1 / 46

creativecommons/licenses/by-sa/2.0/

http://creativecommons.org/licenses/by-sa/2.0/. 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/

knox
Télécharger la présentation

creativecommons/licenses/by-sa/2.0/

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. http://creativecommons.org/licenses/by-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. Server/ Program Literature database Gene names database Language rules database Gene list Rule list How does meta-text analysis create networks? Your genes scripts Entry List of entries mentioning your gene e.g activate, inhibit rescue e.g Ste20

  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. Database of profiles for each protein in each organism Database of proteins in fully sequenced genomes Server/ Program Using phylogenetic profiles to predict protein interactions A 1 C 0.9 … … B 0.11 … … Your Sequence (A) 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 Calculate coincidence index Protein id A A B C 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! i/number of genomes<1 j/number of genomes 0 0 2 1

  13. Protein A Protein B Protein C Protein D Protein D Protein C Protein A Protein B Protein B Protein C Protein D Protein A Syntheny/Conservation of gene neighborhoods Genome 1 Genome 2 Protein A Protein B Protein C Protein D Proteins A and B are in a conserved relative position in most genomes which is an indication that they are likely to interact Genome 3 Which of these proteins interact? … Genome …

  14. Protein A Protein B Protein C Protein D Protein B Protein C Protein A Protein D Protein B Protein C Protein D Protein A Gene fusion events Genome 1 Protein A Protein B Protein C Protein D Genome 2 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 Genome 3 … Genome …

  15. Protein A Protein B Protein C Protein D Protein D Protein C Protein A Protein B Protein B Protein C Protein D Protein A Building phylogenetic trees of proteins Genome 1 Phylogenetic trees represent the evolutionary history of homologue genes/proteins based on their sequence Genome 2 Genome 3 … Genome … Get sequence of all homogues, align and build a phylogenetic tree

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

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

  18. Predicting gene functional interactions using micro array data Genes overexpressed as a result of stimulus Group of genes/proteins involved in response to the stimulus cells Purify cDNA Compare cDNA levels of corresponding genes in the different populations Genes underexpressed as a result of stimulus Stimulum Purify cDNA cells Genes with expression independent of stimulus

  19. Predicting protein functional interactions using mass spec data Proteins present as a result of stimulus Group of proteins involved in response to the stimulus cells Purify proteins Identify Proteins and compare Protein profiles/levels in the different populations Proteins absent as a result of stimulus Stimulum Purify proteins cells Proteins Present in both conditions

  20. Predicting regulatory modules with CHIP-ChIp experiments Compare in Microarray Crosslink Protein/DNA Reverse cross link & Purify DNA Pieces Break DNA cells Afinity Purification of Transcription factor Reverse cross link & Purify DNA Pieces bound to TF Break DNA

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

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

  23. E D A C B F Predicting protein networks using protein interaction data Database of protein interactions Your Sequence (A) Server/ Program 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 DNA Effect 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. T Complex Receptor Ligand What is in silico protein docking? • Given two molecules find their correct association using a computer: = +

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

  30. A G G … D … V C H P K I I E… In silico two hybrid docking Protein A Protein B AGGMEYW…. AA – CDWY… … AGG –DYW VCHPRIIE…. VCH -KIIE… … VCH –KIIE… E. coli S. typhi … Y. pestis E. coli S. typhi … Y. pestis 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 Accessible (Connolly) Surface • First, a surface representation is needed Van der Waals 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 2 Score 3 Score 4 Score 1 • Calculate inter-molecular forces for each grid point • Place grid over protein

  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. Overall process of docking Mol 1 Mol 2 Final list of solutions Rigid Body energy calculation Re-rank using statistics of residue contact, H/bond, biological information, etc Re-rank using rotamers, flexibility in protein backbone angles, Molecular dynamics, etc. List of Complexes

  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.

More Related