Generation of photocaged nanobodies for intracellular applications in an animal using genetic code expansion and computationally guided protein engineering**

Jack M.O. Shea, Angeliki Goutou, Jack Brydon, Cyrus R. Sethna, Christopher W. Wood, Sebastian Greiss*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Nanobodies are becoming increasingly popular as tools for manipulating and visualising proteins in vivo. The ability to control nanobody/antigen interactions using light could provide precise spatiotemporal control over protein function. We develop a general approach to engineer photo-activatable nanobodies using photocaged amino acids that are introduced into the target binding interface by genetic code expansion. Guided by computational alanine scanning and molecular dynamics simulations, we tune nanobody/target binding affinity to eliminate binding before uncaging. Upon photo-activation using 365 nm light, binding is restored. We use this approach to generate improved photocaged variants of two anti-GFP nanobodies that function robustly when directly expressed in a complex intracellular environment together with their antigen. We apply them to control subcellular protein localisation in the nematode worm Caenorhabditis elegans. Our approach applies predictions derived from computational modelling directly in a living animal and demonstrates the importance of accounting for in vivo effects on protein-protein interactions.

Original languageEnglish
Article numbere202200321
Number of pages11
JournalChemBioChem
Volume23
Issue number16
Early online date22 Jun 2022
DOIs
Publication statusPublished - 18 Aug 2022

Keywords

  • C. elegans
  • computational alanine scanning
  • nanobodies
  • photocaged non-canonical amino acids
  • protein engineering

Fingerprint

Dive into the research topics of 'Generation of photocaged nanobodies for intracellular applications in an animal using genetic code expansion and computationally guided protein engineering**'. Together they form a unique fingerprint.

Cite this