Structure Databases

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Structure Databases

• DNA/Protein structure-function analysis and
  prediction
• Lecture 6
• Bioinformatics Section, Vrije Universiteit,
  Amsterdam

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The dictionary definition

• Main Entry database Pronunciation
  'dA-t-"bAs, 'da- also 'dä-Function nounDate
  circa 1962
• a usually large collection of data organized
  especially for rapid search and retrieval (as by
  a computer)
• - Webster dictionary

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WHAT is a database?

• A collection of data that needs to be
• Structured
• Searchable
• Updated (periodically)
• Cross referenced
• Challenge
• To change meaningless data into useful
  information that can be accessed and analysed the
  best way possible.
• For example
• HOW would YOU organise all biological sequences
  so that the biological information is optimally
  accessible?
• You need an appropriate database management
  system (DBMS)

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DBMS
Database

• Internal organization
• Controls speed and flexibility
• A unity of programs that
• Store
• Extract
• Modify

Store
Extract
Modify
USER(S)
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DBMS organisation types

• Flat file databases (flat DBMS)
• Simple, restrictive, table
• Hierarchical databases (hierarchical DBMS)
• Simple, restrictive, tables
• Relational databases (RDBMS)
• Complex,versatile, tables
• Object-oriented databases (ODBMS)
• Complex, versatile, objects

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Relational databases

• Data is stored in multiple related tables
• Data relationships across tables can be either
  many-to-one or many-to-many
• A few rules allow the database to be viewed in
  many ways
• Lets convert the course details to a relational
  database

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Our flat file database
FLAT DATABASE 2
Course details
Name Depart. Course E1 E2
E3 P1 P2
Student 1 Chemistry Biology A B B
A C ..
Student 1 Chemistry Maths C C B
A A ..
Student 1 Chemistry English A A A
A A ..
. . . .
Student 2 Ecology Biology A B A
A A ..
Student 2 Ecology Maths A D A
A A ..
. . . .
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Normalize (1NF)

• We remove repeating records (rows)

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Normalize (2NF)

• We remove redundant fields (columns)

wID Project
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Relational Databases

• What have we achieved?
• No repeating information
• Less storage space
• Better reality representation
• Easy modification/management
• Easy usage of any combination of records
• Remember
• the DBMS has programs to access and edit this
  information so ignore the human reading
  limitation of the primary keys

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Accessing database information

• A request for data from a database is called a
  query
• Queries can be of three forms
• Choose from a list of parameters
• Query by example (QBE)
• Query language

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Query Languages

• The standard
• SQL (Structured Query Language) originally
  called SEQUEL (Structured English QUEry Language)
• Developed by IBM in 1974 introduced commercially
  in 1979 by Oracle Corp.
• Standard interactive and programming language for
  getting information from and updating a database.
• RDMS (SQL), ODBMS (Java, C, OQL etc)

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Distributed databases

• From local to global attitude
• Data appears to be in one location but is most
  definitely not
• A definition Two or more data files in different
  locations, periodically synchronized by the DBMS
  to keep data in all locations consistent (A,B,C)
• An intricate network for combining and sharing
  information
• Administrators praise fast network
  technologies!!!
• Users praise the internet!!!

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Data warehouse

• Periodically, one imports data from databases and
  store it (locally) in the data warehouse.
• Now a local database can be created, containing
  for instance protein family data (sequence,
  structure, function and pathway/process data
  integrated with the gene expression and other
  experimental data).
• Disadvantage expensive, intensive, needs to be
  updated.
• Advantage easy control of integrated data-mining
  pipeline.

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So why do biologists care?
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Three main reasons

• Database proliferation
• Dozens to hundreds at the moment
• More and more scientific discoveries result from
  inter-database analysis and mining
• Rising complexity of required data-combinations
• E.g. translational medicine from bench to
  bedside (genomic data vs. clinical data)

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Biological databases

• Like any other database
• Data organization for optimal analysis
• Data is of different types
• Raw data (DNA, RNA, protein sequences)
• Curated data (DNA, RNA and protein annotated
  sequences and structures, expression data)

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Raw Biological dataNucleic Acids (DNA)
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Raw Biological dataAmino acid residues (proteins)
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Curated Biological Data
DNA, nucleotide sequences
Gene boundaries, topology
Gene structure
Introns, exons, ORFs, splicing
Mass spectometry
Expression data
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Curated Biological Data
Proteins, residue sequences
Mass spectometry (metabolomics, proteomics)
Extended sequence information
MCTUYTCUYFSTYRCCTYFSCD
Secondary structure
Post-Translational protein Modification (PTM)
Hydrophobicity, motif data
Protein-protein interaction
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Curated Biological data3D Structures, folds
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Biological Databases
The 2003 NAR Database Issue http//nar.oupjournal
s.org/content/vol31/issue1/
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Distributed information

• Pearsons Law The usefulness of a column of data
  varies as the square of the number of columns it
  is compared to.

