In silico screening of mutational effects on enzyme-proteic inhibitor affinity: a docking-based approach.
BACKGROUND
Molecular recognition between enzymes and proteic inhibitors is crucial for normal functioning of many biological pathways. Mutations in either the enzyme or the inhibitor protein often lead to a modulation of the binding affinity with no major alterations in the 3D structure of the complex.


RESULTS
In this study, a rigid body docking-based approach has been successfully probed in its ability to predict the effects of single and multiple point mutations on the binding energetics in three enzyme-proteic inhibitor systems. The only requirement of the approach is an accurate structural model of the complex between the wild type forms of the interacting proteins, with the assumption that the architecture of the mutated complexes is almost the same as that of the wild type and no major conformational changes occur upon binding. The method was applied to 23 variants of the ribonuclease inhibitor-angiogenin complex, to 15 variants of the barnase-barstar complex, and to 8 variants of the bovine pancreatic trypsin inhibitor-beta Trypsin system, leading to thermodynamic and kinetic estimates consistent with in vitro data. Furthermore, simulations with and without explicit water molecules at the protein-protein interface suggested that they should be included in the simulations only when their positions are well defined both in the wild type and in the mutants and they result to be relevant for the modulation of mutational effects on the association process.


CONCLUSIONS
The correlative models built in this study allow for predictions of mutational effects on the thermodynamics and kinetics of association of three substantially different systems, and represent important extensions of our computational approach to cases in which it is not possible to estimate the absolute free energies. Moreover, this study is the first example in the literature of an extensive evaluation of the correlative weights of the single components of the ZDOCK score on the thermodynamics and kinetics of binding of protein mutants compared to the native state.Finally, the results of this study corroborate and extend a previously developed quantitative model for in silico predictions of absolute protein-protein binding affinities spanning a wide range of values, i.e. from -10 up to -21 kcal/mol. The computational approach is simple and fast and can be used for structure-based design of protein-protein complexes and for in silico screening of mutational effects on protein-protein recognition.
Dell'Orco
Daniele
D
Department of Chemistry, University of Modena and Reggio Emilia, Italy. dellorco@unimo.it <dellorco@unimo.it>
De Benedetti
Pier Giuseppe
PG
Fanelli
Francesca
F
D007611:Aprotinin / Q000378:metabolism; D001426:Bacterial Proteins / Q000378:metabolism; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D004791:Enzyme Inhibitors / Q000378:metabolism*; D004798:Enzymes / Q000235:genetics* / Q000378:metabolism*; D006801:Humans; D007700:Kinetics; D008958:Models, Molecular; D017354:Point Mutation / Q000235:genetics*; D011485:Protein Binding; D012259:Ribonuclease, Pancreatic / Q000378:metabolism; D012260:Ribonucleases / Q000037:antagonists & inhibitors / Q000378:metabolism; D013816:Thermodynamics; D014357:Trypsin / Q000378:metabolism
D001426:Bacterial Proteins; D004791:Enzyme Inhibitors; D004798:Enzymes; C057438:barstar protein, Bacillus amyloliquefaciens; D007611:Aprotinin; D012260:Ribonucleases; C019760:Bacillus amyloliquefaciens ribonuclease; C046366:angiogenin; D012259:Ribonuclease, Pancreatic; D014357:Trypsin