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Comparing Nonbonded Metal Ion Models in the Divalent Cation Binding Protein PsaA.

Hugo I MacDermott-OpeskinChristopher A McDevittMegan L O'Mara
Published in: Journal of chemical theory and computation (2020)
Divalent metal cations are essential for many biological processes; however, accurately modeling divalent metal ions has proved a significant challenge for molecular dynamics force fields. Here we show that the choice of ion model influences the observed dynamics in PsaA, a metal binding protein from Streptococcus pneumoniae. We conduct extensive unbiased simulations and free energy calculations of PsaA bound to its cognate ligand Mn2+ and inhibitory ligand Zn2+ using three nonbonded ion models: a 12-6 model, a 12-6-4 model, and a multisite model. The observed coordination geometries and metal binding dynamics are sensitive to the choice of ion model, with the most dramatic differences observed in free energy calculations of ion release. We show that the conformational ensemble of Mn-bound PsaA is more similar to the crystallographic metal bound open state. This work extends the current model of PsaA metal binding and provides a framework for the rationalization of experimentally determined metal binding behavior. Our findings support the use of the 12-6-4 ion model for further simulations of divalent cation binding proteins.
Keyphrases
  • molecular dynamics
  • binding protein
  • density functional theory
  • molecular dynamics simulations
  • ionic liquid
  • risk assessment
  • minimally invasive
  • machine learning
  • deep learning
  • quantum dots