protein sequence databases

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

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Protein Sequence Databases. Nathan Edwards Department of Biochemistry and Mol. & Cell. Biology Georgetown University Medical Center. Protein Sequence Databases. Link between mass spectra and proteins A protein’s amino-acid sequence provides a basis for interpreting Enzymatic digestion - PowerPoint PPT Presentation

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Page 1: Protein Sequence Databases

Protein Sequence DatabasesProtein Sequence Databases

Nathan EdwardsDepartment of Biochemistry and Mol. & Cell. BiologyGeorgetown University Medical Center

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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.

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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.

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Much more than sequence

Names• Accession, Name, Description

Biological Source• Organism, Source, Taxonomy

LiteratureFunction

• Biological process, molecular function, cellular component

• Known and predictedFeatures

• Polymorphism, Isoforms, PTMs, DomainsDerived Data

• Molecular weight, pI

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Database types

Curated• Swiss-Prot• UniProt• RefSeq NP

Translated• TrEMBL• RefSeq XP, ZP

Omnibus• NCBI’s nr• MSDB• IPI

Other• PDB• HPRD• EST• Genomic

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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

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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

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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

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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

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RefSeq

• Particular focus on major research organisms• Tightly integrated with genome projects.

• Curated entries: NP accessions• Predicted entries: XP accessions• Others: YP, ZP, AP

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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

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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)

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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”

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Others

• HPRD• Manually curated integration of literature

• PDB• Focus on protein structure

• dbEST• Part of GenBank - EST sequences

• Genome Sequences

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Human Sequences

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

SwissProt ~ 20,000

RefSeq ~ 39,000

TrEMBL ~ 75,000

IPI-HUMAN ~ 87,000

MSDB ~130,000

nr ~230,000

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DNA to Protein Sequence

Derived from http://online.itp.ucsb.edu/online/infobio01/burge

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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

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UCSC Genome Browser

• Shows many sources of protein sequence evidence in a unified display

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PeptideMapper Web Service

I’m Feeling Lucky

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PeptideMapper Web Service

I’m Feeling Lucky

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Unannotated Splice Isoform

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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;

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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

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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]

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FASTA Format

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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.

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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.

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Organism / Species / Taxonomy

• 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

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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

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Controlled Vocabulary

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Controlled Vocabulary

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Controlled Vocabulary

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Controlled Vocabulary

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Controlled Vocabulary

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Controlled Vocabulary

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Controlled Vocabulary

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Controlled Vocabulary

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Controlled Vocabulary

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Controlled Vocabulary

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Controlled Vocabulary

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Controlled Vocabulary

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Controlled Vocabulary

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Controlled Vocabulary

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Ontology Structure

• NCBI Taxonomy• Tree

• Gene Ontology (GO)• Molecular function• Biological process• Cellular component• Directed, Acyclic Graph (DAG)

• Unstructured labels• Overlapping?

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Ontology Structure

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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

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Protein Families

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Protein Families

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Protein Families

• PROSITE, PFam, InterPro, PRINTS• Swiss-Prot keywords

• Differences:• Motif style, ontology structure, degree of

manual curation• Similarities:

• Primarily sequence based, cross species

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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.

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Protein Family / Gene Ontology

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Sequence Variants

• Protein sequence can vary due to• Polymorphism• Alternative splicing• Post-translational modification

• Sequence databases typically do not capture all versions of a protein’s sequence

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Sequence Variants

Swiss-Prot; a curated protein sequence database which strives to provide a high level of annotation (such as the description of the function of a protein, its domains structure, post-translational modifications, variants, etc.), a minimal level of redundancy and high level of integration with other databases

- Swiss-Prot web site front page

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Sequence Variants

b) Minimal redundancy

Many sequence databases contain, for a given protein sequence, separate entries which correspond to different literature reports. In Swiss-Prot we try as much as possible to merge all these data so as to minimize the redundancy of the database. If conflicts exist between various sequencing reports, they are indicated in the feature table of the corresponding entry.

