PreprintCited by 26Protein Structure and DynamicsAlzheimer's disease research and treatmentsAdvanced Physical and Chemical Molecular Interactions

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Protocols for Multi-Scale Molecular Dynamics Simulations: A Comparative Study for Intrinsically Disordered Amyloid Beta in Amber & Gromacs on CPU & GPU

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Smardz, Pamela, Anila, Midhun Mohan, Rogowski, Pawel, Li, Mai Suan, Różycki, Bartosz, Krupa, Pawel·2023·International Journal of Molecular Sciences

Preprint — published as 10.3390/ijms25126698

Abstract

Intrinsically disordered proteins (IDPs) present challenges to conventional experimental techniques due to their large-scale conformational fluctuations and the transient occurrence of structural elements. This work illustrates computational methods for studying IDPs at various levels of resolution. The included simulation protocol offers a step-by-step guide on how to conduct molecular dynamics (MD) simulations and analyze the results using the Amber and Gromacs packages, employing both all-atom and coarse-grained approaches. This protocol can be easily adapted to study other biomacromolecules, including folded and disordered proteins and peptides. Furthermore, it is discussed in this work how to perform standard molecular modeling operations, such as amino-acid substitutions (mutagenesis) and insertions of residues missing in a protein structure, as well as how to incorporate post-translational modifications into the simulations, such as disulfide bonds, which are often crucial for proteins to attain their physiologically functional structure. In conventional MD studies, disulfide bonds are typically fixed at the preparation step and remain unchanged throughout the simulations, unable to break or reform. Here, in contrast, a dynamic approach is presented. It involves adequate distance restraints applied to the sulfur atoms of selected cysteine residues, allowing disulfide bonds to break and reform during the simulation. The effectiveness of these methodologies is demonstrated by examining a model IDP, the monomeric form of 1-42 amyloid-β (Aβ42), both with and without disulfide bonds, at different levels of resolution. This study not only contributes to our understanding of the role of disulfide bonds but also provides detailed simulation protocols that can serve as a foundation for future investigations. SUMMARY: Given the challenges of experimental studies on intrinsically disordered proteins, this manuscript demonstrates step-by-step protocols for conducting all-atom and coarse-grained molecular dynamics simulations using two widespread packages, Amber and Gromacs. The monomeric form of 1-42 amyloid-β (Aβ42) is used as an example, from which insights into the structure, dynamics and physicochemical properties of this protein can be obtained.

