ArticleProceedings of the National Academy of Sciences of the United States of America2000
Predicting protein function from structure: unique structural features of proteases.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2000. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed.
- Molecular and in vivo studies of a glutamate-class prolyl-endopeptidase for coeliac disease therapy.Nature communications · 2022Article
- Gene Ontology Capsule GAN: an improved architecture for protein function prediction.PeerJ. Computer science · 2022Article
- Computational analysis of protein-protein interfaces involving an alpha helix: insights for terphenyl-like molecules binding.BMC pharmacology & toxicology · 2013Article
- Cold-active winter rye glucanases with ice-binding capacity.Plant physiology · 2006Article
- Article
- Prediction of novel archaeal enzymes from sequence-derived features.Protein science : a publication of the Protein Society · 2002Article
- Annotation transfer for genomics: measuring functional divergence in multi-domain proteins.Genome research · 2001Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
We have noted consistent structural similarities among unrelated proteases. In comparison with other proteins of similar size, proteases have smaller than average surface areas, smaller radii of gyration, and higher C(alpha) densities. These findings imply that proteases are, as a group, more tightly packed than other proteins. There are also notable differences in secondary structure content between these two groups of proteins: proteases have fewer helices and more loops. We speculate that both high packing density and low alpha-helical content coevolved in proteases to avoid autolysis. By using the structural parameters that seem to show some separation between proteases and nonproteases, a neural network has been trained to predict protease function with over 86% accuracy. Moreover, it is possible to identify proteases whose folds were not represented during training. Similar structural analyses may be useful for identifying other classes of proteins and may be of great utility for categorizing the flood of structures soon to flow from structural genomics initiatives.
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Registered trials
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