- Swiss-Prot User Manual, Section 1.1

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Sequence Variants

IPI provides a top level guide to the main databases that describe the proteomes of higher eukaryotic organisms. IPI:

1. effectively maintains a database of cross references between the primary data sources

2. provides minimally redundant yet maximally complete sets of proteins for featured species (one sequence per transcript)

3. maintains stable identifiers (with incremental versioning) to allow the tracking of sequences in IPI between IPI releases.

- IPI web site front page

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Swiss-Prot Variant Annotations

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Swiss-Prot Variant Annotations

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Swiss-Prot Variant Annotations

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Peptides to Proteins

Nesvizhskii et al., Anal. Chem. 2003

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Peptides to Proteins

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Peptides to Proteins

• A peptide sequence may occur in many different protein sequences• Variants, paralogues, protein families

• Separation, digestion and ionization is not well understood

• Proteins in sequence database are extremely non-random, and very dependent

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Omnibus Database Redundancy Elimination

• Source databases often contain the same sequences with different descriptions

• Omnibus databases keep one copy of the sequence, and • An arbitrary description, or• All descriptions, or• Particular description, based on source preference

• Good definitions can be lost, including taxonomy

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Description Elimination

• gi|12053249|emb|CAB66806.1| hypothetical protein [Homo sapiens]

• gi|46255828|gb|AAH68998.1| COMMD4 protein [Homo sapiens]

• gi|42632621|gb|AAS22242.1| COMMD4 [Homo sapiens]

• gi|21361661|ref|NP_060298.2| COMM domain containing 4 [Homo sapiens]

• gi|51316094|sp|Q9H0A8|COM4_HUMAN COMM domain containing protein 4

• gi|49065330|emb|CAG38483.1| COMMD4 [Homo sapiens]

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Description Elimination

• gi|2947219|gb|AAC39645.1| UDP-galactose 4' epimerase [Homo sapiens]

• gi|1119217|gb|AAB86498.1| UDP-galactose-4-epimerase [Homo sapiens]

• gi|14277913|pdb|1HZJ|B Chain B, Human Udp-Galactose 4-Epimerase: Accommodation Of Udp-N- Acetylglucosamine Within The Active Site

• gi|14277912|pdb|1HZJ|A Chain A, Human Udp-Galactose 4-Epimerase: Accommodation Of Udp-N- Acetylglucosamine Within The Active Site

• gi|2494659|sp|Q14376|GALE_HUMAN UDP-glucose 4-epimerase (Galactowaldenase) (UDP-galactose 4-epimerase)

• gi|1585500|prf||2201313AUDP galactose 4'-epimerase

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Description Elimination

• gi|4261710|gb|AAD14010.1| chlordecone reductase [Homo sapiens]

• gi|2117443|pir||A57407 chlordecone reductase (EC 1.1.1.225) / 3alpha-hydroxysteroid dehydrogenase (EC 1.1.1.-) I [validated] – human

• gi|1839264|gb|AAB47003.1| HAKRa product/3 alpha-hydroxysteroid dehydrogenase homolog [human, liver, Peptide, 323 aa]

• gi|1705823|sp|P17516|AKC4_HUMAN Aldo-keto reductase family 1 member C4 (Chlordecone reductase) (CDR) (3-alpha-hydroxysteroid dehydrogenase) (3-alpha-HSD) (Dihydrodiol dehydrogenase 4) (DD4) (HAKRA)

• gi|7328948|dbj|BAA92885.1| dihydrodiol dehydrogenase 4 [Homo sapiens]

• gi|7328971|dbj|BAA92893.1|dihydrodiol dehydrogenase 4 [Homo sapiens]

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Summary

• Protein sequence databases should be interpreted with as much care as mass spectra

• Protein sequences come from genes• Use controlled vocabularies• Understand the structure of ontologies• Take advantage of computational predictions• Look for sequence variants• Peptides to proteins not as simple as it

seems• Be careful with omnibus databases