Physical limits to membrane curvature sensing by a single protein.


Journal

Physical review. E
ISSN: 2470-0053
Titre abrégé: Phys Rev E
Pays: United States
ID NLM: 101676019

Informations de publication

Date de publication:
Dec 2023
Historique:
received: 10 11 2022
accepted: 11 09 2023
medline: 20 1 2024
pubmed: 20 1 2024
entrez: 20 1 2024
Statut: ppublish

Résumé

Membrane curvature sensing is essential for a diverse range of biological processes. Recent experiments have revealed that a single nanometer-sized septin protein has different binding rates to membrane-coated glass beads of 1-µm and 3-µm diameters, even though the septin is orders of magnitude smaller than the beads. This sensing ability is especially surprising since curvature-sensing proteins must deal with persistent thermal fluctuations of the membrane, leading to discrepancies between the bead's curvature and the local membrane curvature sensed instantaneously by a protein. Using continuum models of fluctuating membranes, we investigate whether it is feasible for a protein acting as a perfect observer of the membrane to sense micron-scale curvature either by measuring local membrane curvature or by using bilayer lipid densities as a proxy. To do this, we develop algorithms to simulate lipid density and membrane shape fluctuations. We derive physical limits to the sensing efficacy of a protein in terms of protein size, membrane thickness, membrane bending modulus, membrane-substrate adhesion strength, and bead size. To explain the experimental protein-bead association rates, we develop two classes of predictive models: (i) for proteins that maximally associate to a preferred curvature and (ii) for proteins with enhanced association rates above a threshold curvature. We find that the experimentally observed sensing efficacy is close to the theoretical sensing limits imposed on a septin-sized protein. Protein-membrane association rates may depend on the curvature of the bead, but the strength of this dependence is limited by the fluctuations in membrane height and density.

Identifiants

pubmed: 38243534
doi: 10.1103/PhysRevE.108.064407
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

064407

Auteurs

Indrajit Badvaram (I)

Department of Biophysics, Johns Hopkins University, Baltimore, Maryland 21218, USA.

Brian A Camley (BA)

Department of Biophysics, Johns Hopkins University, Baltimore, Maryland 21218, USA.
William H. Miller III Department of Physics & Astronomy, Johns Hopkins University, Baltimore, Maryland 21218, USA.

Classifications MeSH