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The GOR Method of Protein Secondary Structure Prediction and Its Application as a Protein Aggregation Prediction Tool

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Prediction of Protein Secondary Structure

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1484))

Abstract

The GOR method of protein secondary structure prediction is described. The original method was published by Garnier, Osguthorpe, and Robson in 1978 and was one of the first successful methods to predict protein secondary structure from amino acid sequence. The method is based on information theory, and an assumption that information function of a protein chain can be approximated by a sum of information from single residues and pairs of residues. The analysis of frequencies of occurrence of secondary structure for singlets and doublets of residues in a protein database enables prediction of secondary structure for new amino acid sequences. Because of these simple physical assumptions the GOR method has a conceptual advantage over other later developed methods such as PHD, PSIPRED, and others that are based on Machine Learning methods (like Neural Networks), give slightly better predictions, but have a “black box” nature. The GOR method has been continuously improved and modified for 30 years with the last GOR V version published in 2002, and the GOR V server developed in 2005. We discuss here the original GOR method and the GOR V program and the web server. Additionally we discuss new highly interesting and important applications of the GOR method to chameleon sequences in protein folding simulations, and for prediction of protein aggregation propensities. Our preliminary studies show that the GOR method is a promising and efficient alternative to other protein aggregation predicting tools. This shows that the GOR method despite being almost 40 years old is still important and has significant potential in application to new scientific problems.

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Acknowledgments

A. Kloczkowski would like to acknowledge support provided by start-up funds from The Research Institute of Nationwide Children’s Hospital. This work was also supported by the Polish Ministry of Science and Higher Education Grant No. IP2012 016872 and “Mobilnosc Plus” No. DN/MOB/069/IV/2015; the National Science Center grant [MAESTRO 2014/14/A/ST6/00088].

Author information

Authors and Affiliations

  1. Faculty of Chemistry, University of Warsaw, Pasteura 1, Warsaw, 02-093, Poland

    Maksim Kouza & Andrzej Kolinski

  2. Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, 46032, USA

    Eshel Faraggi

  3. Battelle Center for MathematicalMedicine, Nationwide Children’s Hospital, 700 Children’s Drive, Columbus, OH, 43215, USA

    Andrzej Kloczkowski

  4. Department of Pediatrics, The Ohio State University College of Medicine, Columbus, OH, 43215, USA

    Andrzej Kloczkowski

  5. Research and Information Systems, LLC, Indianapolis, Indiana, USA

    Eshel Faraggi

Authors
  1. Maksim Kouza
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  2. Eshel Faraggi
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  3. Andrzej Kolinski
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  4. Andrzej Kloczkowski
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Corresponding author

Correspondence to Andrzej Kloczkowski .

Editor information

Editors and Affiliations

  1. Institute for Glycomics and School of Information and Communication Technology, Griffith University, Southport, Queensland, Australia

    Yaoqi Zhou

  2. Battelle Center for Mathematical Medicine, Nationwide Children’s Hospital, Columbus, Ohio, USA

    Andrzej Kloczkowski

  3. Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana, USA

    Eshel Faraggi

  4. Institute for Glycomics and School of Information and Communication Technology, Griffith University, Southport, Queensland, Australia

    Yuedong Yang

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Kouza, M., Faraggi, E., Kolinski, A., Kloczkowski, A. (2017). The GOR Method of Protein Secondary Structure Prediction and Its Application as a Protein Aggregation Prediction Tool. In: Zhou, Y., Kloczkowski, A., Faraggi, E., Yang, Y. (eds) Prediction of Protein Secondary Structure. Methods in Molecular Biology, vol 1484. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-6406-2_2

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  • DOI: https://doi.org/10.1007/978-1-4939-6406-2_2

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-6404-8

  • Online ISBN: 978-1-4939-6406-2

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