http://creativecommons.org/licenses/b y-sa/2.0/. integrating the data prof:rui alves...
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Integrating the Data
Prof:Rui [email protected]
973702406Dept Ciencies Mediques Basiques,
1st Floor, Room 1.08Website of the Course:http://web.udl.es/usuaris/pg193845/Courses/Bioinformatics_2007/
Course: http://10.100.14.36/Student_Server/
Outline
• Methods for reconstruction of functional protein networks– Why is it important?
• Methods for reconstruction of physical protein interactions
Finding the social environment of a protein
• Finding out what a protein does is not enough – Reductase, ok, but of what? (super-mouse)
• There is an incredible ammount of information available regarding the biology of many organisms– Sequences, omics, pathways, etc…
Integrating the information is important for network recontruction
• If we can integrate all the information available for a given protein/gene, then we are likely to be able to predict its social network
• From here to reconstructing the causal set of interactions in the network, there is only a step– Who does what to whom
Methods for network reconstruction
• Mapping Gene onto known pathways– If a gene is orthologous to genes in other
organisms for which we known the pathways and circuits, then we can assume that they work in that circuit in the new organism
Methods for network reconstruction
• Mapping Gene onto known pathways • Using text analysis
– Scientific literature as accumulated over centuries now.
– No one can know everything and read everything.
– However, information is buried in there
– Mining that information can assist in network reconstruction
How does meta-text analysis create networks?
Literature database
Gene names
database
Language rules
database
scripts
Entry
Gene list Rule list
Server/
Program
Your genes
List of entries mentioning your gene
e.g Ste20e.g activate,
inhibit rescue
Problems with this set up
• Delay with respect to available information
• Disregards a lot of information available over the web
Things to do• Statistical Significance
– Internal controls– Overall controls
• Sentence Mining– Definition of action words ontology to help
automated function mining
• Graphical Drawing– Allowing for mouse drag and droping
• Selector for interaction that are to be trusted and included in the model
Problems with this set up
• Slow, analysis and document retrieval is done live– In the future there will be an option so that if a
search has been done by someone before the user will be able to use that, instead of doing a live search
• There is more “junk info”– However you can control that by selecting the
sources of information you want to use
Methods for network reconstruction
• Mapping Gene onto known pathways • Meta text analysis• Evolutionary based protein interaction
prediction– Proteins that work together (i.e. belong to the
smae close social network) evolve together– Ergo, proteins that show co-evolution are to
likely to work together
Proteins that have coevolved share a function
• If protein A has co-evolved with protein B, they are likely to be involved in the same process
• Looking for proteins that coevolved will help prediction social networks of proteins
• There are many methods to look for co-evolution of proteins– Phylogenetic profiling, gene neighbourhoods,
gene fusion events, phylogenetic trees…
Using phylogenetic profiles to predict protein interactions
Your Sequence (A) Server/
Program
Database of profiles for each protein in each organism
Database of proteins in fully sequenced genomes
Protein id A
Target Genome
Homologue in Genome 1?
Homologue in Genome 2?
…
A
B
C
…
Y
N
Y
…
N
Y
N
…
…
…
…
…
A B
00i/number of genomes<1C
1j/number of genomes
A 1
C 0.9
… …
B 0.11
… …
Proteins (A and C) that are present and absent in the same set of genomes are likely to be involved in the same process and therefore interact
Similarly, if protein A is absent in all genomes in which protein B is present there is a likelihood that they perform the same function! 2
Calculate coincidence index
Phylogenetic coincidence server
• We have one that will be up in a few months for yeast, coli, man, chimp, candida and xanthus.
Syntheny/Conservation of gene neighborhoods
Genome 1
Genome 2
Genome 3
Genome …
Protein A Protein B Protein C Protein D
Protein A Protein BProtein C Protein D
Protein AProtein B Protein CProtein D
…
Protein A Protein B Protein C Protein D
Which of these proteins interact?
