Identification of Protein Domains

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Identification of Protein Domains
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Orthologs and Paralogs

• Describing evolutionary relationships among genes
  (proteins)
• Two major ways of creating homologous genes is
  gene duplication and speciation.
• Homology not sufficiently well-defined Therefore
  additional terms are used

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• Orthologs are two genes from two different
  species that derive from a single gene in the
  last common ancestor of the species.

ortho
para

• Paralogs are genes that derive from a single gene
  that was duplicated within a genome.

ortho
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Co-orthologs are paralogs produced by
duplications of orthologs subsequent to a given
speciation event.
co-ortho
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Inparalogs are paralogs in a given lineage
that all evolved by gene duplications that
happened after the speciation event.
in-para
in-para
out-para

• Outparalogs are paralogs in the given lineage
  that evolved by gene duplications that happened
  before the speciation event

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Orthologs and Paralogs

• Orthologs - evolutionary functional
  counterparts in different species
• Inparalogs important for detecting
  lineage-specific adaptations

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Proteins

• Rapidly growing databases of protein sequences
  due to genome sequencing projects.
• Many new proteins belong to protein families with
  known functions, (significant sequence
  similarity).
• Only a small fraction of known proteins have
  functions determined by experiment.
• Databases providing computational sequence
  analysis allow us to classify new proteins to
  known families, and thus determine their function.

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Protein Domains

• A domain is an independent structural unit which
  can be found alone or in conjunction with other
  domains or repeats.
• Module mobile domain.
• Different domains have distinct functions.
• Many eukaryotic proteins have multiple domains.

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Protein Domains
PX domain with ligand
SH3 domain with ligand
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Identifying Protein Domains

• Problems
• Defining the members of each family.
• Building multiple alignments of the members.
• Finding the boundaries of the domain.

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Identifying Protein Domains

• Little structural data ? identification by
  sequence analysis.

• Even when the structure of the domain is not
  known it may be possible to define its boundaries
  from sequence alone.

• Sequence characterization of families -
  determine 3D structure and molecular functions.

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Identifying Protein Domains
Motif matches are often useful to
indicate functional sites, however

• They do not give a clear picture of the domain
  boundaries.
• Lack sensitivity.

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Identifying Protein Domains

• Automatic methods
• Fast, effective, deals with a lot of information.
• Might fragment domain families.
• Might cause fusion of domain families.
• Manual methods
• Knowledge of protein experts is put to use.
• Slow, require a lot of manpower.

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SMART (Simple Modular Architecture Research
Tool)

• Web-based resource used for
• rapid annotation of protein domains.
• analysis of domain architectures.

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Domain Architecture
Protein PA-3427CG
Species Drosophila melanogaster
Protein ENSMUSP00000023109
Species Mus musculus
Protein ENSANGP00000009529
Species Anopheles gambiae
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SMART (Simple Modular Architecture Research Tool)

• There are over 600 domain families.
• Provides information about
• function .
• subcellular localization.
• phyletic distribution.
• tertiary structure.
• Based on HMMs (Hidden Markov Models).

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SMART (Simple Modular Architecture Research Tool)

• HMM based on seed alignment.
• Threshold values used to determine homology of
  domains.

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SMART (Simple Modular Architecture Research Tool)

• Alignments of proteins by
• Minimize insertions/deletions in conserved
  alignment blocks.
• Optimize amino acid property conservation.
• Closing unnecessary gaps.
• Gapped alignments prefered over ungapped ones
• prediction of domain boundaries.
• greater information content.
• Alignment of entire structural domains.

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PROSITE - database of protein families and
domains

• Database of biologically significant sites and
  patterns. Contains 1,609 profiles.
• Pattern conserved sequence of a few amino
  acids.
• Identifies to which known family of proteins (if
  any) the new sequence belongs.
• Used to determine the function of uncharacterized
  proteins translated from genomic or cDNA
  sequences.

