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Constant-p H molecular dynamics using stochastic titration

Baptista, António M., Teixeira, Vitor H., Soares, Cláudio M.·2002·The Journal of Chemical Physics

Abstract

A new method is proposed for performing constant-pH molecular dynamics (MD) simulations, that is, MD simulations where pH is one of the external thermodynamic parameters, like the temperature or the pressure. The protonation state of each titrable site in the solute is allowed to change during a molecular mechanics (MM) MD simulation, the new states being obtained from a combination of continuum electrostatics (CE) calculations and Monte Carlo (MC) simulation of protonation equilibrium. The coupling between the MM/MD and CE/MC algorithms is done in a way that ensures a proper Markov chain, sampling from the intended semigrand canonical distribution. This stochastic titration method is applied to succinic acid, aimed at illustrating the method and examining the choice of its adjustable parameters. The complete titration of succinic acid, using constant-pH MD simulations at different pH values, gives a clear picture of the coupling between the trans/gauche isomerization and the protonation process, making it possible to reconcile some apparently contradictory results of previous studies. The present constant-pH MD method is shown to require a moderate increase of computational cost when compared to the usual MD method.

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Metadata

Authors
Baptista, A. M., Teixeira, V. H., & Soares, C. M.
Venue
The Journal of Chemical Physics
Published
2002-09-01
Volume
117
Issue
9
Pages
4184-4200
ISSN
  • 0021-9606 (ISSN-L)
  • 1089-7690
OpenAlex
W2050447276
Cited by
313
References
3
FWCI
3.77
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Constant-p H molecular dynamics using stochastic titration. https://app.cochat.ai/papers/10.1063/1.1497164
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Baptista, A. M., Teixeira, V. H., & Soares, C. M. (2002). Constant-p H molecular dynamics using stochastic titration. The Journal of Chemical Physics. https://doi.org/10.1063/1.1497164

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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