title: A weighting method for predicting protein structural class from amino acid composition.
abstract: A protein is generally classified into one of the following four structural classes: all alpha, all beta, alpha+beta and alpha/beta. In this paper, based on the weighting to the 20 constituent amino acids, a new method is proposed for predicting the structural class of a protein according to its amino acid composition. The 20 weighting parameters, which reflect the different properties of the 20 constituent amino acids, have been obtained from a training set of proteins through the linear-programming approach. The rate of correct prediction for a training set of proteins by means of the new method was 100%, whereas the highest rate of previous methods was 82.8%. Furthermore, the results showed that the more numerous training proteins, the more effective the new method.
authors: Department of Physics, Tianjin University, People's Republic of China.
authors: G
authors: G
authors: Zhou
authors: X
authors: X
authors: Xu
authors: C T
authors: CT
authors: Zhang
mesh_terms: D000596:Amino Acids / Q000032:analysis*; D046911:Macromolecular Substances; D008433:Mathematics; D008962:Models, Theoretical; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*; D014961:X-Ray Diffraction
chemical_list: D000596:Amino Acids; D046911:Macromolecular Substances; D011506:Proteins