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An integrative characterisation of proline cis and trans conformers in a disordered peptide

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Pettitt, Alice J., Shukla, Vaibhav Kumar, Figueiredo, Angelo Miguel, Newton, Lydia S., McCarthy, Stephen, Tabor, Alethea B., Heller, Gabriella T., Lorenz, Christian D., Hansen, D. Flemming·2024·Biophysical Journal
DOI 10.1101/2024.05.14.594077PMC PMC11560310

Preprint — published as 10.1016/j.bpj.2024.09.028

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Abstract

Intrinsically disordered proteins (IDPs) often contain proline residues, which undergo cis/trans isomerisation. While molecular dynamics (MD) simulations have the potential to fully characterise the proline cis and trans sub-ensembles, they are limited by the slow timescales of isomerisation and force field inaccuracies. Nuclear magnetic resonance (NMR) spectroscopy can report on ensemble-averaged observables for both the cis and trans proline states, but a full atomistic characterisation of these sub-ensembles is challenging. Given the importance of proline cis/trans isomerisation for influencing the conformational sampling of disordered proteins, we employed a combination of all-atom MD simulations with enhanced sampling (metadynamics), NMR, and small-angle X-ray scattering (SAXS) to characterise the two sub-ensembles of the ORF6 C-terminal region (ORF6 CTR ) from SARS-CoV-2 corresponding to the proline-57 (P57) cis and trans states. We performed MD simulations in three distinct force fields: AMBER03ws, AMBER99SB- disp , and CHARMM36m, which are all optimised for disordered proteins. Each simulation was run for an accumulated time of 180-220 µs until convergence was reached, as assessed by blocking analysis. A good agreement between the cis -P57 populations predicted from metadynamics simulations in AMBER03ws was observed with populations obtained from experimental NMR data. Moreover, we observed good agreement between the radius of gyration predicted from the metadynamics simulations in AMBER03ws and that measured using SAXS. Our findings suggest that both the cis -P57 and trans -P57 conformations of ORF6 CTR are extremely dynamic and that interdisciplinary approaches combining both multi-scale computations and experiments offer avenues to explore highly dynamic states that cannot be reliably characterised by either approach in isolation. SIGNIFICANCE: This study employs MD simulations (with metadynamics), NMR spectroscopy, and SAXS to elucidate the individual cis and trans proline conformations of ORF6 CTR from SARS-CoV-2. The good agreement on proline cis / trans populations observed in experiments (NMR) and those calculated from simulations in the AMBER03ws force field (with SAXS reweighting) showcases the efficiency of this interdisciplinary approach, which can be used to characterise highly dynamic disordered protein states, even for very slow processes. Furthermore, our study emphasises the importance of considering both computational and experimental methodologies to gain a more holistic understanding of highly dynamic proteins. The presented integrative approach sets a precedent for future studies aiming to explore complex and dynamic biological systems with slow transitions such as proline isomerisations.

