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Computational Peptidology pp 241–271Cite as

Computational Approaches to Developing Short Cyclic Peptide Modulators of Protein–Protein Interactions

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Part of the book series: Methods in Molecular Biology ((MIMB,volume 1268))

Abstract

Cyclic peptides are a promising class of bioactive molecules potentially capable of modulating “difficult” targets, such as protein–protein interactions. Cyclic peptides have long been used as therapeutics derived from natural product derivatives, but remain an underexplored class of compounds from the perspective of rational drug design, possibly due to the known weaknesses of peptide drugs in general.

While cyclic peptides are non“druglike” by the accepted empirical rules, their unique structure may lend itself to both membrane permeability and proteolytic resistance—the main barriers to oral delivery. The constrained shape of cyclic peptides also lends itself better to virtual screening approaches, and new tools and successes in this area have been recently noted. An increasing number of strategies are available, both to generate and screen cyclic peptide libraries, and best practises and current successes are described within.

This chapter will describe various computational strategies for virtual screening cyclic peptides, along with known implementations and applications. We will explore the generation and screening of diverse combinatorial virtual libraries, incorporating a range of cyclization strategies and structural modifications. More advanced approaches covered include evolutionary algorithms designed to aid in screening large structural libraries, machine learning approaches, and harnessing bioinformatics resources to bias cyclic peptide virtual libraries towards known bioactive structures.

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Acknowledgements

The authors thank Science Foundation Ireland (grant 08 IN.1 B1864) for funding this work.

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Authors and Affiliations

  1. School of Medicine and Medical Science, University College Dublin, Belfield, Dublin 4, Ireland

    Fergal J. Duffy & Denis C. Shields

  2. Complex and Adaptive Systems Laboratory, University College Dublin, Belfield, Dublin 4, Ireland

    Fergal J. Duffy & Denis C. Shields

  3. Department of Chemistry, Royal College of Surgeons in Ireland, 123 St. Stephens Green, Dublin 2, Ireland

    Marc Devocelle

  4. Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Belfield Office Park-8, Belfield, Dublin 4, Ireland

    Fergal J. Duffy & Denis C. Shields

Authors
  1. Fergal J. Duffy
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  2. Marc Devocelle
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  3. Denis C. Shields
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Corresponding author

Correspondence to Denis C. Shields .

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Editors and Affiliations

  1. Center of Bioinformatics (COBI), School of Life Science and Technology, University of Electronic Science and Technology of China (UESTC), Chengdu, China

    Peng Zhou

  2. Center of Bioinformatics (COBI), School of Life Science and Technology, University of Electronic Science and Technology of China (UESTC), Chengdu, China

    Jian Huang

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Duffy, F.J., Devocelle, M., Shields, D.C. (2015). Computational Approaches to Developing Short Cyclic Peptide Modulators of Protein–Protein Interactions. In: Zhou, P., Huang, J. (eds) Computational Peptidology. Methods in Molecular Biology, vol 1268. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-2285-7_11

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  • DOI: https://doi.org/10.1007/978-1-4939-2285-7_11

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  • Print ISBN: 978-1-4939-2284-0

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