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A few biological databases

• Nucleotide DatabasesAlternative Splicing,
  EMBL-Bank, Ensembl, Genomes Server, Genome, MOT,
  EMBL-Align, Simple Queries, dbSTS Queries,
  Parasites, Mutations, IMGT
• Genome Databases
• Human, Mouse, Yeast, C.elegans, FLYBASE,
  Parasites
• Protein Databases Swiss-Prot, TrEMBL,
  InterPro, CluSTr, IPI, GOA, GO, Proteome
  Analysis, HPI, IntEnz, TrEMBLnew, SP_ML, NEWT,
  PANDIT
• Structure Databases PDB, MSD, FSSP, DALI
• Microarray Database ArrayExpress
• Literature Databases MEDLINE, Software
  Biocatalog, Flybase Archives
• Alignment Databases
• BAliBASE, Homstrad, FSSP

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Structural Databases

• Protein Data Bank (PDB) http//www.rcsb.org/pdb/
• Structural Classification of Proteins (SCOP)
• http//scop.berkeley.edu
• http//scop.mrc-lmb.cam.ac.uk/scop/

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PDB

• 3D Macromolecular structural data
• Data originates from NMR or X-ray crystallography
  techniques
• Total no of structures 34.626 (17/01/2006)
• If the 3D structure of a protein is solved ...
  they have it

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PDB content
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PDB information

• The PDB files have a standard format
• Key features
• Informative descriptors

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PDB-mirror on the WWW
e.g.1AE5
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Example output 1AE5
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SCOP

• Structural Classification Of Proteins
• 3D Macromolecular structural data grouped based
  on structural classification
• Data originates from the PDB
• Current version (v1.69)
• 25973 PDB Entries (July 2005).
• 70859 Domains

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SCOP levels bottom-up

• Family Clear evolutionarily relationshipProteins
  clustered together into families are clearly
  evolutionarily related. Generally, this means
  that pairwise residue identities between the
  proteins are 30 and greater. However, in some
  cases similar functions and structures provide
  definitive evidence of common descent in the
  absence of high sequence identity for example,
  many globins form a family though some members
  have sequence identities of only 15.
• Superfamily Probable common evolutionary
  originProteins that have low sequence
  identities, but whose structural and functional
  features suggest that a common evolutionary
  origin is probable are placed together in
  superfamilies. For example, actin, the ATPase
  domain of the heat shock protein, and hexakinase
  together form a superfamily.
• Fold Major structural similarityProteins are
  defined as having a common fold if they have the
  same major secondary structures in the same
  arrangement and with the same topological
  connections. Different proteins with the same
  fold often have peripheral elements of secondary
  structure and turn regions that differ in size
  and conformation. In some cases, these differing
  peripheral regions may comprise half the
  structure. Proteins placed together in the same
  fold category may not have a common evolutionary
  origin the structural similarities could arise
  just from the physics and chemistry of proteins
  favouring certain packing arrangements and chain
  topologies.

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SCOP-mirror on the WWW
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Enter SCOP at the top of the hierarchy
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Keyword search of SCOP entries
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CATH

• Class, derived from secondary structure content,
  is assigned for more than 90 of protein
  structures automatically.
• Architecture, which describes the gross
  orientation of secondary structures, independent
  of connectivities, is currently assigned
  manually.
• Topology level clusters structures according to
  their toplogical connections and numbers of
  secondary structures.
• The Homologous superfamilies cluster proteins
  with highly similar structures and functions. The
  assignments of structures to topology families
  and homologous superfamilies are made by sequence
  and structure comparisons.

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CATH-mirror on the WWW
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DSSP

• Dictionary of secondary structure of proteins
• The DSSP database comprises the secondary
  structures of all PDB entries
• DSSP is actually software that translates the PDB
  structural co-ordinates into secondary
  (standardized) structure elements
• A similar example is STRIDE

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WHY bother???

• Researchers create and use the data
• Use of known information for analyzing new data
• New data needs to be screened
• Structural/Functional information
• Extends the knowledge and information on a higher
  level than DNA or protein sequences

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In the end .
Computers can figure out all kinds of problems,
except the things in the world that just don't
add up. James Magary We should add For that we
employ the human brain, experts and experience.
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Bio-databases A short word on problems

• Even today we face some key limitations
• There is no standard format
• Every database or program has its own format
• There is no standard nomenclature
• Every database has its own names
• Data is not fully optimized
• Some datasets have missing information without
  indications of it
• Data errors
• Data is sometimes of poor quality, erroneous,
  misspelled
• Error propagation resulting from computer
  annotation

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What to take home

• Databases are a collection of data
• Need to access and maintain easily and flexibly
• Biological information is vast and sometimes very
  redundant
• Distributed databases bring it all together with
  quality controls, cross-referencing and
  standardization
• Computers can only create data, they do not give
  answers
• Review-suggestion Integrating biological
  databases, Stein, Nature 2003