Proteins A and B are in a conserved relative position in most genomes which is an
indication that they are likely to interact
Gene fusion events
Genome 1
Genome 2
Genome 3
Genome …
Protein A Protein DProtein C Protein B
Protein A Protein B Protein C Protein D
Protein AProtein B Protein CProtein D
…
Protein A Protein B Protein C Protein D
Which of these proteins interact?Proteins A and B have suffered gene fusion
events in at least some genomes, which is an indication that they are likely to interact
Building phylogenetic trees of proteins
Genome 1
Genome 2
Genome 3
Genome …
Protein A Protein B Protein C Protein D
Protein A Protein BProtein C Protein D
Protein AProtein B Protein CProtein D
…Get sequence of all homogues, align and
build a phylogenetic tree
Phylogenetic trees represent the evolutionary history of homologue
genes/proteins based on their sequence
Similarity of phylogenetic trees indicates interaction between proteins
A1
B2
C1 D1
A2
A3
… …
…
B1
B3
C2
C3
…
D3
D2Proteins A and B have similar evolutionary trees and thus are likely to interact
Protein/Gene interactions
• Often, people use these methods to say that genes of proteins interact.
• The methods previously describe can not be used accurately to describe PHYSICAL interaction
• When people say interact in this context one is forced to assume FUNCTIONAL (not necessarily physical) interaction, unless more info is available
Methods for network reconstruction
• Mapping Gene onto known pathways • Using meta text analysis• Using phylogenetic profiling• Using omics data
– If two proteins/genes have evolve to perform a function in the same process, it is likely that their activity and gene expression is co-regulated
– Conversely, if proteins/genes are co-regulated, then they are likely to participate in the same process
Predicting gene functional interactions using micro array
datacells
cells
Stimulum
Purify cDNA
Purify cDNA Compare cDNA levels of
corresponding genes in the different
populations
Genes overexpressed
as a result of stimulus
Genes underexpressed
as a result of stimulus
Genes with expression
independent of stimulus
Group of genes/proteins
involved in response to the stimulus
Gene network reconstruction
• Reconstruction of gene networks based on micro-array data is a very difficult endeavor
• It is an inverse problem, meaning that there is usually more than one solution that fits the data
• Pioner groups used either petri nets (e.g. Somogyi, Finland) or mathematical model (Okamoto, Japan)
Group of proteins involved in response
to the stimulus
Predicting protein functional interactions using mass spec data
cells
cells
Stimulum
Purify proteins
Purify proteins Identify Proteins and compare Protein
profiles/levels in the different populations
Proteins present
as a result of stimulus
Proteins absent
as a result of stimulus
Proteins Present
in both conditions
Protein network reconstruction
• Reconstruction of protein networks based on mass spec proteomics data is still very immature.
• To my knowledge no paradigmatic, large scale example of it has yet been done
Regulation of gene expression
• Predicting which TF regulate gene expression is an important part of reconstructing biological circuits of interest
• Omics data and bioinformatics can also be used to do this
Predicting regulatory modules with CHIP-ChIp experiments
cells
Crosslink
Protein/DNA Break DNA
Break DNA
Reverse cross link & Purify DNA Pieces
Afinity Purification of Transcription factor
Reverse cross link & Purify DNA Pieces bound to TF
Compare in MicroarrayDerive consensus sequences for TF binding sites
Scan new genomes for TF regulatory modules
Predicting protein activity modulation with NMR/IR/MS
Metabolomics
cells
Stimulus
Measuring Metabolitescells
Measuring Metabolites
Compare changes in metabolic levels to infer changes in protein activity
Incorporating metabolomics information
• These changes can be incorporated into mathematical models and these models can then be used predictively
Methods for network reconstruction
• Mapping Gene onto known pathways • Using meta text analysis• Using phylogenetic profiling• Using omics data• Using protein interaction data
– Large scale protein interaction data sets are available
– If proteins physically interact, it is likely that they work together in the same network
Predicting protein networks using protein interaction data
Database of protein
interactions
Server/
Program
Your Sequence (A)
A
BC
D E
FContinue until you are satisfied
or completed the network
Outline
• Methods for reconstruction of functional protein networks
• Methods for reconstruction of physical protein interactions
How do proteins work within the network?
