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Reactive molecular dynamics study of the pH-dependent dynamic structure of α-helix

Evidence and attribution

Authority of statements

Prose below summarizes the publication identified by doi, title, and pdf_path. For definitive numerical values, use the JPCB article (prefer the version-of-record PDF over this proof ingest when available).

Summary

Peptide secondary structure is often simulated with nonreactive force fields that freeze protonation states or treat pH only implicitly, missing acid–base events that can reshape hydrogen-bond networks during unfolding. This J. Phys. Chem. B article uses ReaxFF reactive MD to follow an α-helix → coil transition as a function of pH for a peptide model, emphasizing proton transfer between solvent and backbone groups that break patterns nonreactive models cannot capture. At extreme pH, the simulations show substantial unraveling driven by solution–peptide proton transfer, and the authors compare temperature effects on the mechanism. The abstract claims significantly better agreement with ab initio references than prior nonreactive MD for the chemistry examined. The corpus PDF is a proof; minor layout differences from the final issue are possible.

Methods

Force field (biomolecular ReaxFF)

  • Simulations use the authors’ published ReaxFF biomolecular parameterization for C/H/O/N chemistry in peptides and water (article introduction/Methods).

Peptide and solvent setup

  • Ala\(_{13}\) is built in a zwitterionic (charged termini) form deemed stable near neutral pH, placed in a 30 Å cubic cell solvated to ~1 g cm\(^{-3}\) liquid-like density (Methods opening on this page).

pH mapping in reactive MD

  • Acidic/basic conditions are explored by adding excess H\(^+\) and OH\(^-\) to the simulation cell rather than a full constant-pH Monte Carlo scheme—an approximate pH proxy consistent with the article’s framing (see Limitations).

Sampling and observables

  • Trajectories monitor α-helix content (or equivalent secondary-structure metrics defined in the paper) as functions of pH and temperature; integration timestep, thermostat, and total runtime are specified in JPCB Methods/SI rather than this proof-oriented wiki summary.

1 — MD application (ReaxFF biomolecular RMD)

  • Engine / code: LAMMPS molecular dynamics with ReaxFF is the typical integration path for this group’s biomolecular RMD workflows—confirm the explicit engine statement in pdf_path / SI.
  • System size & composition: Ala₁₃ zwitterion in a ~30 Å cubic cell solvated to ~1 g cm⁻³ (Methods summary on this page).
  • Boundaries / periodicity: 3D PBC cubic cell (implicit in the 30 Å protocol description).
  • Ensemble: NVT molecular dynamics at 300 K production segments as reported in JPCB Methods—N/A in this wiki summary to quote alternative ensembles without reopening the PDF.
  • Timestep / thermostat / barostat / duration: N/A in this wiki summary—see JPCB Methods/SI (pdf_path) for Δt, thermostat, ps/ns lengths, and any NPT segments if present.
  • Temperature: multiple temperature conditions are compared in the article alongside pH proxies (abstract).
  • Pressure / stress control: N/A — hydrostatic pressure is not part of the summarized NVT-style helix protocol here; confirm if any NPT equilibration appears in SI.
  • Electric field / metadynamics: N/A — not part of the summarized protocol.

2 — Force-field training (this publication)

N/A — uses a published biomolecular ReaxFF parameterization (cited in the article) rather than reporting a new fit in the abstract framing summarized here.

3 — Static QM

N/A — ab initio references enter as benchmarks for selected chemistry, not as the primary MD engine (abstract).

Findings

1 — Outcomes and mechanisms

Reactive MD identifies new proton-transfer mechanisms during denaturation that nonreactive force fields cannot represent, including solution–backbone transfers that disrupt α-helical hydrogen-bonding patterns. At extreme pH, the peptide undergoes substantial unraveling, and temperature modulates the mechanistic details in the comparisons reported. The authors argue reactive sampling aligns more closely with ab initio references than their nonreactive MD baselines for this chemistry, supporting ReaxFF as a tool for pH-coupled peptide dynamics—within the limitations of empirical protonation models.

2 — Comparisons

  • ReaxFF trajectories vs nonreactive MD baselines and ab initio references for selected motifs (abstract).

3 — Sensitivity

  • pH (via excess H⁺/OH⁻) and temperature modulate helix stability and proton-transfer pathways (abstract).

4 — Limitations / outlook

  • Approximate pH mapping; see ## Limitations.

5 — Corpus / KB honesty

  • papers/Golkaram_JPCB_Helix_2014_proof.pdf may differ slightly from the final JPCB layout; quantitative metrics must be taken from the version-of-record PDF when available.

Limitations

Proof PDF; pH in classical reactive MD is an approximate mapping to excess ions and reactive water chemistry, not a full constant-pH formalism.

Citations and evidence anchors