Open AccessPHD-an automatic mail server for protein secondary structure prediction
Author(s) -
Burkhard Rost,
Chris Sander,
Reinhard Schneider
Publication year - 1994
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/10.1.53
Subject(s) - protein secondary structure , computer science , protein tertiary structure , protein structure prediction , homology (biology) , sequence homology , homology modeling , protein structure , sequence (biology) , range (aeronautics) , sequence alignment , multiple sequence alignment , computational biology , data mining , bioinformatics , biology , peptide sequence , genetics , engineering , amino acid , biochemistry , gene , enzyme , aerospace engineering
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).
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