Local electrostatic optimization in proteins

Loss of protein structure stability as a major causative factor in monogenic disease

The most common cause of monogenic disease is a single base DNA variant resulting in an amino acid substitution. In a previous study, we observed that a high fraction of these substitutions appear to result in reduction of stability of the corresponding protein structure. We have now investigated this phenomenon more fully. A set of structural effects, such as reduction in hydrophobic area, overpacking, backbone strain, and loss of electrostatic interactions, is used to represent the impact of single residue mutations on protein stability. A support vector machine (SVM) was trained on a set of mutations causative of disease, and a control set of non-disease causing mutations. In jack-knifed testing, the method identifies 74% of disease mutations, with a false positive rate of 15%. Evaluation of a set of in vitro mutagenesis data with the SVM established that the majority of disease mutations affect protein stability by 1 to 3 kcal/mol. The method's effective distinction between disease and non-disease variants, strongly supports the hypothesis that loss of protein stability is a major factor contributing to monogenic disease.

Electrostatics in protein-protein docking

A novel geometric-electrostatic docking algorithm is presented, which tests and quantifies the electrostatic complementarity of the molecular surfaces together with the shape complementarity. We represent each molecule to be docked as a grid of complex numbers, storing information regarding the shape of the molecule in the real part and information regarding the electrostatic character of the molecule in the imaginary part. The electrostatic descriptors are derived from the electrostatic potential of the molecule. Thus, the electrostatic character of the molecule is represented as patches of positive, neutral, or negative values. The potential for each molecule is calculated only once and stored as potential spheres adequate for exhaustive rotation/translation scans. The geometric-electrostatic docking algorithm is applied to 17 systems, starting form the structures of the unbound molecules. The results-in terms of the complementarity scores of the nearly correct solutions, their ranking in the lists of sorted solutions, and their statistical uniqueness-are compared with those of geometric docking, showing that the inclusion of electrostatic complementarity in docking is very important, in particular in docking of unbound structures. Based on our results, we formulate several "good electrostatic docking rules": The geometric-electrostatic docking procedure is more successful than geometric docking when the potential patches are large and when the potential extends away from the molecular surface and protrudes into the solvent. In contrast, geometric docking is recommended when the electrostatic potential around the molecules to be docked appears homogeneous, that is, with a similar sign all around the molecule.

Free energy determinants of tertiary structure and the evaluation of protein models

We develop a protocol for estimating the free energy difference between different conformations of the same polypeptide chain. The conformational free energy evaluation combines the CHARMM force field with a continuum treatment of the solvent. In almost all cases studied, experimentally determined structures are predicted to be more stable than misfolded "decoys." This is due in part to the fact that the Coulomb energy of the native protein is consistently lower than that of the decoys. The solvation free energy generally favors the decoys, although the total electrostatic free energy (sum of Coulomb and solvation terms) favors the native structure. The behavior of the solvation free energy is somewhat counterintuitive and, surprisingly, is not correlated with differences in the burial of polar area between native structures and decoys. Rather. the effect is due to a more favorable charge distribution in the native protein, which, as is discussed, will tend to decrease its interaction with the solvent. Our results thus suggest, in keeping with a number of recent studies, that electrostatic interactions may play an important role in determining the native topology of a folded protein. On this basis, a simplified scoring function is derived that combines a Coulomb term with a hydrophobic contact term. This function performs as well as the more complete free energy evaluation in distinguishing the native structure from misfolded decoys. Its computational efficiency suggests that it can be used in protein structure prediction applications, and that it provides a physically well-defined alternative to statistically derived scoring functions.