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Proteins. 2001;Suppl 5:68-75.

Fold recognition from sequence comparisons.

Author information

1
Protein Bioinformatics Group, GlaxoSmithKline, Collegeville, Pennsylvania 19426-0989, USA. Kristin.K.Koretke@gsk.com

Abstract

We applied a new protocol based on PSI-Blast to predict the structures of fold recognition targets during CASP4. The protocol used a back-validation step to infer biologically significant connections between sequences with PSI-Blast E-values up to 10. If connections were found to proteins of known structure, alignments were generated by using HMMer. The protocol was implemented in a fully automated version (SBauto) and in a version that allowed manual intervention (SBfold). We found that the automated version made 17 predictions for target domains, of which 8 identified the correct fold with an average alignment accuracy of 24% for alignable residues and 43% for equivalent secondary structure elements. The manual version improved predictions somewhat, with 10 of 15 predictions identifying the correct fold with alignment accuracies of 33% for alignable residues and 64% for equivalent secondary structure elements. We describe successes and failures of our approach and discuss future developments of fold recognition.

PMID:
11835483
[Indexed for MEDLINE]

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