Quantification using label-free or isotope-labeled approaches

Assessing the EC50 of a given drug-protein interaction depends on residual binding ratios after competition profiling for each dose. Therefore, reliable and reproducible quantification is needed.

The original publication⁹¹ suggested labeling with iTRAQ or TMT and multiplexing of the samples. A new labeling reagent for MS2 based quantification (TMT10) allows labeling of 10 samples and then combining them for subsequent measurement¹⁹⁹. This matched the experimental setup regarding the number of increasing compound concentrations plus DMSO control and pulldown of pulldown sample. Multiplexing was appealing, as it would reduce the measurement time per compound by a factor ten and result in quantitative values across all dosage points for every peptide sequenced.

This might suffer from less identified peptides and proteins. Another option was relative quantification with no label at all. In label-free quantification, MS1 intensities are used as measure of abundance and can be directly compared between samples. However, each experimental condition for one compound needs to be measured in a separate MS-run increasing the measurement time for one competition experiment. Moreover, peptides might not be quantified in each run because of the statistical nature in DDA MS measurements resulting in less peptides and proteins with meaningful dose responses. A dose dependent competition with the multi-kinase inhibitor Golvatinib in the four cell line mix was used for evaluation of label-free or TMT-labeled quantification. For TMT evaluations five dose-response pulldowns of Golvatinib were labeled and pooled to one mix. The pulldown for label-free quantification was performed separately. For TMT measurements, 2.5x more peptide was injected than in the label-free run.

Label-free MS-runs were performed on the Orbitrap Elite using a 2 h gradient and up to 15 precursors per MS1 run were selected for MS2 measurement and isolated with a window of 2 Th in the ion trap (see Experimental Procedures). Over 1800 proteins, including 230 kinases, were identified in this experiment (Figure 12).

35 Figure 12: Protein identification in label-free or TMT quantification. Number of protein (left y-axis) and kinase (right y-axis) identifications influenced by quantification and measurement method. Label-free quantification yields more proteins and kinases than TMT labeled samples. Less kinases were identified in the TMT MS3 acquisition, whereas similar numbers could be identified in TMT MS2 methods

DDR2, EPHA2, RIPK2, and ZAK were selected as example targets. All four proteins showed a dose dependent decrease in residual binding to the beads and showed no residual binding at higher doses (light blue line/points, Figure 13).

For TMT-labeled samples, these MS-parameters had to be varied to find a potential optimal solution. The first method used a 2 h-gradient and subjected the 10 most intense precursors for MS2 measurement with an isolation width of 1.3 Th in the ion trap (2h Top 10; dark grey line/points, Figure 13). With this method, 825 proteins and 142 kinases were identified. For DDR2, no curve could be fitted; the other targets show a decrease in residual binding to 0.8 at the highest compound concentration. A prolonged gradient (4h Top 10; light grey line/points, Figure 13) also did not improve curve fits but yielded slightly more total protein and kinase identifications (1115 and 169, respectively, Figure 12).

The plateau of the dose response curves can be attributed to ratio compression, partially due to co-isolation and co-fragmentation of other peptides²⁰¹. Therefore, the isolation width was decreased from 1.3 to the lowest possible window (0.8 Th; iso 0.8; black line/points, Figure 13) to reduce the impact of co-isolation. Similar numbers of proteins and kinases were identified (Figure 12). The curve shape for potential targets did not change much compared to prior acquisition methods. The residual binding remained at a least ratio of 0.5 for DDR2, RIPK2 and EPHA2 and no competition could be observed for ZAK. To diminish the effect of potential co-isolation further, peptides were fractionated with high pH reversed phase after TMT-labeling. The four resulting fractions were then measured using the 2 h gradient and fragmenting the 10 most intense precursors in MS2 (dark grey line/pyramid, Figure 13). For DDR2, no residual binding could be observed for higher doses, but for other targets minimum residual binding was 0.5 and did not change compared to the other methods. Moreover, measurement time increased to at least 8 h per sample also leading to an increased number of identified kinases (181) compared to non-fractionated TMT samples.

However, identification numbers are still lower than in the label-free measurement and its 20 h.

Another option for less ratio compression is the use of a MS3 method. Peptides were isolated and fragmented for MS2 with the TMT reporter ion remaining at the fragment ion. TMT reporter ions

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were then read out in a third MS measurement (MS3) and simultaneously fragmented after isolation of up to five fragment ions (from one peptide). This measurement method is now implemented in the new generation of tribrid mass spectrometer and the samples were measured on a Fusion Lumos (Thermo Scientific, demo lab). If fragments were isolated with isolation widths of 0.7 Th for both MS2 and MS3 (MS3 2h 0.7/0.7, blue line/square, Figure 13), residual binding for EPHA2 and RIPK2 decreased similarly to that of the label-free curve, but could not improve for ZAK.

DDR2 was not identified. Lastly, fragment ions were isolated for MS3 using isolation windows dependent on the charge of the fragment (1.3 Th for 2+, 1.0 Th for 3+, 0.8 Th for 4+ and 0.7 Th for 5-7+ ions, MS3 2h multicharge, grey line/square, Figure 13). Again, residual binding of EPHA2 and RIPK2 almost decreased to zero at higher doses, resembling the curve of the label-free measurement and, therefore, providing the only suitable alternative to label-free quantification.

Reduced ratio compression in MS3 comes at the cost of identified proteins and kinases. For example, DDR2 could not be identified in these measurements. Roughly, half of the proteins identified in the label-free measurement were found in MS3 measurements and less than 150 kinases could be measured (Figure 12).

The best method was selected based on possible target identification and curve shape of selected Golvatinib targets (Figure 13). Therefore, the Kinobeads drug screen was performed using label-free quantification.

To conclude, TMT quantification could not compete with the label-free measurement. Only in the latter, more proteins and kinases were identified and targets could be determined unambiguously as residual binding completely decreased to zero. The impact of ratio compression was very high in the TMT-labeled samples. This led to underestimation of protein competition off the beads and would hamper proper annotation of previously unknown targets. Label-free quantification overall yields more proteins and kinases as well as better conditions for target identification at the cost of longer measurement time.

Figure 13: Evaluation of quantification options. Exemplary dose response curves for the selected targets DDR2, ZAK, RIPK2 and EPHA2 of Golvatinib after label-free or TMT quantification. Label-free quantification shows characteristic dose response. TMT quantification suffers from ratio compression in the MS2 acquisition mode. The impact of ratio compression is reduced in the TMT-MS3 methods.

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