Protein Sequence Databases

1. Protein Sequence Databases Nathan Edwards Department of Biochemistry and Mol. & Cell. Biology Georgetown University Medical Center

2. Protein Sequence Databases • Link between mass spectra and proteins • A protein’s amino-acid sequence provides a basis for interpreting • Enzymatic digestion • Separation protocols • Fragmentation • Peptide ion masses • We must interpret database information as carefully as mass spectra.

3. More than sequence… Protein sequence databases provide much more than sequence: • Names • Descriptions • Facts • Predictions • Links to other information sources Protein databases provide a link to the current state of our understanding about a protein.

4. Much more than sequence Names • Accession, Name, Description Biological Source • Organism, Source, Taxonomy Literature Function • Biological process, molecular function, cellular component • Known and predicted Features • Polymorphism, Isoforms, PTMs, Domains Derived Data • Molecular weight, pI

5. Database types

6. SwissProt • From ExPASy • Expert Protein Analysis System • Swiss Institute of Bioinformatics • ~ 515,000 protein sequence “entries” • ~ 12,000 species represented • ~ 20,000 Human proteins • Highly curated • Minimal redundancy • Part of UniProt Consortium

7. TrEMBL • Translated EMBL nucleotide sequences • European Molecular Biology Laboratory • European Bioinformatics Institute (EBI) • Computer annotated • Only sequences absent from SwissProt • ~ 10.5 M protein sequence “entries” • ~ 230,000 species • ~ 75,000 Human proteins • Part of UniProt Consortium

8. UniProt • Universal Protein Resource • Combination of sequences from • Swiss-Prot • TrEMBL • Mixture of highly curated (Swiss-Prot) and computer annotation (TrEMBL) • “Similar sequence” clusters are available • 50%, 90%, 100% sequence similarity

9. RefSeq • Reference Sequence • From NCBI (National Center for Biotechnology Information), NLM, NIH • Integrated genomic, transcript, and protein sequences. • Varying levels of curation • Reviewed, Validated, …, Predicted, … • ~ 9.7 M protein sequence “entries” • ~ 209,000 reviewed, ~ 90,000 validated • ~ 39,000 Human proteins

10. RefSeq • Particular focus on major research organisms • Tightly integrated with genome projects. • Curated entries: NP accessions • Predicted entries: XP accessions • Others: YP, ZP, AP

11. IPI • International Protein Index • From EBI • For a specific species, combines • UniProt, RefSeq, Ensembl • Species specific databases • HInv-DB, VEGA, TAIR • ~ 87,000 (from ~ 307,000 ) human protein sequence entries • Human, mouse, rat, zebra fish, arabidopsis, chicken, cow

12. MSDB • From the Imperial College (London) • Combines • PIR, TrEMBL, GenBank, SwissProt • Distributed with Mascot • …so well integrated with Mascot • ~ 3.2M protein sequence entries • “Similar sequences” suppressed • 100% sequence similarity • Not updated since September 2006 (obsolete)

13. NCBI’s nr • “non-redundant” • Contains • GenBank CDS translations • RefSeq Proteins • Protein Data Bank (PDB) • SwissProt, TrEMBL, PIR • Others • “Similar sequences” suppressed • 100% sequence similarity • ~ 10.5 M protein sequence “entries”

14. Others • HPRD • Manually curated integration of literature • PDB • Focus on protein structure • dbEST • Part of GenBank - EST sequences • Genome Sequences

15. Human Sequences • Number of Human genes is believed to be between 20,000 and 25,000

16. DNA to Protein Sequence Derived from http://online.itp.ucsb.edu/online/infobio01/burge

17. Genome Browsers • Link genomic, transcript, and protein sequence in a graphical manner • Genes, ESTs, SNPs, cross-species, etc. • UC Santa Cruz • http://genome.ucsc.edu • Ensembl • http://www.ensembl.org • NCBI Map View • http://www.ncbi.nlm.nih.gov/mapview

18. Shows many sources of protein sequence evidence in a unified display UCSC Genome Browser

19. PeptideMapper Web Service I’m Feeling Lucky

20. PeptideMapper Web Service I’m Feeling Lucky

21. Unannotated Splice Isoform

22. Accessions • Permanent labels • Short, machine readable • Enable precise communication • Typos render them unusable! • Each database uses a different format • Swiss-Prot: P17947 • Ensembl: ENSG00000066336 • PIR: S60367; S60367 • GO: GO:0003700;

23. Names / IDs • Compact mnemonic labels • Not guaranteed permanent • Require careful curation • Conceptual objects • ALBU_HUMAN • Serum Albumin • RT30_HUMAN • Mitochondrial 28S ribosomal protein S30 • CP3A7_HUMAN • Cytochrome P450 3A7

24. Description / Name • Free text description • Human readable • Space limited • Hard for computers to interpret! • No standard nomenclature or format • Often abused…. • COX7R_HUMAN • Cytochrome c oxidase subunit VIIa-related protein, mitochondrial [Precursor]

25. FASTA Format

26. FASTA Format • > • Accession number • No uniform format • Multiple accessions separated by | • One line of description • Usually pretty cryptic • Organism of sequence? • No uniform format • Official latin name not necessarily used • Amino-acid sequence in single-letter code • Usually spread over multiple lines.

27. Organism / Species / Taxonomy • The protein’s organism… • …or the source of the biological sample • The most reliable sequence annotation available • Useful only to the extent that it is correct • NCBI’s taxonomy is widely used • Provides a standard of sorts; Heirachical • Other databases don’t necessarily keep up • Organism specific sequence databases starting to become available.

28. Buffalo rat Gunn rats Norway rat Rattus PC12 clone IS Rattus norvegicus Rattus norvegicus8 Rattus norwegicus Rattus rattiscus Rattus sp. Rattus sp. strain Wistar Sprague-Dawley rat Wistar rats brown rat laboratory rat rat rats zitter rats Organism / Species / Taxonomy

29. Controlled Vocabulary • Middle ground between computers and people • Provides precision for concepts • Searching, sorting, browsing • Concept relationships • Vocabulary / Ontology must be established • Human curation • Link between concept and object: • Manually curated • Automatic / Predicted

30. Controlled Vocabulary

31. Controlled Vocabulary

32. Controlled Vocabulary

33. Controlled Vocabulary

34. Controlled Vocabulary

35. Controlled Vocabulary

36. Controlled Vocabulary

37. Controlled Vocabulary

38. Controlled Vocabulary

39. Controlled Vocabulary

40. Controlled Vocabulary

41. Controlled Vocabulary

42. Controlled Vocabulary

43. Controlled Vocabulary

44. Ontology Structure • NCBI Taxonomy • Tree • Gene Ontology (GO) • Molecular function • Biological process • Cellular component • Directed, Acyclic Graph (DAG) • Unstructured labels • Overlapping?

45. Ontology Structure

46. Protein Families • Similar sequence implies similar function • Similar structure implies similar function • Common domains imply similar function • Bootstrap up from small sets of proteins with well understood characteristics • Usually a hybrid manual / automatic approach

47. Protein Families

48. Protein Families

49. Protein Families • PROSITE, PFam, InterPro, PRINTS • Swiss-Prot keywords • Differences: • Motif style, ontology structure, degree of manual curation • Similarities: • Primarily sequence based, cross species

50. Gene Ontology • Hierarchical • Molecular function • Biological process • Cellular component • Describes the vocabulary only! • Protein families provide GO association • Not necessarily any appropriate GO category. • Not necessarily in all three hierarchies. • Sometimes general categories are used because none of the specific categories are correct.