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Figures

Figure 1 All three force fields predict NAc-ORF6CTR is disordered but only the a03ws and C36m force fields predict that NAc-ORF6CTR undergoes proline cis/trans isomerization. (A) cis-proline (pink) and trans-proline (green) conformations with the positions of Cγ and Cβ indicated. (B) Definition of the ζ (gray) and ψ (purple) dihedral angles used as CVs to enhance proline cis/trans isomerization. (C) Rg probability distributions were calculated using kernel density estimates to compare the a03ws run 1 (orange), a99SB-disp (red), and C36m (blue) ensembles. Ensemble-averaged Rg are shown for each system. The associated error represents the standard deviation between the first and second halves of the analyzed trajectories. The experimental SAXS data and error (standard deviation from the Guinier analysis) are shown in gray. (D) Probability distributions for the ω angle about the Q56-P57 peptide bond in the a03ws run 1 (orange), a99SB-disp (red), and C36m (blue) ensembles. The thickness of the gray distribution represents the uncertainty. The cis-P57 populations are displayed for each system and the error represents the standard deviation between the first and second halves of the analyzed trajectories.
Figure 1 All three force fields predict NAc-ORF6CTR is disordered but only the a03ws and C36m force fields predict that NAc-ORF6CTR undergoes proline cis/trans isomerization. (A) cis-proline (pink) and trans-proline (green) conformations with the positions of Cγ and Cβ indicated. (B) Definition of the ζ (gray) and ψ (purple) dihedral angles used as CVs to enhance proline cis/trans isomerization. (C) Rg probability distributions were calculated using kernel density estimates to compare the a03ws run 1 (orange), a99SB-disp (red), and C36m (blue) ensembles. Ensemble-averaged Rg are shown for each system. The associated error represents the standard deviation between the first and second halves of the analyzed trajectories. The experimental SAXS data and error (standard deviation from the Guinier analysis) are shown in gray. (D) Probability distributions for the ω angle about the Q56-P57 peptide bond in the a03ws run 1 (orange), a99SB-disp (red), and C36m (blue) ensembles. The thickness of the gray distribution represents the uncertainty. The cis-P57 populations are displayed for each system and the error represents the standard deviation between the first and second halves of the analyzed trajectories.CC BY · PubMed Central
Figure 2 NMR verifies the disordered ORF6CTR undergoes proline cis/trans isomerization. (A) 2D 1H-15N HSQC spectrum of 300 μM 15N-labeled ORF6CTR measured at 15°C, pH 6.9, and 14.1 T. Residues colored in green originate from the trans-P57 conformational ensemble, while residues colored in pink and labeled with an asterisk (∗) report on the cis-P57 conformation. The black peak is unassigned. (B) 2D 1H-13C strip taken from the 3D CC(CO)NH spectrum of the 300 μM 13C,15N-labeled ORF6CTR at the 15N chemical shift of M58∗. (C) The ORF6CTR13Cα, 13Cβ, and 1Hα chemical shifts were used to calculate the secondary structure propensity scores for both the cis-P57 and trans-P57 subensembles. A positive value indicates α-helical propensity, a negative value indicates a β-strand propensity, whereas a value near zero indicates random coil. (D) The cis-P57 populations at 15°C (solid fill) and 37°C (dashed fill) are shown for each well-resolved cis-P57 and trans-P57 peak in the 2D 1H-15N HSQC spectrum. The integrated peak volume was used to calculate the mean cis-P57 population and standard deviation across residues E55, Q56, and E59. (E) The van ’t Hoff analysis of P57 cis/trans isomerization determined from the integrated peak volume. The mean natural logarithm of the equilibrium constant for proline cis/trans isomerization about the Q56-P57 peptide bond as a function of temperature was calculated using residues E55, Q56, and E59. Error bars represent the standard deviation across the three residues used in the analysis. The van ’t Hoff linear fit yielded a cis-P57 population of 10 ± 2% at 37°C.
Figure 2 NMR verifies the disordered ORF6CTR undergoes proline cis/trans isomerization. (A) 2D 1H-15N HSQC spectrum of 300 μM 15N-labeled ORF6CTR measured at 15°C, pH 6.9, and 14.1 T. Residues colored in green originate from the trans-P57 conformational ensemble, while residues colored in pink and labeled with an asterisk (∗) report on the cis-P57 conformation. The black peak is unassigned. (B) 2D 1H-13C strip taken from the 3D CC(CO)NH spectrum of the 300 μM 13C,15N-labeled ORF6CTR at the 15N chemical shift of M58∗. (C) The ORF6CTR13Cα, 13Cβ, and 1Hα chemical shifts were used to calculate the secondary structure propensity scores for both the cis-P57 and trans-P57 subensembles. A positive value indicates α-helical propensity, a negative value indicates a β-strand propensity, whereas a value near zero indicates random coil. (D) The cis-P57 populations at 15°C (solid fill) and 37°C (dashed fill) are shown for each well-resolved cis-P57 and trans-P57 peak in the 2D 1H-15N HSQC spectrum. The integrated peak volume was used to calculate the mean cis-P57 population and standard deviation across residues E55, Q56, and E59. (E) The van ’t Hoff analysis of P57 cis/trans isomerization determined from the integrated peak volume. The mean natural logarithm of the equilibrium constant for proline cis/trans isomerization about the Q56-P57 peptide bond as a function of temperature was calculated using residues E55, Q56, and E59. Error bars represent the standard deviation across the three residues used in the analysis. The van ’t Hoff linear fit yielded a cis-P57 population of 10 ± 2% at 37°C.CC BY · PubMed Central
Figure 3 The a03ws force field most accurately predicts the disordered NAc-ORF6CTR ensemble and P57 cis/trans populations after SAXS BME reweighting. (A) The calculated SAXS intensities from the a03ws run 1 metadynamic simulation (orange) and the SAXS BME reweighted simulation (brown) compared with the experimental SAXS intensities (gray), and the error associated with each intensity (gray). (B) Rg probability distributions were calculated using kernel density estimates to compare the SAXS BME reweighted a03ws run 1 ensemble (brown) and the SAXS BME reweighted a03ws run 2 ensemble (teal). The associated error represents the standard deviation between the first and second halves of the analyzed trajectories. The experimental SAXS data and error (standard deviation from the Guinier analysis) are shown in gray. (C) Probability distributions for the ω angle about the Q56-P57 peptide bond in the SAXS BME reweighted a03ws run 1 ensemble (brown) and the SAXS BME reweighted a03ws run 2 ensemble (teal). The two reweighted independent a03ws ensembles were used to calculate the mean cis-P57 population and standard deviation. Additional plots for the SAXS BME reweighted a03ws run 2 and C36m ensembles can be found in the supporting material.
