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Prediction of Cell-Penetrating Peptides

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Cell-Penetrating Peptides

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1324))

Abstract

The in silico methods for the prediction of the cell-penetrating peptides are reviewed. Those include the multivariate statistical methods, machine-learning methods such as the artificial neural networks and support vector machines, and molecular modeling techniques including molecular docking and molecular dynamics.

The applicability of the methods is demonstrated on the basis of the exemplary cases from the literature.

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Author information

Authors and Affiliations

  1. Department of Neurochemistry, Stockholm University, Stockholm, Sweden

    Mattias Hällbrink

  2. Institute of Chemistry, University of Tartu, Ravila 14a, 50411, Tartu, Estonia

    Mati Karelson

Authors
  1. Mattias Hällbrink
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  2. Mati Karelson
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Corresponding author

Correspondence to Mati Karelson .

Editor information

Editors and Affiliations

  1. Department of Neurochemistry, Stockholm University, Stockholm, Sweden

    Ãœlo Langel

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Hällbrink, M., Karelson, M. (2015). Prediction of Cell-Penetrating Peptides. In: Langel, Ü. (eds) Cell-Penetrating Peptides. Methods in Molecular Biology, vol 1324. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-2806-4_3

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  • DOI: https://doi.org/10.1007/978-1-4939-2806-4_3

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-2805-7

  • Online ISBN: 978-1-4939-2806-4

  • eBook Packages: Springer Protocols

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