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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
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High Throughput Protein Domain Elucidation by Limited Proteolysis-Mass SpectrometryJeff 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
Overview of NY and SGX Research Consortium (NYSGXRC) • Vision • The NYSGXRC will establish a cost-effective, high-throughput 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 high-throughput 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)
A Successful Example Domain 1 Domain 2 Domain 3 Domain 4 Cterm 1 Full length protein: Low yield, 2mg/L High tendency to aggregate Cannot be concentrated above 1mg/ml Domain 1 ? Domain 2 Domain 3 Domain4 4 Cterm - 76 LP construct: High yield, 30mg/L Stable overtime Concentration of 5mg/ml Protein crystallized
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
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 • Large scale cloning, expression/solubility testing and resubmission to crystallization underway
Plans Forward Automated Proteolysis Experiment Automated Data Acquisition Automated Data Assembly Automated Molecular Biology Need to Automate Sample preparation Need to Automate Data Interpretation
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