1 / 20

Protein World

Protein World. SARA 12-12-2002 Amsterdam Tim Hulsen. Genome sequencing. Since 1995: sequencing of complete ‘genomes’ (DNA): A/C/G/T order ACGTCATCGTAGCTAGCTAGTCGTACGTATG TGCAGTAGCATCGATCGATCAGCATGCATAC

clint
Download Presentation

Protein World

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. Protein World SARA 12-12-2002 Amsterdam Tim Hulsen

  2. Genome sequencing • Since 1995: sequencing of complete ‘genomes’ (DNA): A/C/G/T order ACGTCATCGTAGCTAGCTAGTCGTACGTATG TGCAGTAGCATCGATCGATCAGCATGCATAC • At this moment more than 80 genomes have been sequenced and published, of all kinds of organisms: • Animals • Plants • Fungi • Bacteria

  3. Genomes  Proteins • ‘Transcription’ and ‘translation’ of specific regions of the genome leads to proteins, consisting of twenty types of ‘amino acids’: ATG ACG CTG AGC TGC GGA CGT TGA -> TLSCGR • Proteins are responsible for all kinds of life processes • All the proteins that can be produced in an organism together are called the ‘proteome’ • Sequence comparisons make possible the classification of proteins

  4. Protein families • e.g. The GPCR family: • Sequence comparison helps in predicting the function of new proteins

  5. Determining protein functions • Function of 40-50% of the new proteins is unknown • Understanding of protein functions and relationships is important for: • Study of fundamental biological processes • Drug design • Genetic engineering

  6. Sequence comparison • Smith-Waterman dynamic programming algorithm (1981): calculates similarity/distance between two sequences: Query ---PLIT-LETRESV- Subject NEQPKVTMLETRQTAD (bold=similar) • Results in a SW-score that is a measure for how similar the two sequences are to each other • Disadvantage: score is dependent of length • After the alignments, the proteins are ‘clustered’ (divided into families) according to their similarity

  7. Existent databases • Domain-based clusterings: Prosite, Pfam, ProDom, Prints, Domo, Blocks • Protein-based clusterings: ProtoMap, COGs, Systers, PIR, ClusTr • Structural classifications: SCOP, CATH, FSSP Why should there be another database?

  8. Another method • Enhanced Smith-Waterman algorithm: Monte-Carlo evaluation (Lipman et al., 1984) • How big is the chance that two sequences are similar but not related? • One of the two sequences is randomized and recalculated (200 times). Randomization leads to sequences with the same length and the same composition, but different order • Method leads to calculation of the Z-value: S(A,B) - µ Z(A,B) = ------------------- σ

  9. Advantages • The obtained Z-value is a very reliable measure for sequence, compared to SW-score: • SW-score is dependent of length, Z-value is not • Amino acid bias does not affect the Z-value • Independent of the database size • Easier updating of the database, without a total recalculation

  10. Disadvantage • LOTS of calculation time needed, especially when all proteins in all proteomes are compared to each other (“all-against-all”)!  SARA

  11. SARA calculation • Proteomes of 82 organisms compared ‘all-against-all’ with the use of the Monte Carlo algorithm: more than 400,000 proteins! • 21,600 CPU days (~520,000 CPU hours) • = 21,600 PCs running parallel over 24 hours / 1 PC running for ~ 60 years • Using supercomputer TERAS (1024-CPU SGI Origin 3800) at SARA: less than two months!

  12. Parties involved • Gene-IT (Paris, France) • SARA (Amsterdam, the Netherlands) • CMBI (Nijmegen, the Netherlands) • Organon (Oss, the Netherlands) • EBI (Hinxton, UK)

  13. Supporting parties • Financed by NCF, foundation in support of supercomputing • Under the auspices of BioASP, the new Dutch knowledge and service center for Bioinformatics

  14. Results available through BioASP • http://www.bioasp.nl • Log in and click on links ‘Research’ and ‘Protein World’: 1 2

  15. Results available through BioASP • Organism selection screen:

  16. Results available through BioASP • Results screen:

  17. Results available through BioASP • Alignment screen:

  18. Conclusions • Currently the most comprehensive and most accurate data-set of protein comparisons • A start for a maintainable and unique database of all proteins currently known • A rich data-source for clustering, data-mining and orthology determination

  19. Orthology determination • Orthologs: genes/proteins in different species that derive from a common ancestor • Orthologs often have the same function • Interesting! Information from other species could help in annotating a protein

  20. Thank you for your attention Any questions?

More Related