Objectives: TPP was developed to identify drug-binding targets by analyzing the impact on interacting proteins’ thermal stability of the binding of a drug molecule without requiring compound modification or candidate protein purification. To detect and identify ligand-induced shifts of thermal stability curves and thus drug target in the case of SARS-COV-2, an optimized and multiplexed quantification workflow using isobaric labelling with TMT (Tandem Mass Tag) was applied over a temperature gradient.
Methods: To obtain a final thermal curve, a gradient composed of 16 temperatures was applied on 5 conditions: infected cells, positive control (non-infected cells with addition of drug), non-infected and non-treated cells, infected cells with the functional drug and finally, negative control (infected cells with a non-functional drug).
After a centrifugation step, proteins contained in the supernatant of each condition were digested by SP3 (Single Plot Solid Phase enhanced Sample Preparation), then labelled by TMT-16plex. One pool was obtained per condition and further C-18 desalted. The labelled peptide mixture was analyzed on a nanoAcquity system coupled to an Orbitrap Eclipse Tribrid mass spectrometer (Thermo Scientific). Data processing was done using Proteome Discoverer and Statistical Analysis with a TPP-package in R.
Results: More than 1500 proteins were quantified in the five conditions and thermal stability curves could be drawn for all of them. As promising results, a list of candidate proteins with significant thermal shifts were selected and are in the process of being validated.
Conclusion: While those initial results are encouraging, further optimizations are still required especially at the sample design and data treatment steps.