Virtual screening for dipeptide aggregation

toward predictive tools for peptide self-assembly

Pim Frederix, Rein Vincent Ulijn, Neil Hunt, Tell Tuttle

Research output: Contribution to journalArticle

70 Citations (Scopus)

Abstract

Several short peptide sequences are known to self-assemble into supramolecular nanostructures with interesting properties. In this study, coarse-grained molecular dynamics is employed to rapidly screen all 400 dipeptide combinations and predict their ability to aggregate as a potential precursor to their self-assembly. The simulation protocol and scoring method proposed allows a rapid determination of whether a given peptide sequence is likely to aggregate (an indicator for the ability to self-assemble) under aqueous conditions. Systems that show strong aggregation tendencies in the initial screening are selected for longer simulations, which result in good agreement with the known self-assembly or aggregation of dipeptides reported in the literature. Our extended simulations of the diphenylalanine system show that the coarse-grain model is able to reproduce salient features of nanoscale systems and provide insight into the self-assembly process for this system.
Original languageEnglish
Pages (from-to)2380-2384
Number of pages5
JournalJournal of Physical Chemistry Letters
Volume2
Issue number19
Early online date2 Sep 2011
DOIs
Publication statusPublished - 2011

Fingerprint

Dipeptides
Self assembly
Peptides
Screening
Agglomeration
Molecular dynamics
Nanostructures

Keywords

  • dipeptide
  • peptide self-assembly
  • screening
  • TIC - Bionanotechnology

Cite this

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Virtual screening for dipeptide aggregation : toward predictive tools for peptide self-assembly. / Frederix, Pim; Ulijn, Rein Vincent; Hunt, Neil; Tuttle, Tell.

In: Journal of Physical Chemistry Letters, Vol. 2, No. 19, 2011, p. 2380-2384.

Research output: Contribution to journalArticle

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AB - Several short peptide sequences are known to self-assemble into supramolecular nanostructures with interesting properties. In this study, coarse-grained molecular dynamics is employed to rapidly screen all 400 dipeptide combinations and predict their ability to aggregate as a potential precursor to their self-assembly. The simulation protocol and scoring method proposed allows a rapid determination of whether a given peptide sequence is likely to aggregate (an indicator for the ability to self-assemble) under aqueous conditions. Systems that show strong aggregation tendencies in the initial screening are selected for longer simulations, which result in good agreement with the known self-assembly or aggregation of dipeptides reported in the literature. Our extended simulations of the diphenylalanine system show that the coarse-grain model is able to reproduce salient features of nanoscale systems and provide insight into the self-assembly process for this system.

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