Abstract

The detection of small molecules in living cells using genetically encoded FRET sensors has revolutionized our understanding of signaling pathways at the sub-cellular level. However, engineering fluorescent proteins and specific binding domains to create new sensors remains challenging because of the difficulties associated with the large size of the polypeptides involved, and their intrinsically huge conformational variability. Indeed, FRET sensors’ design still relies on vague structural notions, and trial and error combinations of linkers and protein modules. We recently designed a FRET sensor for the second messenger cAMP named CUTie (Cyclic nucleotide Universal Tag for imaging experiments), which granted sub-micrometer resolution in living cells. Here we apply a combination of sequence/structure analysis to produce a new-generation FRET sensor for the second messenger cGMP based on Protein kinase G I (PKGI), which we named CUTie2. Coarse-grained molecular dynamics simulations achieved an exhaustive sampling of the relevant spatio-temporal coordinates providing a quasi-quantitative prediction of the FRET efficiency, as confirmed by in vitro experiments. Moreover, biochemical characterization showed that the cGMP binding module maintains virtually the same affinity and selectivity for its ligand thant the full-length protein. The computational approach proposed here is easily generalizable to other allosteric protein modules, providing a cost effective-strategy for the custom design of FRET sensors.

Highlights

  • The development of genetically encoded sensors based on Föster resonance energy transfer (FRET) effect is a well-established methodology for the non-invasive and real-time study of a plethora of cellular events (Nikolaev and Lohse, 2006; Berrera et al, 2008; Meng and Sachs, 2011; Calamera et al, 2019).In general, FRET sensors are composed of a molecular detector, which undergoes a conformational change upon a given signal

  • FRET sensors applied to the study of cyclic nucleotides (CNs) have been instrumental for dissecting molecular details of the corresponding signaling pathways, and several protein architectures have been reported to work as FRET sensors for CNs (Sprenger and Nikolaev, 2013; Pendin et al, 2016)

  • This manuscript presents a computational methodology for the design and quasi-quantitative prediction of FRET efficiency of genetically encodable sensors for cyclic guanosine 3′-5′-monophosphate (cGMP)

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Summary

Introduction

The development of genetically encoded sensors based on Föster resonance energy transfer (FRET) effect is a well-established methodology for the non-invasive and real-time study of a plethora of cellular events (Nikolaev and Lohse, 2006; Berrera et al, 2008; Meng and Sachs, 2011; Calamera et al, 2019). FRET sensors are composed of a molecular detector, which undergoes a conformational change upon a given signal. A couple of fluorophores suitable for FRET and linked to convenient domains of the detector module complete the sensor architecture. The use of spectral variants of the Green Fluorescent Protein (GFP) as FRET pairs opened the possibility to generate genetically encoded sensors for monitoring intracellular signaling FRET sensors applied to the study of cyclic nucleotides (CNs) have been instrumental for dissecting molecular details of the corresponding signaling pathways, and several protein architectures have been reported to work as FRET sensors for CNs (Sprenger and Nikolaev, 2013; Pendin et al, 2016)

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