotypic screens and further examined in complex biological systems [1]. In contrast to target-based screening, molecules identified using this approach have the advantage of possessing desirable physicochemical properties from the beginning (such as cell penetration), but are active against the relevant target in its intracellular context, under physiological conditions. Despite this key advantage, success in defining the target, mechanism of action (MoA), and the final lead optimization of hits derived from phenotypic screens has been low [4,6]
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