Secondary structure of proteins and three-dimensional pattern recognition

We describe a new, parameter-free, method to predict the secondary structure of a protein. It is based on the recognition of well-defined pentapeptides, which allows the discrimination of alpha helices, beta sheets and random coils in proteins. Presently, a success rate of about 65% is achieved for a three-state model.