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Nonbonded Parameter Optimization Improving Simulation of Intrinsically Disordered Phosphoproteins.

Xinyao Zheng1, Ge Song1, Zhengxin Li1

  • 1State Key Laboratory of Microbial Metabolism, Department of Bioinformatics and Biostatistics, SJTU-Yale Joint Center for Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 200240 Shanghai, China.

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Summary

A new force field, phosRg, improves molecular dynamics (MD) simulations of phosphoproteins by accurately predicting their radius of gyration (Rg). This advancement enhances our understanding of crucial cellular processes regulated by phosphorylated proteins.

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Area of Science:

  • Biochemistry and Molecular Biology
  • Computational Chemistry
  • Structural Biology

Background:

  • Phosphorylated proteins are vital regulators in cellular signaling, expansion, and biochemical reactions.
  • Molecular dynamics (MD) simulations are essential for studying phosphoprotein dynamics.
  • Existing force fields often inaccurately represent phosphoprotein radii of gyration (Rg).

Purpose of the Study:

  • To develop and validate an improved molecular dynamics force field for phosphoproteins.
  • To enhance the accuracy of Rg and chemical shift predictions for phosphorylated proteins.
  • To investigate the conformational properties of phosphoproteins using MD simulations.

Main Methods:

  • Reoptimization of vdW radius for oxygen and phosphorus atom charges using a reweighting algorithm and thermodynamic integration.
  • Development of the phosRg force field.
  • Validation against experimental data for seven representative phosphoproteins.
  • Assessment of the TIP4P-D solvent model for phosphoprotein simulations.

Main Results:

  • The phosRg force field shows improved agreement with experimental Rg and chemical shift compared to phosaa10.
  • phosRg simulations yield more extended phosphoprotein conformations.
  • phosRg simulations exhibit reduced hydrophobic interactions and hydrogen bonds compared to phosaa10.
  • The TIP4P-D solvent model is compatible with phosRg for simulating phosphorylated proteins.

Conclusions:

  • The dual-objective optimization strategy effectively improves force field parameters for phosphoproteins.
  • phosRg offers a more accurate representation of phosphoprotein dynamics and conformations.
  • phosRg is recommended for future simulations of phosphorylated proteins and related systems.