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. 2023 Dec 6;145(48):26095-26105.
doi: 10.1021/jacs.3c08014. Epub 2023 Nov 21.

How Cell-Penetrating Peptides Behave Differently from Pore-Forming Peptides: Structure and Stability of Induced Transmembrane Pores

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How Cell-Penetrating Peptides Behave Differently from Pore-Forming Peptides: Structure and Stability of Induced Transmembrane Pores

Haleh Alimohamadi et al. J Am Chem Soc. .

Abstract

Peptide-induced transmembrane pore formation is commonplace in biology. Examples of transmembrane pores include pores formed by antimicrobial peptides (AMPs) and cell-penetrating peptides (CPPs) in bacterial membranes and eukaryotic membranes, respectively. In general, however, transmembrane pore formation depends on peptide sequences, lipid compositions, and intensive thermodynamic variables and is difficult to observe directly under realistic solution conditions, with structures that are challenging to measure directly. In contrast, the structure and phase behavior of peptide-lipid systems are relatively straightforward to map out experimentally for a broad range of conditions. Cubic phases are often observed in systems involving pore-forming peptides; however, it is not clear how the structural tendency to induce negative Gaussian curvature (NGC) in such phases is quantitatively related to the geometry of biological pores. Here, we leverage the theory of anisotropic inclusions and devise a facile method to estimate transmembrane pore sizes from geometric parameters of cubic phases measured from small-angle X-ray scattering (SAXS) and show that such estimates compare well with known pore sizes. Moreover, our model suggests that although AMPs can induce stable transmembrane pores for membranes with a broad range of conditions, pores formed by CPPs are highly labile, consistent with atomistic simulations.

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Conflict of interest statement

The authors declare no competing financial interest.

Figures

Figure 1.
Figure 1.
Using induced membrane curvature deformations by NGC-generating inclusions in SAXS spectra to estimate the radius of transmembrane pores generated by pore-forming peptides. Cubic structure and transmembrane pores are both characterized by a saddle shape (NGC) with positive and negative principal curvatures c1>0 and c2<0.
Figure 2.
Figure 2.
Estimating the radius of transmembrane pores induced by pore former peptides based on the generated cubic structures in SAXS experiments. (A) Induced deviatoric curvature D0 in a cubic structure by a pore former peptide is used to estimate the radius of a circular pore in a planar membrane. The transmembrane pore is modeled as a semitoroidal cap with a radius of rp and a height equal to the bilayer thickness 2b(π/2<θ<3π/2). (B) Change in the energy of the system from a planar membrane with no pore to a planar membrane with a single circular pore (eq 5) as the function of the pore radius for three different lattice constants (ap/2=6nm2,σ=0.05As/m2, and ld=1nm,γ=10pN, and using Pn3m). Arrows show the location of minimum energy that corresponds to the radius of a stable transmembrane pore formed in the membrane. (C) Nonmonotonic function of pore radius with increasing the cubic lattice constant (ap/2=6nm2,σ=0.05As/m2, and γ=10pN). (D) Change in the energy of the system as a function of pore radius for different ratios of Debye length to the peptide surface area and induced deviatoric curvature, ζ=ld/ap×D0σ=0.05As/m2 and γ=10pN.
Figure 3.
Figure 3.
Size of transmembrane pores depends on the cubic lattice constant (a), charge density (σ), line tension (γ), and the surface area of the peptide ap. Contour plot of the transmembrane pore radius for a range of (A) cubic lattice constants and Debye length σ=0.05As/m2,ap/2=6nm2, and γ=10pN), (B) cubic lattice constants and charge density (ld=1nm,ap/2=6nm2 and γ=10pN), (C) cubic lattice constants and line tension σ=0.05As/m2,ap/2=6nm2, and ld=1nm, (D) cubic lattice constants and peptide surface area σ=0.05As/m2, and ld=1nm, and γ=10pN). The gray domains in panels (A–D) mark the regions with no pores.
Figure 4.
Figure 4.
Sensitivity analysis of pore sizes induced by AMPs and CPPs to variation in the membrane properties. We used the measured cubic lattice constants of AMPs and CPPs in our previous studies and calculated the pore radius (eq 5) with 20% variation in (A) the Debye length ld, (B) the surface charge density (σ), and (C) the line tension (γ).l0d=1nm,σ0=0.05As/m2, and γ0=10pN. AMPs are robust in generating stable pores with variations in membrane properties.
Figure 5.
Figure 5.
Molecular dynamic simulations to investigate the pore stabilization capability of magainin AMP versus HIV TAT CPP. (A) Structure of the preformed transmembrane pore with five magainin peptides at the beginning of the simulation. (B) Equilibrated structure of the transmembrane pore after 1000 ns long MD simulation. (C) Top and (D) side view of the equilibrated membrane pore without water molecules. Blue and cyan colors represent peptides and lipids, respectively. Oxygen atoms of the water molecules are shown by red spheres. Bile spheres represent the phosphorus atoms of the lipid heads. (E) Zoomed-in image of the pore structure shows that the hydrophobic residues (white) bind with the lipid tails (gray), and the hydrophilic residues (blue and green) are in contact with the water (red). Lipids and water are shown in the “surf” representation. (F) Radius of the pore as a function of simulation time. (G) Structure of the preformed transmembrane pore with five HIV TAT peptides at the beginning of the simulation. (H) Membrane pore closes within only 9 ns of equilibration. (I) Side view of the membrane after the closure of the pore,and the peptides move out from the membrane core. Green and cyan colors represent the HIV TAT peptide and the lipids, respectively.

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