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MSD pisa a web service for studying P rotein I nterfaces, S urfaces and A ssemblies

MSD pisa a web service for studying P rotein I nterfaces, S urfaces and A ssemblies Eugene Krissinel. http://www.ebi.ac.uk/msd-srv/prot_int/pistart.html. What PISA is about. Crystal = translated Unit Cell.

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MSD pisa a web service for studying P rotein I nterfaces, S urfaces and A ssemblies

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  1. MSDpisa a web service for studying Protein Interfaces, Surfaces and Assemblies Eugene Krissinel http://www.ebi.ac.uk/msd-srv/prot_int/pistart.html

  2. What PISA is about Crystal = translated Unit Cell More than 80% of protein structures are solved by means of X-ray diffraction on crystals. An X-ray diffraction experiment produces atomic coordinates of the crystal’s Asymmetric Unit (ASU). In general, neither ASU nor Unit Cell has any relation to Biological Units, or stable protein complexes which act as units in physiological processes. PISA attempts to recover Biological Units from the protein crystallography data. Unit Cell = all space symmetry group mates of ASU PDB file

  3. Crystal interfaces Stability of protein complexes depends on properties of protein-protein interfaces, such as • free energy of formation DGint • solvation energy gain DGS • interface area • hydrogen bonds and salt bridges across the interface • hydrophobic specificity PISA calculates crystal contacts and their physical-chemical properties

  4. Interface assessment A crystal may be viewed as a packing of assemblies with biologically insignificant contacts between them. Protein assembly is a packing of monomeric units with biologically relevant interfaces between them. PISA is a tool to assess crystal interfaces for biological significance.

  5. Dissociation into stable subunits with minimum Properties of assemblies Protein assemblies may exist in certain conditions and dissociate in other. Sometimes aggregation properties are the key to biological function. PISA calculates properties of protein assemblies, such as free energy of dissociation DGdiss, and predicts a probable dissociation pattern.

  6. PISA workflow summary 1. Calculate properties of all structures 2. Calculate all crystal contacts and their properties 3. Find all assemblies which are possible in given crystal 4. Evaluate all assemblies for chemical stability and leave only potentially stable ones 5. Range assemblies by chances to be a biological unit

  7. Assembly set Assembly set Engaged interface types Engaged interface types 6 8 5 1 7 2 3 4 111 110 000 001 101 010 011 100 - dimer N2 - all crystal - dimer N1 - only monomers - dimer N3 Enumerating assemblies in crystal • crystal is represented as a periodic graph with monomeric chains as vertices and interfaces as edges • each set of assemblies is identified by engaged interface types • all assemblies may be enumerated by a backtracking scheme engaging all possible combinations of different interface types Example: crystal with 3 interface types

  8. Chemical stability of protein complexes • It is not properties of individual interfaces but rather chemical stability of protein complex in general that really matters • Protein chains will most likely associate into largest complexes that are still stable • A protein complex is stable if its free energy of dissociation is positive:

  9. Solvation energies of dissociated subunits Free energy of H-bond formation Free energy of salt bridge formation Solvation energy of protein complex Number of H-bonds between dissociated subunits Number of salt bridges between dissociated subunits Choice of dissociation subunits: Dissociation into stable subunits with minimum Protein affinity

  10. Entropy of dissociation Murray C.W. and Verdonik M.L. (2002) J. Comput.-Aided Mol. Design 16, 741-753. Mass of i-th subunit k-th principal moment of inertia of i-th subunit Fitted parameter Fitted parameter

  11. 198+20 <=> 198 homomers and 20 heteromers Benchmark results Assembly classification on the benchmark set of 218 structures published in Ponstingl, H., Kabir, T. and Thornton, J. (2003) Automatic inference of protein quaternary structures from crystals. J. Appl. Cryst. 36, 1116-1122. Fitted parameters: Classification error in Gdiss : ± 5 kcal/mol • Free energy of a H-bond : • Free energy of a salt bridge : • Constant entropy term : • Surface entropy factor : = 0.51 kcal/mol = 0.21 kcal/mol = 11.7 kcal/mol = 0.57·10-3 kcal/(mol*Å2)

  12. What is beyond the benchmark set? Classification results obtained for 366 recent depositions into PDB in reference to manual classification in MSD-EBI : 321+45 <=> 321 homomers and 45 heteromers Classification error in Gdiss : ± 5 kcal/mol

  13. Is it ever going to be 100%? Nobody should be that naive, because : • theoretical models for protein affinity and entropy change upon protein complexation are primitive • coordinate (experimental) data is of a limited accuracy • there is no feasible way to take conformations in crystal into account • experimental data on multimeric states is very limited and not always reliable - calibration of parameters is difficult • protein assemblies may exist in some environments and dissociate in other - a definite answer is simply not there

  14. Web-server PISA http://www.ebi.ac.uk/msd-srv/prot_int/pistart.html

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