High Throughput Protein Domain Elucidation by Limited Proteolysis-Mass Spectrometry Jeff Bonanno and Xia Gao Structural GenomiX, Inc.

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Presentation transcript:

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, 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

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 Domain 3 Domain 4 Domain 1Domain 2 1 Full length protein: Low yield, 2mg/L High tendency to aggregate Cannot be concentrated above 1mg/ml Domain 3 Domain4 Domain 1 ?Domain 2 4 LP construct: High yield, 30mg/L Stable overtime Concentration of 5mg/ml Protein crystallized Cterm 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 Large scale cloning, expression/solubility testing and resubmission to crystallization underway

Plans Forward Automated Proteolysis Experiment Automated Data Acquisition Automated Data Assembly Need to Automate Sample preparation Need to Automate Data Interpretation Automated Molecular Biology

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