| Abstract: | Protein structural class--alpha, beta, mixed (alpha/beta or alpha + beta), irregular--can be predicted from the amino acid sequence by discriminant analysis. Discrimination is based on distributions, in the classes, of vectors of attributes characterizing the sequences. In this paper, two sets of attributes and two methods of estimating their distributions are compared using more than 100 proteins from the Protein Data Bank. The best results were obtained when canonical variates of the frequencies of occurrence of 20 amino acids and non-parametric estimates of their distributions were used. Three variates are sufficient to allocate proteins to one of four classes with 83% reliability (estimated by cross-validation) and four variates allowed allocation to one of five classes with 78% reliability. |
