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y-sa/2.0/. Integrating the Data Prof:Rui Alves 973702406 Dept Ciencies Mediques Basiques, 1st.

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Presentation on theme: "y-sa/2.0/. Integrating the Data Prof:Rui Alves 973702406 Dept Ciencies Mediques Basiques, 1st."— Presentation transcript:

1 http://creativecommons.org/licenses/b y-sa/2.0/

2 Integrating the Data Prof:Rui Alves ralves@cmb.udl.es 973702406 Dept Ciencies Mediques Basiques, 1st Floor, Room 1.08 Website of the Course:http://web.udl.es/usuaris/pg193845/Courses/Bioinformatics_2007/ Course: http://10.100.14.36/Student_Server/

3 Outline Methods for reconstruction of functional protein networks –Why is it important? Methods for reconstruction of physical protein interactions

4 Proteins do not work alone!

5 Methods for network reconstruction Using text analysis

6 Publication databases are source of information

7 Meta text databases create network models from publication analysis

8 iHOP is a sofisticated context analysis motor

9 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 Ste20 e.g activate, inhibit rescue

10 Methods for network reconstruction Meta text analysis Evolutionary based protein interaction prediction

11 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…

12 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? … ABC…ABC… YNY…YNY… NYN…NYN… …………………… AB 00 i/number of genomes<1 C 1 j/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

13 Syntheny/Conservation of gene neighborhoods Genome 1 Genome 2 Genome 3 Genome … Protein AProtein BProtein CProtein D Protein AProtein BProtein C Protein D Protein A Protein BProtein C Protein D … Protein AProtein BProtein CProtein 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

14 Gene fusion events Genome 1 Genome 2 Genome 3 Genome … Protein AProtein DProtein C Protein B Protein AProtein BProtein CProtein D Protein A Protein BProtein C Protein D … Protein AProtein BProtein CProtein 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

15 Building phylogenetic trees of proteins Genome 1 Genome 2 Genome 3 Genome … Protein AProtein BProtein CProtein D Protein AProtein BProtein C Protein D Protein A Protein BProtein C Protein 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

16 Similarity of phylogenetic trees indicates interaction between proteins A1 B2 C1 D1 A2 A3 …… … B1 B3 C2 C3 … D3 D2 Proteins A and B have similar evolutionary trees and thus are likely to interact

17 Methods for network reconstruction Using meta text analysis Using phylogenetic profiling Using omics data

18 Predicting gene functional interactions using micro array data cells Stimulum 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

19 Group of proteins involved in response to the stimulus Predicting protein functional interactions using mass spec data cells Stimulum 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

20 Predicting regulatory modules with CHIP-ChIp experiments cells Crosslink Protein/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 Microarray

21 Predicting protein activity modulation with NMR/IR/MS Metabolomics cells Stimulus Measuring Metabolites cells Measuring Metabolites Compare changes in metabolic levels to infer changes in protein activity

22 Methods for network reconstruction Using meta text analysis Using phylogenetic profiling Using protein docking Using omics data Using protein interaction data

23 Predicting protein networks using protein interaction data Database of protein interactions Server/ Program Your Sequence (A) A BC D E F Continue until you are satisfied or completed the network

24 Outline Methods for reconstruction of functional protein networks Methods for reconstruction of protein interactions

25 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?

26 Proteins work by binding Effect DNA Proteins work by binding!

27 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

28 What is in silico protein docking? Given two molecules find their correct association using a computer: + = Receptor Ligand T Complex

29 What types of in silico docking exist? Sequence Based Docking:

30 In silico two hybrid docking E. coli S. typhi … Y. pestis AGGMEYW…. AA – CDWY… … AGG –DYW Protein A E. coli S. typhi … Y. pestis VCHPRIIE…. VCH -KIIE… … VCH –KIIE… Protein B V C H P K I I E… AGG…D…AGG…D… D/K or E/R may be involved in a salt bridge Pearson Correlation

31 What types of in silico docking exist? Sequence Based Docking In silico structural protein docking

32 Structure based docking Protein-Protein docking –Rigid (usually) Protein-Ligand docking –Rigid protein, flexible ligand Very demanding on computational resources

33 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)

34 Atom based docking First, a surface representation is needed Van der Waals Surface Accessible (Connolly) Surface Solvent accessible Surface

35 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

36 Grid-based techniques Grid-based Techniques –Alternative to calculating protein atom / ligand atom interactions. more efficient (number of grid points < number of atoms)

37 Grid based docking Score 1 Score 2 Score 3 Score 4 Place grid over protein Calculate inter- molecular forces for each grid point

38 The docking function There are many and none is the best for all cases Scores will depend on the exact docking function you use

39 A docking function for surface matching Molecules a, b placed on l × m × n grid Match surfaces Fourier transform makes calculation faster Tabulate and rank all possible conformations

40 A docking function for electrostatics There are many they use different force field approximations to calculate energy of electrostatic interactions. The basics: Charge distributions for proteins Potential for proteins

41 The full docking function Calculates a relative binding energy that integrates electrostatic and shape matching factors. For example:

42 Overall process of docking

43 Mol 1Mol 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

44 Summary Methods for reconstruction of functional protein networks –Bibliomics –Genomics –Phenomics, etc Methods for reconstruction of protein interactions –Sequence based –Structure based

45 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

46 Problem Importance Computer aided drug design – a new drug should fit the active site of a specific receptor. Many reactions in the cell occur through interactions between the molecules. No efficient techniques for crystallizing large complexes and finding their structure.


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