Figure 3 The a03ws force field most accurately predicts the disordered NAc-ORF6CTR ensemble and P57 cis/trans populations after SAXS BME reweighting. (A) The calculated SAXS intensities from the a03ws run 1 metadynamic simulation (orange) and the SAXS BME reweighted simulation (brown) compared with the experimental SAXS intensities (gray), and the error associated with each intensity (gray). (B) Rg probability distributions were calculated using kernel density estimates to compare the SAXS BME reweighted a03ws run 1 ensemble (brown) and the SAXS BME reweighted a03ws run 2 ensemble (teal). The associated error represents the standard deviation between the first and second halves of the analyzed trajectories. The experimental SAXS data and error (standard deviation from the Guinier analysis) are shown in gray. (C) Probability distributions for the ω angle about the Q56-P57 peptide bond in the SAXS BME reweighted a03ws run 1 ensemble (brown) and the SAXS BME reweighted a03ws run 2 ensemble (teal). The two reweighted independent a03ws ensembles were used to calculate the mean cis-P57 population and standard deviation. Additional plots for the SAXS BME reweighted a03ws run 2 and C36m ensembles can be found in the supporting material.CC BY · PubMed Central
Figure 4 NAc-ORF6CTRcis-P57 and trans-P57 subensembles predicted by the a03ws run 1 SAXS BME reweighted metadynamic simulation have very similar profiles. (A) Rg probability distributions were calculated using kernel density estimates to compare the cis-P57 (pink) and trans-P57 (green) conformational subensembles. The associated error represents the standard deviation between the first and second halves of the analyzed trajectory. The experimental SAXS data and error (standard deviation from the Guinier analysis) are shown in gray. (B) Ensemble-averaged Cα minimum distance contact maps for the cis-P57 (pink) and trans-P57 (green) conformations. Color intensity represents the probability of a contact between residues, with white indicating no contact, and increasing color intensity suggesting higher contact probabilities. (C) Secondary structure populations for all residues in the cis-P57 (pink) and the trans-P57 (green) conformations based on SAXS BME statistical weights. Coil populations are represented by solid lines and α-helical populations by dashed lines. β-strand represents less than 0.5% of the population for each residue so was not included. Error bars (black) represent the standard deviation between the first and second halves of the analyzed trajectory. (D) Consistency of the 1HN and 15N cis-P57 and trans-P57 ORF6CTR experimental chemical shifts with the predicted chemical shifts from the reweighted NAc-ORF6CTR a03ws run 1 ensemble. The error in CamShift (silver) is shown. The standard deviation for predicted chemical shifts between the first and second halves of the analyzed trajectory were also plotted but are too small to see. See the supporting material for the a03ws run 2 and C36m analysis.
Figure 4 NAc-ORF6CTRcis-P57 and trans-P57 subensembles predicted by the a03ws run 1 SAXS BME reweighted metadynamic simulation have very similar profiles. (A) Rg probability distributions were calculated using kernel density estimates to compare the cis-P57 (pink) and trans-P57 (green) conformational subensembles. The associated error represents the standard deviation between the first and second halves of the analyzed trajectory. The experimental SAXS data and error (standard deviation from the Guinier analysis) are shown in gray. (B) Ensemble-averaged Cα minimum distance contact maps for the cis-P57 (pink) and trans-P57 (green) conformations. Color intensity represents the probability of a contact between residues, with white indicating no contact, and increasing color intensity suggesting higher contact probabilities. (C) Secondary structure populations for all residues in the cis-P57 (pink) and the trans-P57 (green) conformations based on SAXS BME statistical weights. Coil populations are represented by solid lines and α-helical populations by dashed lines. β-strand represents less than 0.5% of the population for each residue so was not included. Error bars (black) represent the standard deviation between the first and second halves of the analyzed trajectory. (D) Consistency of the 1HN and 15N cis-P57 and trans-P57 ORF6CTR experimental chemical shifts with the predicted chemical shifts from the reweighted NAc-ORF6CTR a03ws run 1 ensemble. The error in CamShift (silver) is shown. The standard deviation for predicted chemical shifts between the first and second halves of the analyzed trajectory were also plotted but are too small to see. See the supporting material for the a03ws run 2 and C36m analysis.CC BY · PubMed Central
Figure 5 ORF6CTR is very dynamic in both the trans-P57 and cis-P57 conformations. (A) 15N longitudinal relaxation rates (R1), (B) 15N transverse relaxation rates (R2), (C) {1H}-15N steady-state hetNOEs, and (D) J(0) values of 300 μM 15N-labeled ORF6CTR at 15°C and pH 6.9. The backbone motions are shown for all peaks corresponding to the trans-P57 conformation (green), and only for the well-resolved peaks with a measurable intensity corresponding to the cis-P57 (pink) conformation. Error bars represent the fitting of the NMR data in (A) and (C). The error bars for (B) were calculated by error propagation. The error bars for (D) represent the standard deviations for each residue, which were calculated using Monte Carlo uncertainty propagation. All experiments were recorded at a static magnetic field strength of 14.1 T.
Figure 5 ORF6CTR is very dynamic in both the trans-P57 and cis-P57 conformations. (A) 15N longitudinal relaxation rates (R1), (B) 15N transverse relaxation rates (R2), (C) {1H}-15N steady-state hetNOEs, and (D) J(0) values of 300 μM 15N-labeled ORF6CTR at 15°C and pH 6.9. The backbone motions are shown for all peaks corresponding to the trans-P57 conformation (green), and only for the well-resolved peaks with a measurable intensity corresponding to the cis-P57 (pink) conformation. Error bars represent the fitting of the NMR data in (A) and (C). The error bars for (B) were calculated by error propagation. The error bars for (D) represent the standard deviations for each residue, which were calculated using Monte Carlo uncertainty propagation. All experiments were recorded at a static magnetic field strength of 14.1 T.CC BY · PubMed Central