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Figures

Figure A1 Schematic workflow for performing typical molecular dynamics simulations.
Figure A1 Schematic workflow for performing typical molecular dynamics simulations.CC BY · PubMed Central
Figure A2 Visualization of the simulation boxes using both all-atom and coarse-grained methods. Atoms or interaction centers (beads) are represented as spheres in red (water), black (ions), and blue (Aβ42 peptide). To save computational time, the MD simulations in the Amber package employed a truncated octahedron box, while the Martini simulations used a standard cubic box.
Figure A2 Visualization of the simulation boxes using both all-atom and coarse-grained methods. Atoms or interaction centers (beads) are represented as spheres in red (water), black (ions), and blue (Aβ42 peptide). To save computational time, the MD simulations in the Amber package employed a truncated octahedron box, while the Martini simulations used a standard cubic box.CC BY · PubMed Central
Figure A3 Time evolution of the minimum non-self image distance in the all-atom Amber ff19SB simulations of Aβ42 (A), of Aβ42 with the static disulfide bond (B), and of Aβ42 with the dynamic disulfide bond (C), as well as in the SIRAH coarse-grained simulations of Aβ42 (D) and of Aβ42 with the static disulfide bond (E). Different colors are used to indicate various trajectories.
Figure A3 Time evolution of the minimum non-self image distance in the all-atom Amber ff19SB simulations of Aβ42 (A), of Aβ42 with the static disulfide bond (B), and of Aβ42 with the dynamic disulfide bond (C), as well as in the SIRAH coarse-grained simulations of Aβ42 (D) and of Aβ42 with the static disulfide bond (E). Different colors are used to indicate various trajectories.CC BY · PubMed Central
Figure A4 Time evolution of the radius of gyration (A–E) and of the maximum dimension (F–J) obtained from the MD simulations employing the all-atom Amber force field ff19SB (A–C,F–H) and SIRAH coarse-grained force field (D,E,I,J) without the disulfide bond (A,D,F,I), with the static disulfide bond (B,E,G,J), and with the dynamic treatment of the disulfide bond (C,H). Different colors are used to indicate various trajectories.
Figure A4 Time evolution of the radius of gyration (A–E) and of the maximum dimension (F–J) obtained from the MD simulations employing the all-atom Amber force field ff19SB (A–C,F–H) and SIRAH coarse-grained force field (D,E,I,J) without the disulfide bond (A,D,F,I), with the static disulfide bond (B,E,G,J), and with the dynamic treatment of the disulfide bond (C,H). Different colors are used to indicate various trajectories.CC BY · PubMed Central
Figure A5 Time evolution of the radius of gyration (A,B) and of the maximum dimension (C,D) obtained from the Martini simulations of Aβ42 (A,C) and Aβ42disul (B,D) with λ = 1. Both Aβ42 and Aβ42disul exhibit large conformational fluctuations at the thermodynamic equilibrium. Because of the constraint imposed by the covalent bond between Cys17 and Cys34, Aβ42disul exhibits smaller values of Rg and Dmax than Aβ42.
Figure A5 Time evolution of the radius of gyration (A,B) and of the maximum dimension (C,D) obtained from the Martini simulations of Aβ42 (A,C) and Aβ42disul (B,D) with λ = 1. Both Aβ42 and Aβ42disul exhibit large conformational fluctuations at the thermodynamic equilibrium. Because of the constraint imposed by the covalent bond between Cys17 and Cys34, Aβ42disul exhibits smaller values of Rg and Dmax than Aβ42.CC BY · PubMed Central
Figure 1 Histograms of Rg values obtained from the simulations in Amber ff19SB (panels A–C), SIRAH (panels D,E), and Martini 3 (panels F,G) force fields for wild-type (panels A,D,F) and disulfide-bond mutants (panels B,C,E,G).
Figure 1 Histograms of Rg values obtained from the simulations in Amber ff19SB (panels A–C), SIRAH (panels D,E), and Martini 3 (panels F,G) force fields for wild-type (panels A,D,F) and disulfide-bond mutants (panels B,C,E,G).CC BY · PubMed Central
Figure 2 Histograms of Dmax values obtained from the simulations in Amber ff19SB (panels A–C), SIRAH (panels D,E), and Martini 3 (panels F,G) force fields for wild-type (panels A,D,F) and disulfide-bond mutants (panels B,C,E,G).
Figure 2 Histograms of Dmax values obtained from the simulations in Amber ff19SB (panels A–C), SIRAH (panels D,E), and Martini 3 (panels F,G) force fields for wild-type (panels A,D,F) and disulfide-bond mutants (panels B,C,E,G).CC BY · PubMed Central
Figure 3 Energy landscapes calculated based on the end-to-end distance and Rg values in all trajectories in Amber ff19SB (panels A–C), SIRAH (panels D,E), and Martini 3 (panels F,G) force fields for wild-type (panels A,D,F) and disulfide-bond mutants (panels B,C,E,G).
Figure 3 Energy landscapes calculated based on the end-to-end distance and Rg values in all trajectories in Amber ff19SB (panels A–C), SIRAH (panels D,E), and Martini 3 (panels F,G) force fields for wild-type (panels A,D,F) and disulfide-bond mutants (panels B,C,E,G).CC BY · PubMed Central
Figure 4 Propensity for amino-acid residues to form β-strands (green) or α-helices (violet), averaged over simulation time and trajectories in Amber ff19SB (panels A–C), SIRAH (panels D,E), and Martini 3 (panels F,G) force fields for wild-type (panels A,D,F) and disulfide-bond mutants (panels B,C,E,G).
Figure 4 Propensity for amino-acid residues to form β-strands (green) or α-helices (violet), averaged over simulation time and trajectories in Amber ff19SB (panels A–C), SIRAH (panels D,E), and Martini 3 (panels F,G) force fields for wild-type (panels A,D,F) and disulfide-bond mutants (panels B,C,E,G).CC BY · PubMed Central
Figure 5 Average radius of gyration, Rg, as a function of the water-protein interaction rescaling parameter λ obtained from the Martini simulations of Aβ42 (blue) and Aβ42disul (red). The error bars indicate the standard deviation calculated over a single trajectory using block averaging.
Figure 5 Average radius of gyration, Rg, as a function of the water-protein interaction rescaling parameter λ obtained from the Martini simulations of Aβ42 (blue) and Aβ42disul (red). The error bars indicate the standard deviation calculated over a single trajectory using block averaging.CC BY · PubMed Central
Figure 6 Energy landscapes based on the end-to-end distance and Rg distributions obtained from the Martini 3 simulations of Aβ42 (upper panels: A–C) and Aβ42disul (lower panels D,F) with the solute-solvent scaling parameter λ set to 0.98 (left panels: A,D), 1.00 (center panels: B,E), and 1.02 (right panels: C,F).
Figure 6 Energy landscapes based on the end-to-end distance and Rg distributions obtained from the Martini 3 simulations of Aβ42 (upper panels: A–C) and Aβ42disul (lower panels D,F) with the solute-solvent scaling parameter λ set to 0.98 (left panels: A,D), 1.00 (center panels: B,E), and 1.02 (right panels: C,F).CC BY · PubMed Central
Figure 7 Ribbon representation of the structures from the MD simulations with the all-atom Amber ff19SB (A,D), coarse-grained SIRAH (B,E) and coarse-grained Martini 3 (C,F) force fields with the maximum (A–C) and minimum (D–F) Rg values shown in blue and red, respectively. Disulfide bonds are marked as yellow sticks.
Figure 7 Ribbon representation of the structures from the MD simulations with the all-atom Amber ff19SB (A,D), coarse-grained SIRAH (B,E) and coarse-grained Martini 3 (C,F) force fields with the maximum (A–C) and minimum (D–F) Rg values shown in blue and red, respectively. Disulfide bonds are marked as yellow sticks.CC BY · PubMed Central
Figure 8 Cartoon representation of the most abundant Aβ42 conformations determined from the clustering analysis in Amber ff19SB (panels A–C), SIRAH (panels D,E), and Martini 3 (panels F,G) force fields for wild-type (panels A,D,F) and disulfide-bond mutants (panels B,C,E,G). The population percentages are given below the snapshots. The peptide structure is rainbow colored from blue (N-terminus) to red (C-terminus).
Figure 8 Cartoon representation of the most abundant Aβ42 conformations determined from the clustering analysis in Amber ff19SB (panels A–C), SIRAH (panels D,E), and Martini 3 (panels F,G) force fields for wild-type (panels A,D,F) and disulfide-bond mutants (panels B,C,E,G). The population percentages are given below the snapshots. The peptide structure is rainbow colored from blue (N-terminus) to red (C-terminus).CC BY · PubMed Central
Figure 9 Contact maps obtained from coarse-grained structures of Aβ42 (A) and Aβ42disul (B) generated in the Martini simulations with λ = 1 (no scaling of solute-solvent interactions). The color scale indicates the natural logarithm of contact frequency. The points in red, yellow, and blue represent frequent, transient, and rare contacts, respectively.
Figure 9 Contact maps obtained from coarse-grained structures of Aβ42 (A) and Aβ42disul (B) generated in the Martini simulations with λ = 1 (no scaling of solute-solvent interactions). The color scale indicates the natural logarithm of contact frequency. The points in red, yellow, and blue represent frequent, transient, and rare contacts, respectively.CC BY · PubMed Central
Figure 10 The final structure obtained from the Martini simulation of Aβ42disul is shown in three different representations. (A) The coarse-grained structure, where the backbone and sidechain beads are colored in red and gray, respectively. The SC1 beads of Cys17 and Cys34 are highlighted in yellow. (B) The all-atom structure, as obtained from the backmapping calculation, is displayed in a stick-and-ball representation. The backbone atoms are shown in red. The sidechain carbon, nitrogen, and oxygen atoms are shown in gray, blue, and red, respectively. The sulfur atoms forming the covalent disulfide bridge are highlighted in yellow. (C) The all-atom structure is presented in a ribbon representation: the main chain is shown in red, while sidechains are not displayed, except for Cys17 and Cys34, which are shown in the stick representation with sulfur atoms forming a disulfide bond marked in yellow.
Figure 10 The final structure obtained from the Martini simulation of Aβ42disul is shown in three different representations. (A) The coarse-grained structure, where the backbone and sidechain beads are colored in red and gray, respectively. The SC1 beads of Cys17 and Cys34 are highlighted in yellow. (B) The all-atom structure, as obtained from the backmapping calculation, is displayed in a stick-and-ball representation. The backbone atoms are shown in red. The sidechain carbon, nitrogen, and oxygen atoms are shown in gray, blue, and red, respectively. The sulfur atoms forming the covalent disulfide bridge are highlighted in yellow. (C) The all-atom structure is presented in a ribbon representation: the main chain is shown in red, while sidechains are not displayed, except for Cys17 and Cys34, which are shown in the stick representation with sulfur atoms forming a disulfide bond marked in yellow.CC BY · PubMed Central

