Progress of 1D protein structure prediction at last

TitleProgress of 1D protein structure prediction at last
Publication TypeJournal Article
Year of Publication1995
AuthorsRost, B, Sander, C
KeywordsAmino Acid Sequence *Bacterial Proteins Computer Communication Networks DNA-Binding Proteins/chemistry *Drosophila Proteins Molecular Sequence Data Neural Networks (Computer) *Protein Structure, Secondary RNA-Binding Proteins/chemistry Sequence Alignment Subtilisins/chemistry

Accuracy of predicting protein secondary structure and solvent accessibility from sequence information has been improved significantly by using information contained in multiple sequence alignments as input to a neural network system. For the Asilomar meeting, predictions for 13 proteins were generated automatically using the publicly available prediction method PHD. The results confirm the estimate of 72% three-state prediction accuracy. The fairly accurate predictions of secondary structure segments made the tool useful as a starting point for modeling of higher dimensional aspects of protein structure.