A Comparison of Bonded and Nonbonded Zinc(II) Force Fields with NMR Data

Abstract

Classical molecular dynamics (MD) simulations are widely used to inspect the behavior of zinc(II)-proteins at the atomic level, hence the need to properly model the zinc(II) ion and the interaction with its ligands. Different approaches have been developed to represent zinc(II) sites, with the bonded and nonbonded models being the most used. In the present work, we tested the well-known zinc AMBER force field (ZAFF) and a recently developed nonbonded force field (NBFF) to assess how accurately they reproduce the dynamic behavior of zinc(II)-proteins. For this, we selected as benchmark six zinc-fingers. This superfamily is extremely heterogenous in terms of architecture, binding mode, function, and reactivity. From repeated MD simulations, we computed the order parameter (S2) of all backbone N-H bond vectors in each system. These data were superimposed to heteronuclear Overhauser effect measurements taken by NMR spectroscopy. This provides a quantitative estimate of the accuracy of the FFs in reproducing protein dynamics, leveraging the information about the protein backbone mobility contained in the NMR data. The correlation between the MD-computed S2 and the experimental data indicated that both tested FFs reproduce well the dynamic behavior of zinc(II)-proteins, with comparable accuracy. Thus, along with ZAFF, NBFF represents a useful tool to simulate metalloproteins with the advantage of being extensible to diverse systems such as those bearing dinuclear metal sites.

A database overview of metal-coordination distances in metalloproteins

“…Such distances can be used as a reference for the determination, refinement and/or validation of novel 3D metalloprotein structures. In addition, the identified metal-specific preferences for different configurations of Asp versus Glu binding can be taken into account not only during the structure-determination/validation process but also in the development of improved force fields for molecular-dynamics simulations (Macchiagodena et al, 2020;Bazayeva et al, 2023;Melse et al, 2023). We also investigated whether our results could be affected by the evolution of structure-determination methods over time by partitioning the whole data set into tenyear blocks based on the date of structure deposition.…”