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Metadata

Authors
Pettitt, A. J., Shukla, V. K., Figueiredo, A. M., Newton, L. S., McCarthy, S., Tabor, A. B., Heller, G. T., Lorenz, C. D., & Hansen, D. F.
Affiliations
  • King's College London (GB)
  • The Francis Crick Institute (GB)
  • Institute of Structural and Molecular Biology (GB)
Corresponding author
  • Lorenz, Christian D.
  • Hansen, D. Flemming
ORCID
Venue
Biophysical Journal
Publisher
openRxiv
Published
2024-05-15
Volume
123
Issue
21
Pages
3798-3811
ISSN
0006-3495 (ISSN-L)
DOI
10.1101/2024.05.14.594077
PMC
PMC11560310
OpenAlex
W4402879499
Cited by
9
References
1
Citations by year
2026: 6 · 2025: 3
FWCI
1.22
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Biophysical Journal (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • HAL (submittedVersion, cc-by)
  • UCL Discovery (University College London) (submittedVersion, cc-by)
  • Figshare (submittedVersion, cc-by)
  • The Francis Crick Institute (cc-by)
Funders
  • Wellcome Trust (FC001029, 101569/Z/13/Z, MR/N013867/1, 109073/Z/15/Z)
  • Francis Crick Institute (FC001029)
  • Diamond Light Source
  • UK Research and Innovation (EP/X036782/1, MR/N013867/1)
  • Cancer Research UK (FC001029)
  • University College London
  • Partnership for Advanced Computing in Europe AISBL
  • Directorate for Biological Sciences
  • Medical Research Council (FC001029, MR/N013867/1, COVID-19)
  • Engineering and Physical Sciences Research Council (EP/X036782/1)
  • Biotechnology and Biological Sciences Research Council (BB/X009955/1, BB/T008709/1, BB/R000255/1, T008709)
  • Newnham College, University of Cambridge
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
  • Physical Sciences › Chemistry › Organic Chemistry › Chemical Synthesis and Analysis
  • Physical Sciences › Chemistry › Physical and Theoretical Chemistry › Advanced Physical and Chemical Molecular Interactions
Keywords
proline cis-trans isomerization, intrinsically disordered proteins, SARS-CoV-2, cis-trans conformers, metadynamics, force field comparison, CHARMM36m, radius of gyration, small-angle X-ray scattering, nuclear magnetic resonance, conformational dynamics
MeSH terms
SARS-CoV-2, Isomerism, Peptides, Proline, Protein Conformation, Viral Proteins, X-Ray Diffraction, Scattering, Small Angle, Molecular Dynamics Simulation, Intrinsically Disordered Proteins

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