Bioinformatics Master Course: DNA/Protein Structure-Function Analysis and Prediction

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Bioinformatics Master CourseDNA/Protein
Structure-Function Analysis and Prediction

• Lecture 13 Protein Function

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Sequence-Structure-Function
Ab initio prediction and folding
Sequence Structure Function
impossible but for the smallest structures
Threading
Function prediction from structure
Homology searching (BLAST)
very difficult
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Metabolomics fluxomics
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Systems Biology

• is the study of the interactions between the
  components of a biological system, and how these
  interactions give rise to the function and
  behaviour of that system (for example, the
  enzymes and metabolites in a metabolic pathway).
  The aim is to quantitatively understand the
  system and to be able to predict the systems
  time processes
• the interactions are nonlinear
• the interactions give rise to emergent
  properties, i.e. properties that cannot be
  explained by the components in the system
• Biological processes include many time-scales,
  many compartments and many interconnected network
  levels (e.g. regulation, signalling,
  expression,..)

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Systems Biology

• understanding is often achieved through modeling
  and simulation of the systems components and
  interactions.
• Many times, the four Ms cycle is adopted
• Measuring
• Mining
• Modeling
• Manipulating

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The silicon cell (some people think
silly-con cell)
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(No Transcript)
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A system response
Apoptosis programmed cell death Necrosis
accidental cell death
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Human
Yeast
Comparative metabolomics
We need to be able to do automatic pathway
comparison (pathway alignment)
This pathway diagram shows a comparison of
pathways in (left) Homo sapiens (human) and
(right) Saccharomyces cerevisiae (bakers yeast).
Changes in controlling enzymes (square boxes in
red) and the pathway itself have occurred (yeast
has one altered (overtaking) path in the graph)
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The citric-acid cycle
http//en.wikipedia.org/wiki/Krebs_cycle
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The citric-acid cycle
Fig. 1. (a) A graphical representation of the
reactions of the citric-acid cycle (CAC),
including the connections with pyruvate and
phosphoenolpyruvate, and the glyoxylate shunt.
When there are two enzymes that are not
homologous to each other but that catalyse the
same reaction (non-homologous gene displacement),
one is marked with a solid line and the other
with a dashed line. The oxidative direction is
clockwise. The enzymes with their EC numbers are
as follows 1, citrate synthase (4.1.3.7) 2,
aconitase (4.2.1.3) 3, isocitrate dehydrogenase
(1.1.1.42) 4, 2-ketoglutarate dehydrogenase
(solid line 1.2.4.2 and 2.3.1.61) and
2-ketoglutarate ferredoxin oxidoreductase (dashed
line 1.2.7.3) 5, succinyl- CoA synthetase
(solid line 6.2.1.5) or succinyl-CoAacetoacetate
-CoA transferase (dashed line 2.8.3.5) 6,
succinate dehydrogenase or fumarate reductase
(1.3.99.1) 7, fumarase (4.2.1.2) class I (dashed
line) and class II (solid line) 8,
bacterial-type malate dehydrogenase (solid line)
or archaeal-type malate dehydrogenase (dashed
line) (1.1.1.37) 9, isocitrate lyase (4.1.3.1)
10, malate synthase (4.1.3.2) 11,
phosphoenolpyruvate carboxykinase (4.1.1.49) or
phosphoenolpyruvate carboxylase (4.1.1.32) 12,
malic enzyme (1.1.1.40 or 1.1.1.38) 13, pyruvate
carboxylase or oxaloacetate decarboxylase
(6.4.1.1) 14, pyruvate dehydrogenase (solid
line 1.2.4.1 and 2.3.1.12) and pyruvate
ferredoxin oxidoreductase (dashed line 1.2.7.1).
M. A. Huynen, T. Dandekar and P. Bork Variation
and evolution of the citric acid cycle a genomic
approach'' Trends Microbiol, 7, 281-29 (1999)
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The citric-acid cycle
b) Individual species might not have a complete
CAC. This diagram shows the genes for the CAC for
each unicellular species for which a genome
sequence has been published, together with the
phylogeny of the species. The distance-based
phylogeny was constructed using the fraction of
genes shared between genomes as a similarity
criterion29. The major kingdoms of life are
indicated in red (Archaea), blue (Bacteria) and
yellow (Eukarya). Question marks represent
reactions for which there is biochemical evidence
in the species itself or in a related species but
for which no genes could be found. Genes that lie
in a single operon are shown in the same color.
Genes were assumed to be located in a single
operon when they were transcribed in the same
direction and the stretches of non-coding DNA
separating them were less than 50 nucleotides in
length.
M. A. Huynen, T. Dandekar and P. Bork Variation
and evolution of the citric acid cycle a genomic
approach'' Trends Microbiol, 7, 281-29 (1999)
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Experimental

