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Computational Design of Peptides with Improved Recognition of the Focal Adhesion Kinase FAT Domain

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Computational Peptide Science

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2405))

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Abstract

We describe a two-stage computational protein design (CPD) methodology for the design of peptides binding to the FAT domain of the protein focal adhesion kinase. The first stage involves high-throughput CPD calculations with the Proteus software. The energies of the folded state are described by a physics-based energy function and of the unfolded peptides by a knowledge-based model that reproduces aminoacid compositions consistent with a helicity scale. The obtained sequences are filtered in terms of the affinity and the stability of the complex. In the second stage, design sequences are further evaluated by all-atom molecular dynamics simulations and binding free energy calculations with a molecular mechanics/implicit solvent free energy function.

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Acknowledgements

This work was co-funded by the European Regional Development Fund and the Republic of Cyprus through the Research and Innovation Foundation (Project: INFRASTRUCTURES/1216/0060). EM was supported by a graduate student fellowship from the University of Cyprus.

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Authors and Affiliations

  1. Department of Physics, University of Cyprus, Nicosia, Cyprus

    Eleni Michael, Savvas Polydorides & Georgios Archontis

Authors
  1. Eleni Michael
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  2. Savvas Polydorides
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  3. Georgios Archontis
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Corresponding author

Correspondence to Georgios Archontis .

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Editors and Affiliations

  1. Lab de Biologie Structurale de la Cellule (CNRS UMR7654), Ecole Polytechnique, Palaiseau, France

    Thomas Simonson

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Michael, E., Polydorides, S., Archontis, G. (2022). Computational Design of Peptides with Improved Recognition of the Focal Adhesion Kinase FAT Domain. In: Simonson, T. (eds) Computational Peptide Science. Methods in Molecular Biology, vol 2405. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1855-4_18

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  • DOI: https://doi.org/10.1007/978-1-0716-1855-4_18

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-1854-7

  • Online ISBN: 978-1-0716-1855-4

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