Thermodynamic Integration Networks and Their Application to Charge Transfer Reactions within the AauDyPI Fungal Peroxidase

Abstract

We present a computer simulation study of the thermodynamics and kinetics of charge transfer reactions within the fungal peroxidase AauDyPI from Auricularia auriculae-judae. Driving forces and reorganization energies are obtained from a thermodynamic integration scheme based upon molecular dynamics simulations. To enhance the numerical accuracy, the free energies are analyzed within a least-squares scheme of a closely knit thermodynamic network. We identify Tyr147, Tyr229, and Trp105 as oxidative agents, and find Trp377 to be a long-lived reaction intermediate. The results are compared to recent experimental findings.

Thermodynamic integration network approach to ion transport through protein channels: Perspectives and limits

“…The Figure shows representative examples of ∂V (Λ)/∂Λ‐plots obtained from the TI‐calculations: the transport reaction of the cesium ion from the center to the mouth of the DH dimer, the alchemical transformation reaction from Cs + to K + at the center of the H2H dimer and the solvation of sodium ion (the direction of the simulated reaction is from water to vacuum). In contrast to our investigations of electron transfer, the data obtained from reactions involving ions cannot be described by a linear function. The shape of all ∂V (Λ)/∂Λ‐ plots is roughly hyperbolic.…”

“…Recently, we have presented that the thermodynamic network analysis based on the least squares problem has noticeably improved the statistical accuracy of the simulated free energies gained with TI methods . Although, the focus of our recent studies was lying on electron transfer reactions.…”

“…Our main perspective is a methodological one, we are interested in the question to which degree the thermodynamic integration approach can be applied to systems in which the thermodynamic states correspond to transient centers of alkali metal cation localization, that is, particles that show a high degree of mobility. We are motivated by a recent extension of the TI methodology in the context of electron transfer, the construction of thermodynamic integration networks . They enable a least‐squares calculation within a net of free energy computations, and the estimate of a corresponding error.…”

Computational Modeling Methods for Understanding the Interaction of Lignin and Its Derivatives with Oxidoreductases as Biocatalysts

“…This fact evidenced the activation and deactivation of different LRET pathways in A. aricula-judae DyP [86]. Other more recent studies [87], have also attempted to characterize the oxidative sites present in AauDyP by means of molecular dynamics simulations, where energy differences in the charge transfer processes among the oxidative centers have been identified. Trp377 is recognized as the most kinetically favorable amino acid for hosting the electron hole, confirming the previously mentioned findings, otherwise the residue Tyr229, or the cluster formed by Trp105-Tyr147-Tyr337, are also thermodynamically favored.…”

Monte Carlo simulation and thermodynamic integration applied to protein charge transfer

“…The simulation data can be made the subject of a least squares analysis, leading to improved free energies, an error estimate, and the possible identification of outliers. Here, we follow the work of Bauß et al [24] We consider the free energy, ΔG i , of each donor or acceptor as a variable of the equation corresponding to the free energy difference of the reaction pathway involving i. For example, a free energy difference ΔΔG ij between two different hemes i and j can be expressed as in Equation (5), this should be equal to the free energy difference obtained from the simulation between two states, ΔΔG ij, sim .…”