EBI is an Outstation of the European Molecular Biology Laboratory. Alex Mitchell InterPro team...

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EBI is an Outstation of the European Molecular Biology Laboratory. Alex Mitchell InterPro team [email protected] Using InterPro for functional analysis of protein sequences

Transcript of EBI is an Outstation of the European Molecular Biology Laboratory. Alex Mitchell InterPro team...

EBI is an Outstation of the European Molecular Biology Laboratory.

Alex MitchellInterPro [email protected]

Using InterPro for functional analysis of protein sequences

Why do we need predictive annotation tools?

• Given a set of uncharacterised sequences, we usually want to know:

– what are these proteins; to what family do they belong?

– what is their function; how can we explain this in structural terms?

Pairwise alignment approaches (e.g., BLAST)

Pairwise alignment approaches (e.g., BLAST)

• Good at recognising similarity between closely related sequences

• Perform less well at detecting divergent homologues

Pairwise alignment approaches (e.g., BLAST)

The protein signature approach

• We can then use these models to infer relationships with previously characterised sequences

• This is the approach taken by protein signature databases

• They go about this in 3 different ways...

• Alternatively, we can model the conservation of amino acids at specific positions within a multiple sequence alignment, seeking ‘patterns’ across closely related proteins

Protein signature methods

(patterns)

(fingerprints)

(profiles & HMMs)

Sequencefeatures

Domains

Families

What are protein signatures?

Multiple sequence alignment

Protein family/domainBuild model

Search

Mature model

ITWKGPVCGLDGKTYRNECALL

AVPRSPVCGSDDVTYANECELK

UniProt

Significant match

Protein analysis

Full domain alignment methods

Single motif methods

Multiple motif methods

Regex patterns (PROSITE)

Profiles (Profile Library)

HMMs (Pfam)

Identity matrices (PRINTS)

Diagnostic approaches (sequence-based)

Patterns

Extract pattern sequencesxxxxxxxxxxxxxxxxxxxxxxxx

Sequence alignment

MotifDefine pattern

Pattern signature

C-C-{P}-x(2)-C-[STDNEKPI]-x(3)-[LIVMFS]-x(3)-CBuild regular expression

PS00000

Patterns

Patterns are mostly directed against functional residues: active sites, PTM, disulfide bridges, binding sites

• Anchoring the match to the extremity of a sequence<M-R-[DE]-x(2,4)-[ALT]-{AM}

• Some aa can be forbidden at some specific positions which can help to distinguish closely related subfamilies

• Short motifs handling - a pattern with very few variability and forbidden positions, can produce significant matches e.g. conotoxins: very short toxins with few conserved cysteines C-{C}(6)-C-{C}(5)-C-C-x(1,3)-C-C-x(2,4)-C-x(3,10)- C

Drawbacks

• Simple but less powerful

Advantages

Fingerprints

Sequence alignment

Correct order

Correct spacing

Motif 2 Motif 3Motif 1Define motifs

Fingerprint signature 1 2 3

PR00000

Extract motif sequences

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Weight matrices

The significance of motif context

order

interval

• Identify small conserved regions in proteins

• Several motifs characterise family

• Offer improved diagnostic reliability over single motifs by virtue of the biological context provided by motif neighbours

Profiles & HMMs

Sequence alignment

Entire domainDefine coverage

Whole protein

Use entire alignment for domain or protein xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

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Build model Models insertions and deletions

Profile or HMM signature

• PROSITE domains: high quality manually curated seeds (using biologically characterized UniProtKB/Swiss-Prot entries), documentation and annotation rules. Oriented toward functional domain discrimination.

• HAMAP families: manually curated bacterial, archaeal and plastid protein families (represented by profiles and associated rules), covering some highly conserved proteins and functions.

