The frequency of ion-pair substructures in proteins is quantitatively related to electrostatic potential: a statistical model for nonbonded interactions.
A statistical analysis of ion pairs in protein crystal structures shows that their abundance with respect to uncharged controls is accurately predicted by a Boltzmann-like function of electrostatic potential. It appears that the mechanisms of protein folding and/or evolution combine to produce a "thermal" distribution of local nonbonded interactions, as has been suggested by statistical-mechanical theories. Using this relationship, we develop a maximum likelihood methodology for estimation of apparent energetic parameters from the data base of known structures, and we derive electrostatic potential functions that lead to optimal agreement of observed and predicted ion-pair frequencies. These are similar to potentials of mean force derived from electrostatic theory, but departure from Coulombic behavior is less than has been suggested.
Bryant
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Biometrics Laboratory, Wadsworth Center for Laboratories and Research, New York State Department of Health, Albany 12201-0509.
Lawrence
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D005075:Biological Evolution; D004553:Electric Conductivity; D007477:Ions; D008956:Models, Chemical; D015233:Models, Statistical; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*; D013816:Thermodynamics
D007477:Ions; D011506:Proteins