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Probing the dynamic landscape of peptides in molecular assemblies by synergized NMR experiments and MD simulations - PubMed

  • ️Mon Jan 01 2024

Probing the dynamic landscape of peptides in molecular assemblies by synergized NMR experiments and MD simulations

Ricky Nencini et al. Commun Chem. 2024.

Abstract

Peptides or proteins containing small biomolecular aggregates, such as micelles, bicelles, droplets and nanodiscs, are pivotal in many fields ranging from structural biology to pharmaceutics. Monitoring dynamics of such systems has been limited by the lack of experimental methods that could directly detect their fast (picosecond to nanosecond) timescale dynamics. Spin relaxation times from NMR experiments are sensitive to such motions, but their interpretation for biomolecular aggregates is not straightforward. Here we show that the dynamic landscape of peptide-containing molecular assemblies can be determined by a synergistic combination of solution state NMR experiments and molecular dynamics (MD) simulations. Solution state NMR experiments are straightforward to implement without an excessive amount of sample, while direct combination of spin relaxation data to MD simulations enables interpretation of dynamic landscapes of peptides and other aggregated molecules. To demonstrate this, we interpret NMR data from transmembrane, peripheral, and tail anchored peptides embedded in micelles. Our results indicate that peptides and detergent molecules do not rotate together as a rigid body, but peptides rotate in a viscous medium composed of detergent micelle. Spin relaxation times also provide indirect information on peptide conformational ensembles. This work gives new perspectives on peptide dynamics in complex biomolecular assemblies.

© 2024. The Author(s).

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1. Experimental results for peptides in SDS micelles.

a Amino acid sequences with 15N labelled residues shown in red for transmembrane GWALP23, peripheral Magainin 2, and mitochondria-directed tail anchor (eElaB(TA), eYqjD(TA), yFis1(TA), and hMff(TA)) peptides. b 1H - 15N HSQC spectra and (c) T1, T2 and hetNOE spin relaxation times measured from the peptides in SDS micelle and sodium-phosphate buffer at 310 K with 850 MHz spectrometer.

Fig. 2
Fig. 2. Spin relaxation times of SDS micelles in water at 307 K.

a Snapshots from MD simulations showing the gel-like phase for Amber simulations and liquid-like phase for CHARMM36 simulations. b Deuterium T1 and T2 spin relaxation data from experiments and MD simulations for isotopically labelled α, γ and ω segments. c Chemical structure of SDS with the assignment of labelled segments. d Effective correlation times, τeff, of each C-H bond in SDS molecules from MD simulations.

Fig. 3
Fig. 3. Effect of micelle size and dimerization on spin relaxation times.

a Spin relaxation times of hMff(TA) peptide as a function of SDS micelle size. The dashed line shows the average over 3 replicas simulated with 1 peptide per micelle. The shaded region is the standard error of the mean calculated from the 3 simulations. b Spin relaxation times of GWALP peptide as a monomer or dimer as a function of the SDS micelle size. c Spin relaxation times of yFis1(TA) peptide in a micelle with 50 SDS molecules as a monomer or dimer. For the dimer, a solid line shows the average over the 2 peptides in a micelle in one simulation. For the monomer, the dashed line is the average taken over 3 replicas. Shaded regions are the standard errors of the mean. d Spin relaxation times of eElaB(TA) peptide in a micelle with 50 SDS molecules as a monomer or dimer, and in a micelle with 40 SDS molecules as a monomer.

Fig. 4
Fig. 4. Spin relaxation times from the best simulations compared with experiments.

a Spin relaxation times from the best simulations and experiments. Experimental values are in the middle of the shown rectangles and the edges represent the experimental error. The lines represent an average over 3 simulation replicas and the shaded region shows the error of the mean. b Representative snapshots of the studied peptides in SDS micelles.

Fig. 5
Fig. 5. Dynamics landscape of micelles with peptides.

Dynamic landscape of (a) peptides and (b) SDS molecules from the simulations in the best agreement with experiments in Fig. 4. The point sizes represent the weight of each timescale in the rotational relaxation process.

Fig. 6
Fig. 6. Rotational dynamics of peptides as a function of micelle size.

Characteristic timescales from Stokes–Einstein equation (black line) and MD simulations for hMff(TA) monomer (red) and GWALP dimer (brown) in micelles with different numbers of SDS molecules. X-axis shows the radius of gyration.

Fig. 7
Fig. 7. Correlations between helicity and spin relaxation times of peptides.

a Three most abundant secondary structures detected by DSSP analysis and spin relaxation times from a simulation of yFis1(TA) in a micelle with 50 SDS molecules. b Scatter plot and Pearson correlation coefficients between helicity and spin relaxation times from individual residues in all simulations listed in Supplementary Tables 1, 2. The local environment helicity on the x-axis is the average over the given residue and the left and the right neighbouring residue if these exist. The colour of a point then encodes for the helicity of the given residue without neighbour averaging. c Pearson correlation coefficients and their p-values between the residual local environment helicity and spin relaxation times calculated separately for individual simulations. d Average helicities over three replicas with representative snapshots from MD simulations.

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