title: Spatial optimization of electrostatic interactions between the ionized groups in globular proteins.
abstract: A model approach is suggested to estimate the degree of spatial optimization of the electrostatic interactions in protein molecules. The method is tested on a set of 44 globular proteins, representative of the available crystallographic data. The theoretical model is based on macroscopic computation of the contribution of charge-charge interactions to the electrostatic term of the free energy for the native proteins and for a big number of virtual structures with randomly distributed on protein surface charge constellations (generated by a Monte-Carlo technique). The statistical probability of occurrence of random structures with electrostatic energies lower than the energy of the native protein is suggested as a criterion for spatial optimization of the electrostatic interactions. The results support the hypothesis that the folding process optimizes the stabilizing effect of electrostatic interactions, but to very different degree for different proteins. A parallel analysis of ion pairs shows that the optimization of the electrostatic term in globular proteins has increasingly gone in the direction of rejecting the repulsive short contacts between charges of equal sign than of creating of more salt bridges (in comparison with the statistically expected number of short-range ion pairs in the simulated random structures). It is observed that the decrease in the spatial optimization of the electrostatic interactions is usually compensated for by an appearance of disulfide bridges in the covalent structure of the examined proteins.
authors.affiliation: Central Laboratory of Biophysics, Bulgarian Academy of Sciences, Sofia.
authors.forename: V Z
authors.initials: VZ
authors.lastname: Spassov
authors.forename: B P
authors.initials: BP
authors.lastname: Atanasov
mesh_terms: D000426:Alcohol Dehydrogenase / Q000737:chemistry; D003198:Computer Simulation; D007477:Ions; D008956:Models, Chemical; D009010:Monte Carlo Method; D009113:Muramidase / Q000737:chemistry; D011487:Protein Conformation; D013816:Thermodynamics
chemical_list: D007477:Ions; D000426:Alcohol Dehydrogenase; D009113:Muramidase