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PROSITE - database of protein families and domains

• A protein too distant from any other to detect
  its resemblance by overall sequence alignment,
  can be classified according to a Pattern.
• Patterns arise because of requirements of binding
  sites that impose very tight constraint on the
  evolution of portions of the protein.

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PROSITE how is a pattern developed ?

• As short as possible.
• Detects all/most sequences it describes.
• As little false results as possible.

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PROSITE how is a pattern developed ?

• First study reviews on a protein family.
• Then build alignment table with particular
• attention to residues and regions important to
• the biological function of that family.
• - Enzyme catalytic sites.
• Prostethic group attachment sites (heme).
• Amino acids involved in binding a metal ion.
• Cysteines involved in disulfide bonds.
• - Regions involved in binding a molecule
  (ADP/ATP, GDP/GTP, calcium, DNA, etc.) or another
  protein.

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PROSITE steps in the development of a pattern

• Finding a core pattern 4-5 biologically
  significant residues.
• Test the pattern on a large database.
• If lucky there is correlation in this region
  which indicates a good pattern.
• Mostly, there is no correlation
• Gradually increase the size of the pattern.
• search over other patterns.

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PROSITE An example
This pattern is small and would probably pick up
too many false positive results

• ALRDFATHDDF
• SMTAEATHDSI
• ECDQAATHEAS

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• Patterns - small regions, high sequence
  similarity.

• Profiles characterize a protein family or
  domain over its entire length.

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Research Finding new domain familiesAutomatic
methods

• The team started with 107 nuclear domains.
• Using SMART - get all proteins with at least one
  of these domains, characterize their complete
  domain structure.
• Regions not annotated using known SMART domain
  models were extracted with their domain context.

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Finding new domain families Automatic methods

• Grouping proteins by region similarity.
• Finding homologs using PSI-BLAST on longest of
  every group (Threshold E-value
• Finding domain organization via SMART.
• Homologous regions candidates for a novel
  domain family.

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Finding new domain families
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Finding new domain families Manual confirmation

• Different context novel module family.
• Proteins with nuclear AND extracellular domains
  excluded.
• Multiple alignments and known locations of
  domains definition of domains borders.
• Automatic searches to find more members, E-value
  
• Marginal similarity to domain family possible
  divergent family.

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Prediction of Function Chromatin-Binding Domains

• Protein SPT6 containing CSZ domain, regulates
  transcription through a histone-binding
  capability.
• It also contains two other types of domains,
  which are unlikely to bind histones.
• Therefore it was predicted that CSZ domain has
  that function.

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Research

• Search of C-terminal by PSI-BLAST (E-valuefound UBX containing proteins and metazoan
  homologs of PNGases.
• PNGases proteins involved in UPR.
• UPR unfolded protein response.
• PUG the homologous regions.
• PUG domains found in proteins with
  domains central to ubiquitin- mediated
  proteolysis, (UBA and UBX).

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• Conclusion
• PUG containing proteins might link the UPR to
  ubiquitin mediated protein degradation.

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PUG
UBA
Believed to have a role in the UPR
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ApoptosisUbx domain from human faf1
Dna binding proteinc-terminal uba domain of the
human homologue of rad23a (hhr23a)
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• Orthologs of PNGases in metazoan are present
  singly, (not in multiple paralogs) likely to
  have similar cellular localization.
• The ortholog in Sacharaomyces cervisiae is known
  to be localized mainly in the nucleus.

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• HMM from the PUG marginal similarity to
  IRE1p-like Kinases which are known to initiate
  the UPR as well.
• They suggest the presence of divergent PUG
  domains in the C termini of these Proteins.
• Analysis revealed a conserved region in metazoan
  PNGases. Named it PAW. Put it in SMART.

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• The team found 28 novel nuclear domain families.
• Most of them with representatives in diverse
  molecular context in different species.
• Some specific to single species.
• Others divergent members of previously
  recognized families.

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The End