Ming Luo, Ph.D. University of Alabama at Birmingham March 29, 2004 NIH

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Presentation transcript:

Ming Luo, Ph.D. University of Alabama at Birmingham March 29, 2004 NIH Systematic Identification of Protein Domains for Structure Determination Ming Luo, Ph.D. University of Alabama at Birmingham March 29, 2004 NIH

Current Progress on C. elegans Proteins Selected ORFs Cloned Expressed Soluble (1 L) Purified * (6 L) 4/7/2003 14,440 2,342 1,369 268 110 3/7/2004 15,556 7,326 3,218 503 189 * Unique ORFs, each expressed and purified multiple times.

Domain Identification Markley Methods 1. Conserved Sequence (e.g. Pfam) Spontaneous Degradation 3. Proteolysis 4. Functional Data

Predict Domains by Sequence 2-H9 1 356 29 286 346 55 320 11-D11 647 323 475 28-C5 313 25 273 11-E3 151 304 11-D5 500 41 436 20-D7 278 283 Program used: SMART (http://smart.embl-heidelberg.de/) Schultz et al. (1998) Proc. Natl. Acad. Sci. USA 95, 5857-5864 Letunic et al. (2002) Nucleic Acids Res 30, 242-244 Four expressed One soluble None purified

Spontaneous Degradation 1F11 76F6 3D2 Purified protein samples were stored at 4°C over one month.

Mass Spectrometry Solution Specimen 3D2 Eluted from Gel 18H1

MS + AA Sequencing 76F6 3D2 21279 18-210 GSQSTSL 261 MS 19695 140-309 AA Code SAIKD 140-309 379 21279 GSQSTSL 18-210 261 76F6 3D2

Proteolysis Trypsin Digestion Min 0 5 10 15 20 60 MW 9H3 Trypsin Digestion Trypsin:protein 1:200, 10 mM Tris, pH7.6, 37°C. 2. N-terminal Sequencing after transfer to PVDF ELTSAEK--- 3. Mass Spectrometry using solution mixture 19277 17774 Result: 59-212

Functional Data 1D10 Predicted Signal Peptide parameters from Soren Brunak's SignalP server: Signal peptide predicted: HMM-cleavage prediction: MPKLPLLLSFPLLFFASFAYA--(22)DEDFVT ANN-cleavage prediction: MPKLPLLLSFPLLFFASFAYA--(22)DEDFVT 79D4

SUMMARY

CONCLUSIONS Smaller structural domains are most suitable for HTP structure determination. Domains experimentally identified from folded proteins are most reliable. Spontaneously occurring or limited proteolysis, followed by N-terminal sequencing and mass spectrometry, are most efficient approaches.

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