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Cost Function Networks to Solve Large Computational Protein Design Problems

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Operations Research and Simulation in Healthcare

Abstract

Proteins are chains of simple molecules called amino acids. The sequence of amino acids in the chain defines the three-dimensional shape of the protein and ultimately its biochemical function. Over millions of years, living organisms have evolved a large catalog of proteins. By exploring the space of possible amino acid sequences, protein engineering aims at similarly designing tailored proteins with specific desirable properties such as therapeutic properties in biomedical engineering for healthcare purposes. In computational protein design (CPD), the challenge of identifying a protein that performs a given task is defined as the combinatorial optimization of a complex energy function over amino acid sequences. First, we introduce the CPD problem and some of the main approaches that have been used by structural biologists to solve it. The CPD problem can be formulated as a cost function network (CFN). We present some of the most efficient techniques in CFN. Overall, the CFN approach shows the best efficiency on these problems, improving by several orders of magnitude against the previous exact CPD-dedicated approaches and also against integer programming approaches.

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Notes

  1. 1.

    www.rcsb.org/stats/distribution_residue-count.

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Acknowledgements

This work has been partly funded by the “Agence nationale de la Recherche” (ANR-10-BLA-0214, ANR-12-MONU-0015-03, and ANR-16-CE40-0028).

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Authors and Affiliations

  1. Université Fédérale de Toulouse, ANITI, INRAE, Toulouse, France

    David Allouche, Simon de Givry, Thomas Schiex & Matthias Zytnicki

  2. LISBP, INSA, UMR INRA 792/CNRS 5504, Toulouse, France

    Sophie Barbe

  3. UMR MIA-Paris, INRA, AgroParisTech, University of Paris-Saclay, Paris, France

    George Katsirelos

  4. LITIO, University of Oran 1, Oran, Algeria

    Yahia Lebbah

  5. GREYC, UMR 6072-CNRS, University of Caen Normandy, Caen, France

    Samir Loudni

  6. ORPAILLEUR Team, LORIA, INRIA - Nancy, Vandœuvre-lès-Nancy, France

    Abdelkader Ouali

  7. IRIT, UMR 5505-CNRS, University of Toulouse, Toulouse, France

    David Simoncini

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  1. David Allouche
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    Malek Masmoudi

  2. Department of Business, Higher Colleges of Technology, Abu Dhabi, United Arab Emirates

    Bassem Jarboui

  3. Université Paris-Est Créteil Val-de-Ma, Paris, France

    Patrick Siarry

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Allouche, D. et al. (2021). Cost Function Networks to Solve Large Computational Protein Design Problems. In: Masmoudi, M., Jarboui, B., Siarry, P. (eds) Operations Research and Simulation in Healthcare. Springer, Cham. https://doi.org/10.1007/978-3-030-45223-0_4

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