• Assume we now have the network our protein is involved in.
• How do we further analyze the role of the protein?
So what?
So, if we can predict how proteins DOCK to their ligands, then we will be able to understand how the binding allows them to work systemically
Design drugs to overcome mutations in binding sites
Design proteins to prevent/enhance other interactions
What is in silico protein docking?
• Given two molecules find their correct association using a computer:
+
=
Recep
tor Ligand
T
Complex
In silico two hybrid docking
E. coli
S. typhi
…
Y. pestis
AGGMEYW….
AA – CDWY…
…
AGG –DYW
Protein AE. coli
S. typhi
…
Y. pestis
VCHPRIIE….
VCH -KIIE…
…
VCH –KIIE…
Protein B
V C H P K I I E…
A
G
G
…
D
…
D/K or E/R may be involved in a salt bridge
Pearson Correlation
What types of in silico docking exist?
• Sequence Based Docking
• In silico structural protein docking
Structure based docking
• Protein-Protein docking
– Rigid (usually)
• Protein-Ligand docking
– Rigid protein, flexible ligand
Very demanding on computational resources
Structural docking in a nutshell
• Scan molecular surfaces of protein for best surface fit– First steric, then energetics – Can (and should) include biologically relevant
information (e.g. residue X is known from mutation experiments to be involved in the docking → discard any docking not involving this residue)
Atom based docking
• First, a surface representation is needed
Van der Waals Surface
Accessible (Connolly)Surface
Solvent accessibleSurface
Calculating the best docking
• Scan molecular surfaces of protein for best surface fit– Calculate the position where a largest number of
atoms fits together, factor in energy + biology and rank solutions according to that
Grid-based techniques
•Grid-based Techniques
–Alternative to calculating protein atom / ligand atom interactions. more efficient (number of grid points < number of atoms)
Grid based docking
Score 1
Score 2Score 3
Score 4
Place grid over protein
Calculate inter-molecular forces for each grid point
The docking function
• There are many and none is the best for all cases
•Scores will depend on the exact docking function you use
A docking function for surface matching
•Molecules a, b placed on l × m × n grid
•Match surfaces
•Fourier transform makes calculation faster
moleculetheofsurfacetheon
moleculetheinside
moleculetheoutside
ba nml
1
0
, ,,
', ', ' 1, 2, 3 ', ', ' 1, 2, 3' 1 ' 1 ' 1
,N N N
l m n l step m step n step l m n l step m step n stepl m n
Ca b a b
•Tabulate and rank all possible conformations
A docking function for electrostatics
• There are many
•they use different force field approximations to calculate energy of electrostatic interactions.
•The basics:
dVrrrrE bbaabbaaticelectrosta
Charge distributions for proteins
Potential for proteins
The full docking function
• Calculates a relative binding energy that integrates electrostatic and shape matching factors. For example:
tot Electrostatic Electrostatic shape matching shapematchingE c E c E
Overall process of docking
1, 2,,,
( , )i jp p
i j
Energy Form Matching Electrostatics
Mol 1 Mol 2
Rigid Body energy calculation
List of Complexes
Re-rank using statistics of residue contact, H/bond, biological information, etc
Re-rank using rotamers, flexibility in protein backbone angles, Molecular dynamics, etc.
Final list of solutions
Summary
• Methods for reconstruction of functional protein networks– Bibliomics
– Genomics
– Phenomics, etc
• Methods for reconstruction of protein interactions– Sequence based
– Structure based
Grid-based techniques
• Grid-based Techniques
– Notes:
• Grids spaced <1 Å
– Results show very little change in error for grids spacing between .25 and 1 Å