Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
The identification of the targets of therapeutic drugs is one of the major challenges for pharmaceutical companies. The main target responsible for drug action is often known, but most drugs also bind other targets, either causing deleterious side effects in patients, or enabling the drug to be used for treating other diseases as well. Although plenty of methods are currently available for drug profiling, there are still a lot of drugs with unexplained side effects and with potential alternative uses. In this context, a novel method for target deconvolution was developed in the research group of Prof. Kai Johnsson, and is called Yeast Three-Hybrid. This method relies on the SNAP-tag technology for anchoring of the drug, and consists in screening libraries of human proteins for potential targets of drugs of interest. This novel approach was successfully applied in the lab and already led to the discovery of the mechanism of action of the anti-inflammatory drug sulfasalazine. In the first part of this work, automation of certain steps in the Y3H screening platform was implemented. This enabled more drugs and more libraries to be used at the same time. The automated platform was used to screen up to 12 libraries against 17 drugs of interest. Targets were then evaluated through methods based on affinity chromatography and protein cross-linking. Both methods rely on the SNAP-tag technology and therefore enable the same drug derivative to be used in both screenings and validation. The most relevant finding was that interactions between drugs and secreted proteins could be identified in screenings, although Yeast Three-Hybrid interactions occur in the nucleus of yeast cells. This is a significant result because it broadens the scope of the Yeast Three-Hybrid approach. In the second part of the project, the validation of Yeast Three-Hybrid hits and the sensitivity of the system were improved in a couple of ways. One important contribution was the development of a competition assay for easy validation of targets in yeast cells. This assay could definitely help make a selection if many hits were found in screenings and it would be necessary to decide with which hits to pursue further. In addition, the sensitivity of our system was compared to other Yeast Three- Hybrid systems. A comparison with the same system based on bacterial dihydrofolate reductase as bait yielded striking results for the drugs erlotinib and sulfasalazine. Taken together, the results showed that the dihydrofolate reductase-based system was more sensitive than the SNAP-based system, most likely because of the better permeability of the drug derivatives. Then, if only one system had to be selected for future screenings, it would most probably be the dihydrofolate reductase-based system. These last results were the most significant of this work because they initiated an important transition in the way future screenings will be performed. In summary, this work has brought many improvements to the Yeast Three-Hybrid screening platform in terms of throughput, hit validation, and sensitivity. These improvements will increase the chance of identifying protein targets of drugs in future screenings, and therefore contribute to the scientific progress in the field of drug profiling and more generally drug discovery.
Christoph Bostedt, Camila Bacellar Cases Da Silveira
Paul Joseph Dyson, Irina Sinenko, Roland Christopher Turnell-Ritson