Further developments of protein secondary structure prediction using information theory. New parameters and consideration of residue pairs.

We have re-evaluated the information used in the Garnier-Osguthorpe-Robson (GOR) method of secondary structure prediction with the currently available database. The framework of information theory provides a means to formulate the influence of local sequence upon the conformation of a given residue, in a rigorous manner. However, the existing database does not allow the evaluation of parameters required for an exact treatment of the problem. The validity of the approximations drawn from the theory is examined. It is shown that the first-level approximation, involving single-residue parameters, is only marginally improved by an increase in the database. The second-level approximation, involving pairs of residues, provides a better model. However, in this case the database is not big enough and this method might lead to parameters with deficiencies. Attention is therefore given to overcoming this lack of data. We have determined the significant pairs and the number of dummy observations necessary to obtain the best result for the prediction. This new version of the GOR method increases the accuracy of prediction by 7%, bringing the amount of residues correctly predicted to 63% for three states and 68 proteins, each protein to be predicted being removed from the database and the parameters derived from the other proteins. If the protein to be predicted is kept in the database the accuracy goes up to 69.7%.