Protein Interaction Property Similarity Analysis

Application examples of PIPSA
(Protein Interaction Property Similarity Analysis)

WW Domains

Plastocyanin mutants analysis

Triose phosphate isomerase kinetic parameter predictions (qPIPSA)

Schleinkofer K. , Wiedemann U. , Otte l., Wang T., Krause G., Oschkinat H. and Wade R.C.
Comparative Structural and Energetic Analysis of WW Domain/Peptide Interactions.
J. Mol. Biol. 2004, 344, 865-881.

WW domains are small globular protein interaction modules found in a wide spectrum of proteins. They recognize their target proteins by binding specifically to short linear peptide motifs that are often proline-rich. To understand the determinants of the ligand binding propensities of WW domains, 42 WW domains were analyzed to derive quantitative structure-activity relationships .
From a protein interaction property similarity analysis (PIPSA) of the WW domain structures, a structure-based classification of WW domains is proposed that expands the existent sequence-based classification scheme.

Representatives of the different classes of WW domains have markedly different electrostatic potentials:
The electrostatic potential is an additional distinguishing feature of WW domains not captured by sequence analysis. It is conserved among those WW domains interacting with peptides containing charged residues. Consistent with the opposite charge of the specificity determining residue within the ligand (arginine and phospho-serine/phospho-threonine respectively), the Ra- and Rb-group members show a conserved negative potential whereas the poS/poT-group members show a conserved positive potential. On the other hand, the hydrophobic potential is equally important for ligand binding for all WW domains and thus cannot be used as a distinguishing feature.
The results of application of pipsa analysis to the models of WW domains can be found here (151 MB) .

Plastocyanin mutants analysis

De Rienzo, F., Gabdoulline,R.R., Menziani,M.C., De Benedetti, P.G. and Wade,R.C.
Electrostatic Analysis and Brownian Dynamics Simulation of the Association of Plastocyanin and Cytochrome F
Biophys. J. (2001) 81, 3090-3104.

The oxidation of cytochrome f by the soluble cupredoxin plastocyanin is a central reaction in the photosynthetic electron transfer chain of all oxygenic organisms. Here, two different computational approaches are used to gain new insights into the role of molecular recognition and protein-protein association processes in this redox reaction.
A comparative analysis of the computed molecular electrostatic potentials of seven single and multiple point mutants of spinach plastocyanin (D42N, E43K, E43N, E43Q/D44N, E59K/E60Q, E59K/E60Q/E43N, Q88E) and the wt protein was carried out. The experimentally determined relative rates (k2) for the set of plastocyanin mutants are found to correlate well (r2 0.90 0.97) with the computed measure of the similarity of the plastocyanin electrostatic potentials:

This approach allows to relate similarity indices to observable association rates. Application of PIPSA to derive this correlation can be downloaded here (10 MB) .

Triose phosphate isomerase kinetic parameter predictions (qPIPSA)
Gabdoulline RR, Stein M, Wade RC
qPIPSA: Relating Enzymatic Kinetic Parameters and Interaction Fields
Januray 2007, Submitted
qPIPSA is for quantitative Protein Interaction Property Similarity Analysis. In this analysis, molecular interaction fields, for example, electrostatic potentials, are computed from the enzyme structure. Differences in molecular interaction fields between enzymes are then related to the ratios of their kinetic parameters. This procedure can be used to determine unknown kinetic parameters when enzyme structural information is available and kinetic parameters have been measured for related enzymes, e.g. orthologues from other species, or under different conditions, e.g. a different pH. The interaction of the enzyme with other molecules is not modeled and is assumed to be similar for the proteins compared. The protein structure modeling protocol employed ensures that differences between models reflect genuine differences between the protein sequences, rather than random fluctuations in protein structure. Provided that the measurement conditions and the protein structural models are consistent, correlations between interaction fields and kinetic parameters can be established for sets of related enzymes or for an enzyme under a range of environmental conditions. Outliers may arise due to variation in the importance of different contributions, such as protein stability and conformational changes, to the kinetic parameters. The qPIPSA approach can assist the estimation and validation of kinetic parameters, and provide insights into enzyme mechanism.
Application of PIPSA to correlate Triose phosphate isomerase kinetic parameters with the electrostatic potential differences in the active site can be found here (60 MB file).

Razif Gabdoulline, 2007