Interactive computational and experimental approaches improve the sensitivity of periplasmic binding protein-based nicotine biosensors for measurements in biofluids

Abstract

To develop more sensitive fluorescent protein sensors for nicotine, we combined computational protein design, site-saturated, site-directed, and combinatorial mutagenesis with fluorescence assays, molecular dynamics simulations, and absorbance measurements. The data showed that the resulting molecules, iNicSnFR11 and iNicSnFR12, have higher sensitivity to nicotine than previously reported constructs. In the linear portion of the dose-response relation at sub-μM [nicotine] for iNicSnFR12, ∆F/F₀ increased with a proportionality constant (S-slope) of 2.6 μM⁻¹, representing a 6.5-fold higher sensitivity than iNicSnFR3a. Molecular dynamics calculations enabled identification of a binding pose for nicotine previously indeterminate from experimental data. Further comparative simulations based on this model revealed a tilt in helix 4 in the optimized sensor, likely altering allosteric networks involving the ligand binding site. The absorbance data showed that the fluorescence activation results from increased absorption rather than increased quantum yield for fluorescence. iNicSnFR12 resolved nicotine in diluted mouse and human serum at the peak concentration (100-200 nM) that occurs during smoking or vaping, but also at the decaying concentrations (< 100 nM) during the intervals between smoking or vaping sessions. NicSnFR12 was roughly as sensitive to varenicline or acetylcholine as to nicotine; the sensitivity to choline was at least one order of magnitude less. None of these drugs would markedly distort measurements in human biofluids such as sweat and interstitial fluid. Therefore, iNicSnFR12 is a promising candidate as the molecular sensor that could underlie a continuous nicotine monitor for human biofluids.

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