Differential sensing with arrays of de novo designed peptide assemblies

William M. Dawson*, Kathryn L. Shelley, Jordan M. Fletcher, D. Arne Scott, Lucia Lombardi, Guto G. Rhys, Tania J. LaGambina, Ulrike Obst, Antony J. Burton, Jessica A. Cross, George Davies, Freddie J.O. Martin, Francis J. Wiseman, R. Leo Brady, David Tew, Christopher W. Wood, Derek N. Woolfson

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

Differential sensing attempts to mimic the mammalian senses of smell and taste to identify analytes and complex mixtures. In place of hundreds of complex, membrane-bound G-protein coupled receptors, differential sensors employ arrays of small molecules. Here we show that arrays of computationally designed de novo peptides provide alternative synthetic receptors for differential sensing. We use self-assembling α-helical barrels (αHBs) with central channels that can be altered predictably to vary their sizes, shapes and chemistries. The channels accommodate environment-sensitive dyes that fluoresce upon binding. Challenging arrays of dye-loaded barrels with analytes causes differential fluorophore displacement. The resulting fluorimetric fingerprints are used to train machine-learning models that relate the patterns to the analytes. We show that this system discriminates between a range of biomolecules, drink, and diagnostically relevant biological samples. As αHBs are robust and chemically diverse, the system has potential to sense many analytes in various settings.

Original languageEnglish
Article number383
Number of pages12
JournalNature Communications
Issue number1
Publication statusPublished - 24 Jan 2023

Keywords / Materials (for Non-textual outputs)

  • peptides/chemistry
  • alpha-helical
  • smell
  • protein Conformation


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