Membrane Curvature Sensing by Amphipathic Helices: Insights from Implicit Membrane Modeling

Abstract

Sensing and generation of lipid membrane curvature, mediated by the binding of specific proteins onto the membrane surface, play crucial roles in cell biology. A number of mechanisms have been proposed, but the molecular understanding of these processes is incomplete. All-atom molecular dynamics simulations have offered valuable insights but are extremely demanding computationally. Implicit membrane simulations could provide a viable alternative, but current models apply only to planar membranes. In this work, the implicit membrane model 1 is extended to spherical and tubular membranes. The geometric change from planar to curved shapes is straightforward but insufficient for capturing the full curvature effect, which includes changes in lipid packing. Here, these packing effects are taken into account via the lateral pressure profile. The extended implicit membrane model 1 is tested on the wild-types and mutants of the antimicrobial peptide magainin, the ALPS motif of arfgap1, α-synuclein, and an ENTH domain. In these systems, the model is in qualitative agreement with experiments. We confirm that favorable electrostatic interactions tend to weaken curvature sensitivity in the presence of strong hydrophobic interactions but may actually have a positive effect when those are weak. We also find that binding to vesicles is more favorable than binding to tubes of the same diameter and that the long helix of α-synuclein tends to orient along the axis of tubes, whereas shorter helices tend to orient perpendicular to it. Adoption of a specific orientation could provide a mechanism for coupling protein oligomerization to tubule formation.

Protein structure prediction and design in a biologically-realistic implicit membrane

“…A popular approach to overcoming the computational cost of solvent electrostatics models is the Lazaridis implicit membrane model (IMM1; (34,35)): a Gaussian solvent-exclusion model that uses experimentally measured transfer energies of side-chain analogues in organic solvents to emulate amino acid preferences in the bilayer (36). IMM1 has been applied to various biomolecular modeling problems including studies of antimicrobial peptides (37), de novo folding (38,39), and de novo design of transmembrane helical bundles (11). However, organic solvent slabs differ from phospholipid bilayers because lipids are thermodynamically constrained to a bilayer configuration, resulting in a unique polarity gradient that influences side chain preferences (40)(41)(42).…”

Mechanisms of negative membrane curvature sensing and generation by ESCRT III subunit Snf7

“…In the present work, we use an implicit membrane model adapted to curved membranes to study the binding of Snf7 monomers and oligomers to planar, tubular, and spherical anionic membranes of different curvature. We find that the monomer by itself is curvature sensing but oligomerization also enhances curvature sensitivity.…”

Membrane Interactions of α-Synuclein Revealed by Multiscale Molecular Dynamics Simulations, Markov State Models, and NMR

“…Computational approaches, and in particular MD, have played a key role in exploring the conformational dynamics of α-synuclein and related proteins, both in aqueous solution (28)(29)(30)(31)(32) and when bound to membranes (33)(34)(35)(36)(37)(38)(39). MD simulations have also been shown to be a powerful tool for characterising the interactions of proteins with membrane and lipids (40,41).…”