PROSITE and HAMAP profiles:a functional annotation perspective

HMM databases

Sequence-based

• PIR SUPERFAMILY: families/subfamilies reflect the evolutionary relationship

• PANTHER: families/subfamilies model the divergence of specific functions

• TIGRFAM: microbial functional family classification

• PFAM : families & domains based on conserved sequence

• SMART: functional domain annotation

Structure-based

•SUPERFAMILY : models correspond to SCOP domains

• GENE3D: models correspond to CATH domains

Why we created InterPro

By uniting the member databases, InterPro capitalises on their individual strengths, producing a powerful diagnostic tool & integrated database

– to simplify & rationalise protein analysis

– to facilitate automatic functional annotation of uncharacterised proteins

– to provide concise information about the signatures and the proteins they match, including consistent names, abstracts (with links to original publications), GO terms and cross-references to other databases

InterPro

Structuraldomains

Hidden Markov Models Finger-Prints

Profiles Patterns

Functional annotation of families/domains Protein features 

(sites)

InterPro integration process

Member databases

+ annotation

Proteinsignatures

InterPro

InterPro Entry

Adds extensive annotation

Links to other databases

Structural information and viewers

Groups similar signatures together

Adds extensive annotation

Links to other databases

Hierarchical classification

Interpro hierarchies: Families

FAMILIES can have parent/child relationships with other Families

Parent/Child relationships are based on:

• Comparison of protein hits

child should be a subset of parent

siblings should not have matches in common

• Existing hierarchies in member databases

• Biological knowledge of curators

Interpro hierarchies: Domains

DOMAINS can have parent/child relationships

with other domains

Domains and Families may be linked through Domain Organisation

Hierarchy

InterPro Entry

Adds extensive annotation

Links to other databases

Structural information and viewers

Groups similar signatures together

Adds extensive annotation

Links to other databases

InterPro Entry

Adds extensive annotation

Links to other databases

Structural information and viewers

Groups similar signatures together

Adds extensive annotation

Links to other databases

The Gene Ontology project provides a controlled vocabulary of terms for

describing gene product characteristics

InterPro Entry

Adds extensive annotation

Links to other databases

Structural information and viewers

Groups similar signatures together

Adds extensive annotation

Links to other databases

UniProt

KEGG ... Reactome ... IntAct ...

UniProt taxonomy

PANDIT ... MEROPS ... Pfam clans ...

Pubmed

InterPro Entry

Adds extensive annotation

Links to other databases

Structural information and viewers

Groups similar signatures together

Adds extensive annotation

Links to other databases

PDB 3-D Structures

SCOP Structural domains

CATH Structural domain classification

Searching InterPro

Searching InterPro

Protein family membership

Domain organisation

Domains, repeats& sites

GO terms

Searching InterPro

Searching InterPro

Interactive:http://www.ebi.ac.uk/Tools/pfa/iprscan/

Webservice (SOAP and REST):http://www.ebi.ac.uk/Tools/webservices/services/pfa/iprscan_resthttp://www.ebi.ac.uk/Tools/webservices/services/pfa/iprscan_soap

Downloadable:ftp://ftp.ebi.ac.uk/pub/software/unix/iprscan/

InterProScan access

Searching InterPro

Searching InterPro:

BioMart

• Large volumes of data can be queried efficiently

• The interface is shared with many other bioinformatics resources

• It allows federation with other databases:

PRIDE (mass spectrometry-derived proteins and peptidesREACTOME (biological pathways)

BioMart Search

BioMart allows more powerful and flexible queries

BioMart Search

1) Choose Dataseta. Choose InterPro BioMart

BioMart Search

1) Choose Dataseta. Choose InterPro BioMart

b. Choose InterPro entries or protein matches

BioMart Search

2) Choose FiltersSearch specific entries, signatures or proteins

BioMart Search

2) Choose Filters e.g. Filter by specific proteins

BioMart Search

3) Choose Attributes What results you want

BioMart Search

4) Choose additional Dataset (optional) This is where you link results to Pride and Reactome

BioMart Search Results

User manual

HTML = web-formatted tableCSV = comma-separated valuesTSV = tab-separated valuesXLS = excel spreadsheet

Click to view results