Kutchukian, P. S. et al. (2017) Iterative focused screening with biological fingerprints identifies selective Asc-1 inhibitors distinct from traditional high throughput screening. ACS Chemical Biology, 12(2), pp. 519-527. (doi:10.1021/acschembio.6b00913) This is the author's final accepted version.There may be differences between this version and the published version. You are advised to consult the publisher's version if you wish to cite from it.http://eprints.gla.ac.uk/146530/
In the triage of hits from a high-throughput screening campaign or during the optimization of a lead compound, it is relatively routine to test compounds at multiple concentrations to determine potency and maximal effect. Additional follow-up experiments, such as agonist shift, can be quite valuable in ascertaining compound mechanism of action (MOA). However, these experiments require cross-titration of a test compound with the activating ligand of the receptor requiring 100-200 data points, severely limiting the number tested in MOA assays in a screening triage. We describe a process to enhance the throughput of such cross-titration experiments through the integration of Hewlett Packard's D300 digital dispenser onto one of our robotics platforms to enable on-the-fly cross-titration of compounds in a 1536-well plate format. The process handles all the compound management and data tracking, as well as the biological assay. The process relies heavily on in-house-built software and hardware, and uses our proprietary control software for the platform. Using this system, we were able to automate the cross-titration of compounds for both positive and negative allosteric modulators of two different G protein-coupled receptors (GPCRs) using two distinct assay detection formats, IP1 and Ca detection, on nearly 100 compounds for each target.
Gram-negative bacteria are notoriously more resistant to antibiotics than Gram-positive bacteria, primarily due to the presence of the outer membrane and a plethora of active efflux pumps. However, the potency of antibiotics also varies dramatically between different Gram-negative pathogens, suggesting major mechanistic differences in how antibiotics penetrate permeability barriers.
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