Functional classification of protein toxins as a basis for bioinformatic screening.

Surendra S Negi, Catherine H Schein, Gregory S Ladics, Henry Mirsky, Peter Chang, Jean-Baptiste Rascle, John Kough, Lieven Sterck, Sabitha Papineni, Joseph M Jez, Lucilia Pereira Mouriès, Werner Braun

Journal: Scientific reports 2019;7(1):13940

PMID: 29066768

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Abstract

Proteins are fundamental to life and exhibit a wide diversity of activities, some of which are toxic. Therefore, assessing whether a specific protein is safe for consumption in foods and feeds is critical. Simple BLAST searches may reveal homology to a known toxin, when in fact the protein may pose no real danger. Another challenge to answer this question is the lack of curated databases with a representative set of experimentally validated toxins. Here we have systematically analyzed over 10,000 manually curated toxin sequences using sequence clustering, network analysis, and protein domain classification. We also developed a functional sequence signature method to distinguish toxic from non-toxic proteins. The current database, combined with motif analysis, can be used by researchers and regulators in a hazard screening capacity to assess the potential of a protein to be toxic at early stages of development. Identifying key signatures of toxicity can also aid in redesigning proteins, so as to maintain their desirable functions while reducing the risk of potential health hazards.

Address: Sealy Center for Structural Biology and Molecular Biophysics, Department of Biochemistry and Molecular Biology, University of Texas, Medical Branch, Galveston, TX, 77555-0304, USA.; Foundation for Applied Molecular Evolution, Inc., Alachua, FL, 32615-9495, USA.; DuPont Haskell Laboratory, 1090 Elkton Road, Newark, DE, 19711, USA.; Pioneer Hi-Bred, DuPont Agricultural Biotechnology, 200 Powder Mill Road, Wilmington, DE, 19880, USA.; Bayer SAS, 355 rue Dostoïevski, CS 90153, Valbonne, 06906, Sophia Antipolis, France.; Office of Pesticide Programs, Microbial Pesticides Branch, US Environmental Protection Agency, Washington, DC, USA.; Department of Plant Systems Biology, Department of Plant Biotechnology and Bioinformatics, Ghent University, B-9052, Ghent, Belgium.; Dow AgroSciences LLC, 9330 Zionsville Road, Indianapolis, IN, 46268, USA.; Department of Biology, Washington University in St. Louis, One Brookings Drive, CB 1137, St. Louis, MO, USA.; ILSI Health and Environmental Sciences Institute (HESI), 1156 Fifteenth St., NW, Washington, DC, 20005, USA.; Sealy Center for Structural Biology and Molecular Biophysics, Department of Biochemistry and Molecular Biology, University of Texas, Medical Branch, Galveston, TX, 77555-0304, USA. [email protected].

DOI: 10.1038/s41598-017-13957-1

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https://antibodies.cancer.gov/detail/CPTC-CD48-1

MeSH Terms: Amino Acid Sequence, Cluster Analysis, Computational Biology, Databases, Protein, Gene Order, Models, Molecular, Protein Domains, Proteins, Risk, Toxins, Biological