A continuum model for protein-protein interactions: application to the docking problem.
The prediction of protein-protein interactions in solution is a major goal of theoretical structural biology. Here, we implement a continuum description of the thermodynamic processes involved. The model differs considerably from previous models in its use of "molecular surface" area to describe the hydrophobic component to the free energy of conformational change in solution. We have applied this model to a data set of alternative docked conformations of protein-protein complexes which were generated independently of this work. It was found previously that commonly used energy evaluation techniques fail to distinguish between near-native and certain non-native complexes in this data set. Here, we found that an energy function that takes into account (1) total electrostatic free energy, (2) hydrophobic free energy and (3) loss in side-chain conformational energy was able to reliably discriminate between near-native and non-native configurations but only when molecular surface is used as a descriptor of the hydrophobic effect. It is shown that the molecular surface and the more conventional surface descriptor "solvent accessible surface" give very different quantitative measures of hydrophobicity. In terms of the contribution of different energy components to the free energy of complex formation it was found that loss in side-chain conformational entropy is a second order effect. Electrostatic interaction energy (which is commonly used to score docked conformations) was a poor indicator of complementarity when starting from unbound conformations. It was found that electrostatic desolvation energy and the hydrophobic contribution (based on a molecular surface area descriptor) are much less sensitive to local fluctuations in atomic structure than point-to-point interaction energies and thus may be more suited for use as a scoring function when docking unbound conformations, where atomic complementarity is much less apparent. Whilst a combined energy function was able to distinguish near-native from non-native conformations in the six systems studied here, it remains to be determined to what extent more sizeable conformational changes would influence the results.
Jackson
R M
RM
Biomolecular Modelling Laboratory, Imperial Cancer Research Fund, London, UK.
Sternberg
M J
MJ
D000465:Algorithms; D007611:Aprotinin / Q000737:chemistry / Q000378:metabolism; D002918:Chymotrypsin / Q000037:antagonists & inhibitors / Q000737:chemistry / Q000378:metabolism; D006860:Hydrogen Bonding; D008956:Models, Chemical; D010059:Ovomucin / Q000737:chemistry / Q000378:metabolism; D011485:Protein Binding; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry / Q000378:metabolism*; D013381:Subtilisins / Q000737:chemistry / Q000378:metabolism; D013816:Thermodynamics; D014357:Trypsin / Q000737:chemistry / Q000378:metabolism
D011506:Proteins; D010059:Ovomucin; D007611:Aprotinin; D013381:Subtilisins; D002918:Chymotrypsin; D014357:Trypsin