Tools and workflows to simplify method development for targeted MRM methods

Transcription

1 Tools and workflows to simplify method development for targeted MRM methods Nikunj Tanna Senior Scientist, Scientific Operations Waters Corporation, Milford, MA 2016 Waters Corporation 1

2 Journey of a large molecule Protein in Plasma/Serum Protein-level clean-up (optional) Purified Protein Digestion Peptides Peptide-level clean-up (optional) Purified Peptides Pick unique peptides & transitions Data LC-MS Optimize/Fine-tune MRM transitions 2016 Waters Corporation 2

3 Protein Prospector Skyline BLASTp SIM MassLynx ProteinWorks SPE 2016 Waters Corporation 3

4 Biomarker Whole Protein? Sub-unit? Human/pre-clinical? HC Isotype? CDR sequence? Therapeutic mab ANALYTE ADC Total Ab? Conjugated Ab? Payload/Linker? Modified Peptides/ Proteins Sequence change? AA modifications? 2016 Waters Corporation 4

5 2016 Waters Corporation 5

6 Tools used NCBI BLASTp Uniqueness against proteome of interest SIM Protein sequence alignment tool 2016 Waters Corporation 6

7 Workflow for finding unique tryptic peptides from therapeutic mabs Find the most similar sequences of LC/HC Protein BLAST against the NR NCBI database Align the therapeutic LC/HC sequence with the common mab sequence SIM (alignment tool from ExPASy Proteomics server) Generate tryptic peptides while maintaining the sequence alignment of LC/HC Visually identify possible unique peptides Find how unique are the un-matched tryptic peptides from therapeutic mab Protein BLAST against the NCBI database 2016 Waters Corporation 7

8 Trastuzumab BLAST Results Trastuzumab LC sequence 2016 Waters Corporation 8

9 Trastuzumab LC vs IgG1kappa 1 monkey peptide deamidation site mouse peptide human/lama peptide OK mouse IgG1 LC peptide human/mouse peptide bacterial peptide OK proteotypic peptide OK OK monkey/human peptide OK human/lama peptide OK too long (36 AA) 2016 Waters Corporation 9

10 Peptide Level Blast: IYPTNGYTR HC 2016 Waters Corporation 10

11 FINAL LIST of unique peptides Light Chain ASQDVNTAVAWYQQK (mouse peptide) LLIYSASFLYSGVPSR FSGSR Heavy Chain EVQLVESGGGLVQPGGSLR (monkey peptide) LSCAASGFNIK (mouse peptide, has Cys) DTYIHWVAR QAPGK (human/llama peptide) GLEWVAR (human/mouse peptide) IYPTNGYTR (bacterial peptide) YADSVK (human/llama peptide) FTISADSK NTAYLQMNSLR (has Met) AEDTAVYYCSR (human/llama peptide, has Cys) WGGDGFYAMDYWGQGTLVTVSSASTK (has Met and is too long: 26 AA) EEMTK (too short: 5 AA, missed cleavage) 2016 Waters Corporation 11

12 2016 Waters Corporation 12

13 Tools used Protein Prospector Precursor/product mass prediction MassLynx PIC, Cone Voltage and Collision Energy optimization Skyline 2016 Waters Corporation 13

14 Protein Prospector prediction - FTISADTSK Found and optimized Precursor MRM Fragments 2016 Waters Corporation 14

15 MassLynx Optimization - FTISADTSK Peak area Fixed CV = 35 V Peak area > > > > nm trastuzumab digest Product scan > >822.5 CE formula = m/z +3.1 y5 y6 y7 y CV (V) CE (ev) 2016 Waters Corporation 15

16 Skyline Workflow Target/Analyte sequence and matrix information In-silico digestion, peptide selection, transition prediction HRMS Data No HRMS Data Acquisition & Data Review 1 Pick best 5 MRM transitions from DDA/MS e data Precursor Precursor scan. Pick best precursor Acquisition & Data Review 1 Acquisition & Data Review 2 CE Optimization Generate base MRM method with calculated CE Acquisition & Data Review 2 Final MRM Method Pick best 5 MRM transitions from MRM data Acquisition & Data Review 3 CE Optimization Acquisition & Data Review 4 Final MRM Method 2016 Waters Corporation 16

17 Skyline Workflow SkyLine In silco generation of MRM transitions for peptides Output scouting MRM method MassLynx/Xevo TQ-XS Acquisition of MRM traces for all proposed transitions SkyLine Comparison of overlaid MRM traces, to pick optimal transitions & collision energies Output final MRM method SkyLine is developed by the MacCoss laboratory in the University of Washington MassLynx/Xevo TQ- XS Sample analysis 2016 Waters Corporation 17

18 MRM Method Creation With Skyline, importing a protein sequence elicits an in silico digestion algorithm and MRM transition prediction 2016 Waters Corporation 18

19 MRM Method Creation 2016 Waters Corporation 19

20 Sample Analysis with MassLynx 2016 Waters Corporation 20

21 MRM Method Optimization Xevo TQ-XS Transitions are optimized by collision energy and the results are visualized The optimized method can be exported automatically 2016 Waters Corporation 21

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23 Sample Preparation Optimization ProteinWorks Kits Protein level clean up (depletion, generic affinity, specific affinity)? Peptide level clean up (SPE)? 2016 Waters Corporation 23

24 ProteinWorks Kits in the Workflow Protein in Plasma/Serum Protein-level clean-up (optional) Purified Protein Pick unique peptides & transitions Digestion express Digest Kit Denaturation Reduction Alkylation Enzymatic Digestion Quench Peptides Peptide-level clean-up (optional) µelution SPE Kit Target Peptide Clean-up Purified Peptides Data LC-MS Optimize/Fine-tune MRM transitions 2016 Waters Corporation 24

25 Kit Flexibility: A Diversity of Proteins Cytochrome C Small Protein MW 12, µl sample 10 min digestion Apolipoprotein a1 Biomarker MW 28, µl sample min digestion ProteinWorks Achieves Fast Digestion Times Infliximab Biotherapeutic MW 149, µl sample 2 hour digestion 2016 Waters Corporation 25

26 Flexibility: Across different mabs & multiple plasma volumes Protein Peptide Linear fit (r 2 ) with 1/x weighting Mean % Accuracy Std. Curve Range Standard Curve Range (µg/ml) 15 µl plasma 35 µl plasma 70 µl plasma 15 µl plasma 35 µl plasma 70 plas Infliximab SINSATHYAESVK DILLTQSPAILSVSPGER FTISADTSK Trastuzumab DTYIHWVR IYPTNGYTR Bevacizumab Adalimumab STAYLQMNSLR FTFSLDTSK APYTFGQGTK NYLAWYQQKPGK Linear, precise and accurate with multiple plasma volumes for multiple mabs 2016 Waters Corporation 26

27 2016 Waters Corporation 27

28 Calibration curves and QC s 2016 Waters Corporation 28

29 Calibration curves and QC s µg/ml 2016 Waters Corporation 29

30 Acknowledgements Mary Lame Paula Orens Erin Chambers Mark Wrona Kerri Smith Yun Alelyunas Kelly Doering Useful insights from Kevin Bateman (Merck) Dan Spellman (Merck) Skyline Development Team (University of Washington) Thank you! 2016 Waters Corporation 30

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