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Energy Barriers of Proton Transfer Reactions Between Amino Acid Side Chain Analogs and Water from ab initio Calculations

MPG-Autoren
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Herzog,  Elena
Department of Molecular Membrane Biology, Max Planck Institute of Biophysics, Max Planck Society;

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Frigato,  Tomaso
Max Planck Research Group of Theoretical Biophysics, Max Planck Institute of Biophysics, Max Planck Society;

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Helms,  Volkhard
Max Planck Research Group of Theoretical Biophysics, Max Planck Institute of Biophysics, Max Planck Society;

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Lancaster,  C. Roy D.
Department of Molecular Membrane Biology, Max Planck Institute of Biophysics, Max Planck Society;

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Zitation

Herzog, E., Frigato, T., Helms, V., & Lancaster, C. R. D. (2006). Energy Barriers of Proton Transfer Reactions Between Amino Acid Side Chain Analogs and Water from ab initio Calculations. Journal of Computational Chemistry, 27(13), 1534-1547. doi:10.1002/jcc.20442.


Zitierlink: https://hdl.handle.net/11858/00-001M-0000-0024-D99D-8
Zusammenfassung
Proton transfer reactions were studied in all titratable pairs of amino acid side chains where, under physiologically reasonable conditions, one amino acid may function as a donor and the other one as an acceptor. Energy barriers for shifting the proton from donor to acceptor atom were calculated by electronic structure methods at the MP2/6‐31++G(d,p) level, and the well‐known double‐well potentials were characterized. The energy difference between both minima can be expressed by a parabola using as argument the donor–acceptor distance R(DA). In this work, the fit parameters of the quadratic expression are determined for each donor–acceptor pair. Moreover, it was found previously that the energy barriers of the reactions can be expressed by an analytical expression depending on the distance between donor and acceptor and the energy difference between donor and acceptor bound states. The validity of this approach is supported by the extensive new data set. This new parameterization of proton transfer barriers between titratable amino acid side chains allows us to very efficiently estimate proton transfer probabilities in molecular modelling studies or during classical molecular dynamics simulation of biomolecular systems.