HotPatch: a statistical approach to finding biologically relevant features on protein surfaces.

We describe a fully automated algorithm for finding functional sites on protein structures. Our method finds surface patches of unusual physicochemical properties on protein structures, and estimates the patches' probability of overlapping functional sites. Other methods for predicting the locations of specific types of functional sites exist, but in previous analyses, it has been difficult to compare methods when they are applied to different types of sites. Thus, we introduce a new statistical framework that enables rigorous comparisons of the usefulness of different physicochemical properties for predicting virtually any kind of functional site. The program's statistical models were trained for 11 individual properties (electrostatics, concavity, hydrophobicity, etc.) and for 15 neural network combination properties, all optimized and tested on 15 diverse protein functions. To simulate what to expect if the program were run on proteins of unknown function, as might arise from structural genomics, we tested it on 618 proteins of diverse mixed functions. In the higher-scoring top half of all predictions, a functional residue could typically be found within the first 1.7 residues chosen at random. The program may or may not use partial information about the protein's function type as an input, depending on which statistical model the user chooses to employ. If function type is used as an additional constraint, prediction accuracy usually increases, and is particularly good for enzymes, DNA-interacting sites, and oligomeric interfaces. The program can be accessed online (at http://hotpatch.mbi.ucla.edu).

Side-chain contributions to membrane protein structure and stability.

The molecular forces that stabilize membrane protein structure are poorly understood. To investigate these forces we introduced alanine substitutions at 24 positions in the B helix of bacteriorhodopsin and examined their effects on structure and stability. Although most of the results can be rationalized in terms of the folded structure, there are a number of surprises. (1) We find a remarkably high frequency of stabilizing mutations (17%), indicating that membrane proteins are not highly optimized for stability. (2) Helix B is kinked, with the kink centered around Pro50. The P50A mutation has no effect on stability, however, and a crystal structure reveals that the helix remains bent, indicating that tertiary contacts dominate in the distortion of this helix. (3) We find that the protein is stabilized by about 1kcal/mol for every 38A(2) of surface area buried, which is quite similar to soluble proteins in spite of their dramatically different environments. (4) We find little energetic difference, on average, in the burial of apolar surface or polar surface area, implying that van der Waals packing is the dominant force that drives membrane protein folding.