• Structural genomics
• Functional genomics
• Protein-protein interaction
• Metabolic pathways
• Expression data

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Communicability Functional Genomics

• Interpretation of genome-scale gene expression
  data

External Program
DNA-chip data

• Cluster of coregulated genes
• gene 1
• gene 2
• ...
• gene n

PFMP query

• Pathways affected
• pathway 1
• pathway 2

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Communicability Functional Genomics

• Interpretation of genome-scale gene expression
  data

External Programs
DNA-chip data

• Cluster of coregulated genes
• gene 1
• gene 2
• ...
• gene n

• Pattern discovery
• gene 1
• gene 2
• ...
• (putative regulatory sites)

• Similarities with known regulatory sites
• site 1 Factor 1
• site 2 Factor 2
• ...

PFMP query
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Other Issues

• Partial information (indirect interactions) and
  subsequent filling of the missing steps
• Negative results (elements that have been shown
  not to interact, enzymes missing in an organism)
• Putative interactions resulting from
  computational analyses

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Protein function categories

• Catalysis (enzymes)
• Binding transport (active/passive)
• Protein-DNA/RNA binding (e.g. histones,
  transcription factors)
• Protein-protein interactions (e.g.
  antibody-lysozyme) (experimentally determined by
  yeast two-hybrid (Y2H) or bacterial two-hybrid
  (B2H) screening )
• Protein-fatty acid binding (e.g. apolipoproteins)
• Protein small molecules (drug interaction,
  structure decoding)
• Structural component (e.g. ?-crystallin)
• Regulation
• Signalling
• Transcription regulation
• Immune system
• Motor proteins (actin/myosin)

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Catalytic properties of enzymes
Vmax S V -------------------
Km S
Michaelis-Menten equation
Vmax

• Km kcat
• E S ES E P
• E enzyme
• S substrate
• ES enzyme-substrate complex (transition state)
• P product
• Km Michaelis constant
• Kcat catalytic rate constant (turnover number)
• Kcat/Km specificity constant (useful for
  comparison)

Moles/s
Vmax/2
Km
S
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Protein interaction domains
http//pawsonlab.mshri.on.ca/html/domains.html
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Energy difference upon binding

• Examples of protein interactions (and functional
  importance) include
• Protein protein (pathway analysis)
• Protein small molecules (drug interaction,
  structure decoding)
• Protein peptides, DNA/RNA (function analysis) 
• The change in Gibbs Free Energy of the
  protein-ligand binding interaction can be
  monitored and expressed by the following 
• ?G ? H T ?S       
• (HEnthalpy, SEntropy and TTemperature)

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Protein function

• Many proteins combine functions
• Some immunoglobulin structures are thought to
  have more than 100 different functions (and
  active/binding sites)
• Alternative splicing can generate (partially)
  alternative structures

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Protein function Interaction
Active site / binding cleft
Shape complementarity
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Protein function evolution
Chymotrypsin
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How to infer function

• Experiment
• Deduction from sequence
• Multiple sequence alignment conservation
  patterns
• Homology searching
• Deduction from structure
• Threading
• Structure-structure comparison
• Homology modelling

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Cholesterol Biosynthesis

• Cholesterol biosynthesis primarily occurs in
  eukaryotic cells. It is necessary for membrane
  synthesis, and is a precursor for steroid hormone
  production as well as for vitamin D. While the
  pathway had previously been assumed to be
  localized in the cytosol and ER, more recent
  evidence suggests that a good deal of the enzymes
  in the pathway exist largely, if not exclusively,
  in the peroxisome (the enzymes listed in blue in
  the pathway to the left are thought to be at
  least partly peroxisomal). Patients with
  peroxisome biogenesis disorders (PBDs) have a
  variable deficiency in cholesterol biosynthesis

