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Updated: May 11, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction
Published on: November 3, 2011
Prediction and characterization of cyclic proteins from sequences in three domains of life
Pradyumna Kedarisetti1, Marcin J Mizianty, Quentin Kaas
1Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, T6G 2V4, Canada.
Abstract:
Cyclic proteins (CPs) have circular chains with a continuous cycle of peptide bonds. Their unique structural traits result in greater stability and resistance to degradation when compared to their acyclic counterparts. They are also promising targets for pharmaceutical/therapeutic applications. To date, only a few hundred CPs are known, although recent studies suggest that their numbers might be substantially higher. Here we developed a first-of-its-kind, accurate and high-throughput method called CyPred that predicts whether a given protein chain is cyclic. CyPred considers currently well-represented CP families: cyclotides, cyclic defensins, bacteriocins, and trypsin inhibitors. Empirical tests demonstrate that CyPred outperforms commonly used alignment methods. We used CyPred to estimate the incidence of CPs and found ~3500 putative CPs among 5.7+ million chains from 642 fully sequenced proteomes from archaea, bacteria, and eukaryotes. The median number of putative CPs per species ranges from three for archaea proteomes to two for eukaryotes/bacteria, with 7% of archaea, 11% of bacterial, and 16% of eukaryotic proteomes having 10+ CPs. The differences in the estimated fractions of CPs per proteome are as large as three orders of magnitude. Among eukaryotes, animals have higher ratios of CPs compared to fungi, while plants have the largest spread of the ratios. We also show that proteomes enriched in cyclic proteins evolve more slowly than proteomes with fewer cyclic chains. Our results suggest that further research is needed to fully uncover the scope and potential of cyclic proteins. A list of putative CPs and the CyPred method are available at http://biomine.ece.ualberta.ca/CyPred/. This article is part of a Special Issue entitled: Computational Proteomics, Systems Biology & Clinical Implications. Guest Editor: Yudong Cai.
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