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PreprintCC BYChemRxiv

Accurate modeling of ion-protein binding in solution: molecular mechanics force field innovation and validation on Mg2+

  • Giorgio Schillaci1
  • Julian Mélendez Delgado1
  • Matthew Saunders1
  • Irene Arias Gutierrez1
  • Péter R. Nagy2,3,4
  • Sameer Varma1,5
5 affiliations
  1. 1Department of Molecular Biosciences, University of South Florida, 4202 E. Fowler Ave., Tampa, USA, FL-33620
  2. 2Department of Physical Chemistry and Materials Science, Faculty of Chemical Technology and Biotechnology, Budapest University of Technology and Economics, Műegyetem rkp. 3., Budapest, Hungary, H-1111
  3. 3HUN-REN-BME Quantum Chemistry Research Group, Műegyetem rkp. 3., Budapest, Hungary, H-1111
  4. 4MTA-BME Lendület Quantum Chemistry Research Group, Műegyetem rkp. 3., Budapest, Hungary, H-1111
  5. 5Department of physics, University of South Florida, 4202 E. Fowler Ave., Tampa, Florida, United States, 33620
Open at sourceDOICite

Abstract

Multivalent ions bind to proteins to control many biological processes. Molecular simulations can effectively supplement experiments to resolve underlying mechanisms, but suffer from reliability and feasibility issues in describing ion-protein binding in the condensed phase. Here we present a molecular mechanics based generalizable solution to this long-standing challenge. Using the divalent Mg 2+ as a model, we demonstrate that our approach yields unprecedented accuracy in describing its binding to proteins in solution – compared to high level quantum mechanics, the mean error in local interaction energies is 0.5%, and the binding modes and binding free energies match experiment. Our study also shows that key to achieving this accuracy requires a delicate balance between the large repulsive and attractive forces at short distances near ions for which explicit modeling of polarization is essential. Overall, our work lays foundation for future development of molecular simulation methods for ions and opens the way to quantitatively study Mg-dependent mechanisms in hundreds of enzymes and proteins.

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Cite

BibTeXRIS
BibTeX
@misc{schillaci2026accurate,
  title = {{Accurate modeling of ion-protein binding in solution: molecular mechanics force field innovation and validation on Mg2+}},
  author = {Giorgio Schillaci and Julian Mélendez Delgado and Matthew Saunders and Irene Arias Gutierrez and Péter R. Nagy and Sameer Varma},
  howpublished = {ChemRxiv},
  year = {2026},
  month = sep,
  doi = {10.26434/chemrxiv.15009072/v1},
  url = {https://chemrxiv.org/doi/full/10.26434/chemrxiv.15009072/v1},
  note = {CC BY},
}
RIS
TY  - UNPB
TI  - Accurate modeling of ion-protein binding in solution: molecular mechanics force field innovation and validation on Mg2+
AU  - Giorgio Schillaci
AU  - Julian Mélendez Delgado
AU  - Matthew Saunders
AU  - Irene Arias Gutierrez
AU  - Péter R. Nagy
AU  - Sameer Varma
PY  - 2026
DA  - 2026/09/18
PB  - ChemRxiv
DO  - 10.26434/chemrxiv.15009072/v1
UR  - https://chemrxiv.org/doi/full/10.26434/chemrxiv.15009072/v1
AB  - Multivalent ions bind to proteins to control many biological processes. Molecular simulations can effectively supplement experiments to resolve underlying mechanisms, but suffer from reliability and feasibility issues in describing ion-protein binding in the condensed phase. Here we present a molecular mechanics based generalizable solution to this long-standing challenge. Using the divalent Mg 2+ as a model, we demonstrate that our approach yields unprecedented accuracy in describing its binding to proteins in solution – compared to high level quantum mechanics, the mean error in local interaction energies is 0.5%, and the binding modes and binding free energies match experiment. Our study also shows that key to achieving this accuracy requires a delicate balance between the large repulsive and attractive forces at short distances near ions for which explicit modeling of polarization is essential. Overall, our work lays foundation for future development of molecular simulation methods for ions and opens the way to quantitatively study Mg-dependent mechanisms in hundreds of enzymes and proteins.
ER  -