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Cholesterol Biosynthesis from acetyl-Coa to
mevalonate
Mevalonate plays a role in epithelial cancers
it can inhibit EGFR
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Epidermal Growth Factor as a Clinical Target in
Cancer

• A malignant tumour is the product of uncontrolled
  cell proliferation. Cell growth is controlled by
  a delicate balance between growth-promoting and
  growth-inhibiting factors. In normal tissue the
  production and activity of these factors results
  in differentiated cells growing in a controlled
  and regulated manner that maintains the normal
  integrity and functioning of the organ. The
  malignant cell has evaded this control the
  natural balance is disturbed (via a variety of
  mechanisms) and unregulated, aberrant cell growth
  occurs. A key driver for growth is the epidermal
  growth factor (EGF) and the receptor for EGF (the
  EGFR) has been implicated in the development and
  progression of a number of human solid tumours
  including those of the lung, breast, prostate,
  colon, ovary, head and neck.

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Energy housekeeping

• Adenosine diphosphate (ADP) Adenosine
  triphosphate (ATP)

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Chemical Reaction
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Enzymatic Catalysis
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Gene Expression
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Inhibition
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Metabolic Pathway Proline Biosynthesis
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Transcriptional Regulation
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Methionine Biosynthesis in E. coli
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Shortcut Representation
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High-level Interaction
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Levels of Resolution
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Cholesterol Biosynthesis
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SREBP Pathway
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Signal Transduction
Important signalling pathways Map-kinase (MapK)
signalling pathway, or TGF-? pathway
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Transport
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Phosphate Utilization in Yeast
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Multiple Levels of Regulation

• Gene expression
• Protein activity
• Protein intracellular location
• Protein degradation
• Substrate transport

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Graphical Representation Gene Expression
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Experimental Data Gene Expression
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Experimental Data Transcriptional Regulation
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Experimental Data Transcriptional Regulation
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Transcriptional RegulationIntegrated View
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Pathways and Pathway Diagrams

• Pathways
• Set of nodes (entities) and edges (associations)
• Pathway Diagrams
• XY coordinates
• Node splitting allowed
• Multiple views of the same pathway
• Different abstraction levels

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Metabolic networksGlycolysis and
Gluconeogenesis
Kegg database (Japan)
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Gene Ontology (GO)

• Not a genome sequence database
• Developing three structured, controlled
  vocabularies (ontologies) to describe gene
  products in terms of
• biological process
• cellular component
• molecular function
• in a species-independent manner

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The GO ontology
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Gene Ontology Members

• FlyBase - database for the fruitfly Drosophila
  melanogaster
• Berkeley Drosophila Genome Project (BDGP) -
  Drosophila informatics GO database software,
  Sequence Ontology development
• Saccharomyces Genome Database (SGD) - database
  for the budding yeast Saccharomyces cerevisiae
• Mouse Genome Database (MGD) Gene Expression
  Database (GXD) - databases for the mouse Mus
  musculus
• The Arabidopsis Information Resource (TAIR) -
  database for the brassica family plant
  Arabidopsis thaliana
• WormBase - database for the nematode
  Caenorhabditis elegans
• EBI GOA project annotation of UniProt
  (Swiss-Prot/TrEMBL/PIR) and InterPro databases
• Rat Genome Database (RGD)  - database for the rat
  Rattus norvegicus
• DictyBase  - informatics resource for the slime
  mold Dictyostelium discoideum
• GeneDB S. pombe - database for the fission yeast
  Schizosaccharomyces pombe (part of the Pathogen
  Sequencing Unit at the Wellcome Trust Sanger
  Institute)
• GeneDB for protozoa - databases for Plasmodium
  falciparum, Leishmania major, Trypanosoma brucei,
  and several other protozoan parasites (part of
  the Pathogen Sequencing Unit at the Wellcome
  Trust Sanger Institute)
• Genome Knowledge Base (GK) - a collaboration
  between Cold Spring Harbor Laboratory and EBI)
• TIGR - The Institute for Genomic Research
• Gramene - A Comparative Mapping Resource for
  Monocots
• Compugen (with its Internet Research Engine)
• The Zebrafish Information Network (ZFIN) -
  reference datasets and information on Danio rerio