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Extending the Stochastic Titration CpHMD to CHARMM36m.

João G N Sequeira1, Filipe E P Rodrigues1, Telmo G D Silva1

  • 1BioISI - Instituto de Biossistemas e Ciências Integrativas, Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisboa, Portugal.

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Constant-pH Molecular Dynamics (CpHMD) simulations now support the CHARMM36m force field, enhancing protein studies. This advancement improves computational efficiency and accuracy in predicting protein behavior across various pH conditions.

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Area of Science:

  • Computational Biology
  • Biophysics
  • Biochemistry

Background:

  • Protein behavior is significantly influenced by pH, a factor often overlooked in molecular dynamics simulations.
  • Constant-pH Molecular Dynamics (CpHMD) is a key method for studying these effects but has limited adoption.
  • Stochastic titration CpHMD previously supported only the GROMOS force field family.

Purpose of the Study:

  • To extend the stochastic titration CpHMD method to include the CHARMM36m force field within the GROMACS software package.
  • To evaluate the performance and efficiency of this new implementation across various protein systems.
  • To broaden the applicability of CpHMD for studying pH-dependent protein behavior.

Main Methods:

  • Implemented CHARMM36m force field support for stochastic titration CpHMD in GROMACS.
  • Tested the extended CpHMD method on lysozyme, Staphylococcal nuclease, and human and E. coli thioredoxins.
  • Assessed protein conformational stability and pKa prediction accuracy against experimental data.

Main Results:

  • Proteins remained conformationally stable across a range of extreme pH values.
  • Encouraging Root Mean Square Error (RMSE) values for pKa prediction were observed, particularly for lysozyme and human thioredoxin.
  • The CHARMM36m implementation demonstrated improved computational efficiency compared to GROMOS 54A7.

Conclusions:

  • The extended CpHMD method with CHARMM36m is a stable and computationally efficient approach for simulating pH effects on proteins.
  • This advancement enables the study of diverse systems, including membrane proteins and nucleic acids, using a widely adopted force field.
  • Identified specific residues that present challenges, indicating areas for future methodological improvements.