PHD–an automatic mail server for protein secondary structure prediction

TitlePHD–an automatic mail server for protein secondary structure prediction
Publication TypeJournal Article
Year of Publication1994
AuthorsRost, B, Sander, C, Schneider, R
JournalComput Appl Biosci
Volume10
Pagination53-60
KeywordsAlgorithms Amino Acid Sequence Biological Evolution Computer Communication Networks Databases, Factual Molecular Sequence Data Neural Networks (Computer) *Office Automation *Protein Structure, Secondary Proteins/chemistry/genetics Sequence Alignment/*methods
Abstract

By the middle of 1993, > 30,000 protein sequences has been listed. For 1000 of these, the three-dimensional (tertiary) structure has been experimentally solved. Another 7000 can be modelled by homology. For the remaining 21,000 sequences, secondary structure prediction provides a rough estimate of structural features. Predictions in three states range between 35% (random) and 88% (homology modelling) overall accuracy. Using information about evolutionary conservation as contained in multiple sequence alignments, the secondary structure of 4700 protein sequences was predicted by the automatic e-mail server PHD. For proteins with at least one known homologue, the method has an expected overall three-state accuracy of 71.4% for proteins with at least one known homologue (evaluated on 126 unique protein chains).