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Metadata

Authors
Smardz, P., Anila, M. M., Rogowski, P., Li, M. S., Różycki, B., & Krupa, P.
Affiliations
Institute of Physics (PL)
Venue
International Journal of Molecular Sciences
Publisher
openRxiv
Published
2023-10-24
Volume
25
Issue
12
Pages
6698-6698
ISSN
1422-0067 (ISSN-L)
OpenAlex
W4399863716
Cited by
26
References
1
Citations by year
2026: 10 · 2025: 12 · 2024: 4
FWCI
3.53
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • International Journal of Molecular Sciences (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Funders
  • Narodowym Centrum Nauki (2020/39/B/NZ1/00377, 2019/35/D/ST4/03156)
  • China Scholarship Council
  • Infrastruktura PL-Grid
  • Academic Computer Centre Cyfronet, AGH University of Science and Technology
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
  • Physical Sciences › Chemistry › Physical and Theoretical Chemistry › Advanced Physical and Chemical Molecular Interactions
Keywords
intrinsically disordered proteins, amyloid-beta 42, disulfide bonds, amyloid fibril formation, all-atom molecular dynamics, coarse-grained molecular dynamics, Martini 3 force field, biography of Muhammad, OPC water model, secondary structure content, chemical shift prediction, protein aggregation
MeSH terms
Disulfides, Humans, Peptide Fragments, Protein Conformation, Amyloid beta-Peptides, Protein Structure, Secondary, Molecular Dynamics Simulation, Intrinsically Disordered Proteins

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