
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.
Models, Molecular, Protein Folding, Glycoside Hydrolases, Protein Conformation, Molecular Sequence Data, Nucleoside-Triphosphatase, Protein Structure, Secondary, Acid Anhydride Hydrolases, Protein Structure, Tertiary, Geobacillus stearothermophilus, Automation, Bacterial Proteins, Sequence Analysis, Protein, Computer Simulation, Amino Acid Sequence, Databases, Protein, Carboxylic Ester Hydrolases, Sequence Alignment, Software, Polysaccharide-Lyases
Models, Molecular, Protein Folding, Glycoside Hydrolases, Protein Conformation, Molecular Sequence Data, Nucleoside-Triphosphatase, Protein Structure, Secondary, Acid Anhydride Hydrolases, Protein Structure, Tertiary, Geobacillus stearothermophilus, Automation, Bacterial Proteins, Sequence Analysis, Protein, Computer Simulation, Amino Acid Sequence, Databases, Protein, Carboxylic Ester Hydrolases, Sequence Alignment, Software, Polysaccharide-Lyases
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 18 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
