Adding the AMBER 14SB Force Field to the Stochastic Titration CpHMD Method

Incorporating pH into molecular dynamics simulations is vital for accurately capturing the fully coupled conformational, energetic, and protonation landscape of many systems. The constant-pH molecular dynamics (CpHMD) methodologies represent state-of-the-art approaches to achieve this, with stochastic titration CpHMD (st-CpHMD) currently being one of the most well-developed and validated methods. St-CpHMD is already compatible with both the GROMOS 54A7 and CHARMM 36m force fields, and we extend it here to support the AMBER 14SB force field available in the GROMACS software package. We introduce and validate a minor modification to the official atomic partial charges of ff14SB (to achieve neutralization of the main chain) to render them compatible with st-CpHMD, and we benchmark the final implementation using lysozyme and Staphylococcal nuclease proteins. Although the root-mean-square error (RMSE) values of the predictions for p<i>K</i><sub>a</sub> versus experimental data align closely with those obtained using the other supported force fields, we also identified several challenging cases where the method requires further improvement. AMBER 14SB simulations showed a lower computational cost compared to CHARMM 36m, despite being slightly higher than the GROMOS 54A7 simulations. Our findings also indicate that to further enhance computational speed, future efforts should concentrate on accelerating the PB/MC step. With this extension, we have developed the first CpHMD method implementation compatible with the three most widely used protein force fields, enabling, for the first time, a direct performance comparison among them.

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Publication Details

Journal
Journal of Chemical Theory and Computation
Published
2025-06-16
DOI
https://doi.org/10.1021/acs.jctc.5c00415
Citations
5
Primary Topic
Protein Structure and Dynamics
Type
article
Field-Weighted Citation Impact
4.03

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article

Adding the AMBER 14SB Force Field to the Stochastic Titration CpHMD Method

Adrián E. Roitberg, João G. N. Sequeira, Miguel Machuqueiro
5 citations
Journal of Chemical Theory and Computation
Protein Structure and Dynamics
4.03
article

Adding the AMBER 14SB Force Field to the Stochastic Titration CpHMD Method

Adrián E. Roitberg, João G. N. Sequeira, Miguel Machuqueiro
article en
5 citations

Abstract

Incorporating pH into molecular dynamics simulations is vital for accurately capturing the fully coupled conformational, energetic, and protonation landscape of many systems. The constant-pH molecular dynamics (CpHMD) methodologies represent state-of-the-art approaches to achieve this, with stochastic titration CpHMD (st-CpHMD) currently being one of the most well-developed and validated methods. St-CpHMD is already compatible with both the GROMOS 54A7 and CHARMM 36m force fields, and we extend it here to support the AMBER 14SB force field available in the GROMACS software package. We introduce and validate a minor modification to the official atomic partial charges of ff14SB (to achieve neutralization of the main chain) to render them compatible with st-CpHMD, and we benchmark the final implementation using lysozyme and Staphylococcal nuclease proteins. Although the root-mean-square error (RMSE) values of the predictions for p<i>K</i><sub>a</sub> versus experimental data align closely with those obtained using the other supported force fields, we also identified several challenging cases where the method requires further improvement. AMBER 14SB simulations showed a lower computational cost compared to CHARMM 36m, despite being slightly higher than the GROMOS 54A7 simulations. Our findings also indicate that to further enhance computational speed, future efforts should concentrate on accelerating the PB/MC step. With this extension, we have developed the first CpHMD method implementation compatible with the three most widely used protein force fields, enabling, for the first time, a direct performance comparison among them.

Journal of Chemical Theory and ComputationVol. 21(13)
University of Lisbon (PT), University of Florida (US)
European Commission, Fundação para a Ciência e a Tecnologia
Openalex Percentile: Top 6%
Protein Structure and Dynamics
4.03
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