Secondary structure predictions and medium range interactions

Abstract

Several authors have proposed that predictions of protein secondary structure derived from statistical information about the known structures can be improved when information about neighboring residues participating in short and medium range interactions is included. A substantial improvement shown here indicates that current methods of including this information are not more successful than methods that do not. Evaluations of the Chou and Fasman method (Adv. Enzymol. 47 (1978) 45-148), that does not include information about interactions (except in averaging), have shown it to be about 49% correct for three states (helix, beta-sheet and undefined). In comparison, the method of Garnier et al. (J. Mol. Biol. 120 (1978) 97-120), that explicitly includes information about neighboring residues, has an accuracy of 57% residues correct for three states. However, we have obtained an 8% improvement for predictions of secondary structure based on the algorithm by Chou and Fasman. The improvements are obtained by eliminating many rules and by choosing the best decision constants for structure assignments. The simplified method described here is 57% correct for three states using preference values calculated in 1978.