1 / 20

A New Strategy of Protein Identification in Proteomics

This proposal outlines a new strategy for protein identification in proteomics by reducing database size and automating data transfer for faster and more reliable results. The aim is to streamline data analysis and expedite peptide identification during experiments, ultimately facilitating comprehensive protein characterization. The proposed method involves utilizing local protein databases, developing a peptide filter, and automating data transfer between different mass spectrometry stages.

gvaughan
Download Presentation

A New Strategy of Protein Identification in Proteomics

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. A New Strategy of Protein Identification in Proteomics Xinmin Yin CS Dept. Ball State Univ.

  2. Contents • Background. • Problems. • Proposal. • Conclusion.

  3. What’s Proteomics ? Use of quantitative protein-level measurement of gene expression to characterize biological process and to decipher the mechanisms of gene expression control.

  4. What’s Proteomics ? DNA transcription RNA translation PROTEIN

  5. Current Research in Proteomics Quantitative measurement of proteins expressed in a cell * protein identification * protein quantification

  6. Experimental Flow Chart of Protein Identification cell mass & sequence proteins peptides data processing

  7. Schematic of MALDI MS/MS Laser Detector1 E1 MS1 E2 Peptides MS2 Detector2 Matrix Assisted Laser-induced Desorption Ionization

  8. An Example of MALDI MS/MS Spectrum

  9. Problem of Scaling up MALDI MS/MS to Proteomics Number of peptides is huge Human genome (~60,000 proteins) 2.6 X 106 peptides It will take THREE MONTHS to identify all proteins in a human cell.

  10. My Proposal To develop a new data analysis method • Avoid using MS2 if a peptide can be identified in MS1. • Reduce size of peptide database during data analysis

  11. Facts of MALDI MS/MS Experiment • 40% peptides are unique in mass when mass accuracy of MALDI is better than 10ppm. • Analyzing MS1 spectrum is much easier than analyzing MS2 spectrum. • It takes about 1 to 2 min for analysis of a single MS2 spectrum through database.

  12. My Proposal • Using local protein database for data analysis. • Developing a peptide filter. • Automating data transfer from MS1 to MS2

  13. Local Protein Database PURPOSE: 1. Make peptide database small according to experimental methods 2. Do online data processing • Download protein database from public sites. • Digest proteins in computer. • Select peptides according experimental methods, and store them in memory. • Calculate peptide chemical modification.

  14. Generating Peptide Database Protein Database Peptide Database Enzyme Digestion Each protein can produce 30 ~ 100 peptides

  15. Peptide Filter PURPOSE: 1. Do online data processing 2. Reduce peptides database size 2. Reduce number of peptides passed to MS2 • Identify peptide by mass alone. • Sort identified peptides according to proteins. • Delete rest peptides of the identified protein from peptide database. • Pass unidentified mass information to MS2.

  16. Identifying Peptide by Mass Alone Mth Mexp Npep M + + M = Mth – Mexp If (M < ) Npep++ Npep: number of mass matched peptides : mass accuracy of MS1

  17. Reducing Size of Peptide Database If (Npep == 1) Peptide is unique; Deleting peptides from the same protein Else Send peptide to MS2 for sequence information.

  18. F L O W C H A R T

  19. Program Design Computer Language: C++ Classes: Protein Peptide Linked list

  20. Conclusion 1. My program will generate a list of peptides from the protein database. 2. Peptide identification is carried out while doing experiment. 3. Data analysis time will be significantly reduced. 4. This program will make identification of proteins from a cell possible and reliable.

More Related