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Protein Fold Recognition Exploited by Computational and Functional Approaches: Recent Insights

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Handbook of Computational Neurodegeneration

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Abstract

Proteins are important macromolecules in living organisms and serve basic functions in almost all biological processes. The function of a protein depends directly on how the conformation of the polymer sequence is folded. Protein folding is a highly synergistic process and multiple structure prediction models, along with biochemical experimental methods, have been proposed over the last couple of decades with ever-increasing accuracy. Predicting the native three-dimensional structure by settling the folding process code has recently been of great significance in terms of computational complexity and biological limitations, as misfolded protein aggregates have been associated with neurological diseases including Creutzfeldt-Jacob, Alzheimer’s, and Parkinson’s disease. The combination of multiple techniques for developing ensemble methods has led to great improvement in fold prediction accuracy, a field that is considered one of the most fundamental unsolved scientific challenges, the solution of which promises biological and therapeutic breakthroughs.

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Acknowledgments

This research has been co-financed by the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call Regional Excellence (Research Activity in the Ionian University, for the study of protein folding in neurodegenerative diseases) (FOLDIT) MIS 5047144.

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Authors and Affiliations

  1. Bioinformatics and Human Electrophysiology Laboratory, Department of Informatics, Ionian University, Corfu, Greece

    Marios G. Krokidis, Dionysios Cheirdaris, Aristidis G. Vrahatis & Themis P. Exarchos

  2. Hellenic Open University, MSc Program Bioinformatics and Neuroinformatics, Patras, Greece

    Evangelos Efraimidis

Authors
  1. Marios G. Krokidis
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  2. Evangelos Efraimidis
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  3. Dionysios Cheirdaris
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  4. Aristidis G. Vrahatis
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  5. Themis P. Exarchos
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Corresponding author

Correspondence to Marios G. Krokidis .

Editor information

Editors and Affiliations

  1. Department of Informatics, Ionian University, Corfu, Greece

    Panagiotis Vlamos

  2. Wilfrid Laurier University, Waterloo, ON, Canada

    Ilias S. Kotsireas

  3. Altoida Inc, Atlantic Fellow with the Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland

    Ioannis Tarnanas

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Krokidis, M.G., Efraimidis, E., Cheirdaris, D., Vrahatis, A.G., Exarchos, T.P. (2023). Protein Fold Recognition Exploited by Computational and Functional Approaches: Recent Insights. In: Vlamos, P., Kotsireas, I.S., Tarnanas, I. (eds) Handbook of Computational Neurodegeneration. Springer, Cham. https://doi.org/10.1007/978-3-319-75922-7_27

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