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Evolutionary Algorithms for the Inverse Protein Folding Problem

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Abstract

Protein structure prediction is an essential step in understanding the molecular mechanisms of living cells with widespread application in biotechnology and health. The inverse folding problem (IFP) of finding sequences that fold into a defined structure is in itself an important research problem at the heart of rational protein design. In this chapter, a multi-objective genetic algorithm (MOGA) using the diversity-as-objective (DAO) variant of multi-objectivization is presented, which optimizes the secondary structure similarity and the sequence diversity at the same time and hence searches deeper in the sequence solution space. To validate the final optimization results, a subset of the best sequences was selected for tertiary structure prediction. Comparing secondary structure annotation and tertiary structure of the predicted model to the original protein structure demonstrates that relying on fast approximation during the optimization process permits to obtain meaningful sequences.

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Acknowledgements

Work was funded by the National Research Fund of Luxembourg (FNR) as part of the EVOPERF project at the University of Luxembourg with the AFR contract no. 1356145. Experiments were carried out using the HPC facility of the University of Luxembourg [31].

Author information

Authors and Affiliations

  1. Computer Science and Communications (CSC) Research Unit, FSTC, University of Luxembourg, Luxembourg City, Luxembourg

    Sune S. Nielsen, Grégoire Danoy & Pascal Bouvry

  2. The Genome Analysis Centre (TGAC), Norwich Research Park, Norwich, UK

    Wiktor Jurkowski

  3. Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Luxembourg City, Luxembourg

    Roland Krause & Reinhard Schneider

  4. Université des sciences et technologies de Lille, INRIA Lille Nord Europe, Villeneuve d’Ascq, France

    El-Ghazali Talbi

Authors
  1. Sune S. Nielsen
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  2. Grégoire Danoy
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  3. Wiktor Jurkowski
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  4. Roland Krause
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  5. Reinhard Schneider
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  6. El-Ghazali Talbi
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  7. Pascal Bouvry
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Corresponding author

Correspondence to Sune S. Nielsen .

Editor information

Editors and Affiliations

  1. Statistics and Operations Research Department, University of Valencia, Valencia, Spain

    Rafael Martí

  2. Department of Industrial and Systems Engineering, University of Florida, Gainesville, Florida, USA

    Panos M. Pardalos

  3. Amazon.com, Inc. and University of Washington, Seattle, Washington, USA

    Mauricio G. C. Resende

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Nielsen, S.S. et al. (2018). Evolutionary Algorithms for the Inverse Protein Folding Problem. In: Martí, R., Pardalos, P., Resende, M. (eds) Handbook of Heuristics. Springer, Cham. https://doi.org/10.1007/978-3-319-07124-4_59

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