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High Throughput Protein Domain Elucidation by Limited Proteolysis-Mass Spectrometry Jeff Bonanno and Xia Gao Structural GenomiX, Inc Outline • Overview of SGX technology platform • Overview of NY and SGX research consortium (NYSGXRC) • Mass Spectrometry applications – Integration into SGX technology platform • High Throughput Limited Proteolysis Mass Spectrometry SGX Technology Platform Overview of NY and SGX Research Consortium (NYSGXRC) • Vision The NYSGXRC will establish a cost-effective, highthroughput X-ray crystallography platform that serves as a model for the structural biology laboratory of the future. • Mission To develop and use the technology for highthroughput structural and functional studies of proteins • www.nysgxrc.org NYSGXRC Members • Albert Einstein College of Medicine (AECOM) • Brookhaven National Laboratory (BNL) • Columbia University (CU) • Structural GenomiX, Inc. (SGX) • Sloan Kettering Institute (SKI) • University of California at San Diego (UCSD) • University of California at San Francisco (UCSF) MS Analysis from Gene Expression to Protein Purification • Molecular biology – Verify expression and protein integrity – Provide domain boundary information • Fermentation – Determine heavy atom incorporation – Monitor progression • Purification – QA/QC on final pools – Characterize post-translational modifications – Fraction analysis to provide guidance Methods for Domain Elucidation • Bioinformatic approach – Sequence alignment, e.g. BLAST, Pfam – Secondary structure prediction – Homology modeling • Limited Proteolysis MS – Probing protein structure in solution – Provide termini information of protein functional domain(s) – Provide information on solvent accessible or disordered loop regions (Cohen et al., 1995, Cohen and Chait, 1996, Marcotrigiano et al., 1997, Lee et al., 1996, Xie et al., 1996, Cabral, et al., 1998, Zhang et al., 1997) • Hydrogen/Deuterium Exchange MS (Pantazatos et al., 2004) Principle of Limited Proteolysis-Mass Spectrometry A Successful Example 1 Domain 1 Domain 2 Domain 3 Domain 4 Cterm Full length protein: Low yield, 2mg/L High tendency to aggregate Cannot be concentrated above 1mg/ml 4 Domain 1 Domain ? 2 LP construct: High yield, 30mg/L Stable overtime Concentration of 5mg/ml Protein crystallized Domain 3 Domain4 Cterm - 76 Proteolysis Experiment Conditions • Proteases – Trypsin, Lys-C, Chymotrypsin and GluC • Buffer condition – PH~8, salt and detergent if necessary--Protein native condition • Protein concentration – ~2mg/ml • Time points – 5min, 10min, 30min, 1h, 2hrs and 4hrs. • Capacity – Eight proteins per experiment Sample Preparation for Automated MALDI-MS Analysis • “Thin-Layer” Sample Preparation (Cadene and Chait, 2000) • – High homogeneity offers high success rate for automated data acquisition. Better than 95% attempts result in satisfactory MS spectrum. – Thin-Layer method affords high detection sensitivity, < 10 fmoles. Automated Data Acquisition by Sequence Control from ABI Data Interpretation with PAWS Data Assembly by Digests Reader in Batch Mode Throughput • Total proteolysis experiments: 270 • Total number of data sets acquired: 250 • Total number of data sets analyzed: 210 • Duration of this endeavor: six months • Total FTEs: ~1.0 on average Representative Results • Summary of MS analysis of crystallized proteins which diffract poorly—Three examples – Proteins showed stability toward proteolysis – Removal of His6-tag is recommended – Removal of structural micro-heterogeneity necessary NYSGXRC ESI-MS Broad peak, undefined modifications T763 C-term N-term internal Clv. Seq. Alignment intact T774 BME adduct, 50% intact No truncation up removal of Histag to residue 28 No T1400 single peak, right mass removal of Histag intact 1-28, not well conserved 128-133, not well yes, R[127] conserved • Large scale cloning, expression/solubility testing and resubmission to crystallization underway Plans Forward Automated Automated Automated Automated Proteolysis Data Data Molecular Experiment Acquisition Assembly Biology Need to Need to Automate Sample Automate Data Interpretation preparation Acknowledgements SGX • Julie A. Reynes, Michelle Buchanan and Chau Thai • Curtis Marsh and Boris Laubert • Ken Schwinn and Michael Sauder • Stephen K. Burley • Spencer Emtage Rockefeller University • Brian T. Chait and Martine Cadene Tecan • Brian Smith NIH NIGMS PSI