Partner: Subhadip Senapati |
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Ostatnie publikacje
1. | Senapati S.♦, Poma Bernaola A., Cieplak M.♦, Filipek S.♦, Park P.♦, Differentiating between inactive and active states of rhodopsin by atomic force microscopy in native membranes, Analytical Chemistry, ISSN: 0003-2700, DOI: 10.1021/acs.analchem.9b00546, Vol.91, No.11, pp.7226-7235, 2019 Streszczenie: Membrane proteins, including G protein-coupled receptors (GPCRs), present a challenge in studying their structural properties under physiological conditions. Moreover, to better understand the activity of proteins requires examination of single molecule behaviors rather than ensemble averaged behaviors. Force–distance curve-based AFM (FD-AFM) was utilized to directly probe and localize the conformational states of a GPCR within the membrane at nanoscale resolution based on the mechanical properties of the receptor. FD-AFM was applied to rhodopsin, the light receptor and a prototypical GPCR, embedded in native rod outer segment disc membranes from photoreceptor cells of the retina in mice. Both FD-AFM and computational studies on coarse-grained models of rhodopsin revealed that the active state of the receptor has a higher Young's modulus compared to the inactive state of the receptor. Thus, the inactive and active states of rhodopsin could be differentiated based on the stiffness of the receptor. Differentiating the states based on the Young's modulus allowed for the mapping of the different states within the membrane. Quantifying the active states present in the membrane containing the constitutively active G90D rhodopsin mutant or apoprotein opsin revealed that most receptors adopt an active state. Traditionally, constitutive activity of GPCRs has been described in terms of two-state models where the receptor can achieve only a single active state. FD-AFM data are inconsistent with a two-state model but instead require models that incorporate multiple active states. Słowa kluczowe: nanoindentation, rhodopsin, GPCR, membrane, biophysics, AFM, active, inactive, molecular dynamics, coarse graining, go-like model Afiliacje autorów:
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