Correlation functions as a tool for protein modeling and structure analysis

Abstract

Proteins present unique folding structures whose conformations are determined primarily by their amino acid sequences. At present, there is n o algorithm that would correlate the sequences with the structures determined by X-ray analysis or NMR. Comparative modeling of a new protein sequence based on the known structure of a functionally related protein promises to yield model structures that may provide relevant properties of the protein.To analyze the quality of a model structure, a set of correlation functions was derived from calculations on a subset of proteins from the structure database. Twenty-three highly resolved protein structures with resolutions of at least 1.7 A from various protein families were used as the primary database. The purpose of this initial work was to find highly sensitive functions (including statistical error limits for the parameters) that describe properties of "real" proteins. Each correlation described is characterized by the correlation coefficient, the parameters for linear or nonlinear regression (coefficients of the equation), standard deviation and variance, and the confidence limits describing the statistical probability for values to occur within these limits, e.g., the natural variability of the property under examination. In addition, a method was developed for creating reasonably misfolded proteins. The ability of a correlation function to discriminate between the native structure and the misfolded conformations is expressed by the reliability index, which indicates the sensitivity of a correlation function. The term correlation functions thus summarizes a variety of efforts to find a mathematical description for the properties of protein structures, for their correlation, and for their significance.Keywords: homology modeling; model structure verification; protein folding; protein modelThe deduction of the structure of a protein from the amino acid sequence is still an unresolved problem because the protein folding code is not known (Jaenicke, 1987(Jaenicke, , 1988. The rational design of molecular structures of drugs, polymers, proteins, etc. is a central field of research; presently the most promising method of structure prediction is the design of molecules based on sequence homology to known structures by comparative modeling (Blundell et al., 1987;Moult, 1989).Unfortunately, there are no unambiguous criteria at hand that would discriminate between useful and wrong model structures. In this context, a study of a number of parameters has been performed by Novotny and coworkers (1988). Comparing proteins in their native and completely misfolded states, they arrived at the conclusion that there are only a few criteria that are suited to evaluate the quality of a model structure. The most significant ones are (1) the ratio of the solvent-accessible surfaces of apolar and polar side chains, (2) empirical free energy functions, and (3) the number of buried charged atoms. Further studies including three-dimensional profile scores allow localization of differences...

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