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Toxins 2018, 10(6), 251; https://doi.org/10.3390/toxins10060251

Classes, Databases, and Prediction Methods of Pharmaceutically and Commercially Important Cystine-Stabilized Peptides

1
Institute of Biomedical Studies, Baylor University, Waco, TX 76798, USA
2
Department of Biology, Baylor University, Waco, TX 76798, USA
3
Department of Computer Science, Baylor University, Waco, TX 76798, USA
*
Author to whom correspondence should be addressed.
Received: 16 May 2018 / Revised: 12 June 2018 / Accepted: 14 June 2018 / Published: 19 June 2018
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Abstract

Cystine-stabilized peptides represent a large family of peptides characterized by high structural stability and bactericidal, fungicidal, or insecticidal properties. Found throughout a wide range of taxa, this broad and functionally important family can be subclassified into distinct groups dependent upon their number and type of cystine bonding patters, tertiary structures, and/or their species of origin. Furthermore, the annotation of proteins related to the cystine-stabilized family are under-represented in the literature due to their difficulty of isolation and identification. As a result, there are several recent attempts to collate them into data resources and build analytic tools for their dynamic prediction. Ultimately, the identification and delivery of new members of this family will lead to their growing inclusion into the repertoire of commercial viable alternatives to antibiotics and environmentally safe insecticides. This review of the literature and current state of cystine-stabilized peptide biology is aimed to better describe peptide subfamilies, identify databases and analytics resources associated with specific cystine-stabilized peptides, and highlight their current commercial success. View Full-Text
Keywords: cystine-stabilized peptides; databases; prediction tools; knottins; cyclotides; STPs; NTPs cystine-stabilized peptides; databases; prediction tools; knottins; cyclotides; STPs; NTPs
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Islam, S.M.A.; Kearney, C.M.; Baker, E. Classes, Databases, and Prediction Methods of Pharmaceutically and Commercially Important Cystine-Stabilized Peptides. Toxins 2018, 10, 251.

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