4.2 Article

Comparison of different approaches to derive classical bonded force-field parameters for a transition metal cofactor: a case study for non-heme iron site of ectoine synthase

Journal

THEORETICAL CHEMISTRY ACCOUNTS
Volume 140, Issue 8, Pages -

Publisher

SPRINGER
DOI: 10.1007/s00214-021-02796-z

Keywords

Parametrization; Force field; Transition metals; Iron; Ectoine; Ectoine synthase

Funding

  1. ICSC PAS
  2. PL-Grid Infrastructure

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Computational investigations were conducted to derive amber force field parameters for the Fe(II) cofactor of ectoine synthase, with the spin state probed by DFT and post-HF methods. Results showed that Hessian-based methods accurately represented the geometry around the metal ion, while energy-based methods reproduced energy-structure relationships effectively. Preliminary tests suggested that combining geometrical criteria with energy-based methods may yield parameters with acceptable performance for both energy and geometry.
Computational investigations into the structure and function of metalloenzymes with transition metal cofactors require proper preparation of the model, which requires obtaining reliable force field parameters for the cofactor. Here, we present a test case where several methods were used to derive amber force field parameters for a bonded model of the Fe(II) cofactor of ectoine synthase. Moreover, the spin of the ground state of the cofactor was probed by DFT and post-HF methods, which consistently indicated the quintet state is lowest in energy and well separated from triplet and singlet. The performance of the obtained force field parameter sets, derived for the quintet spin state, was scrutinized and compared taking into account metrics focused on geometric features of the models as well as their energetics. The main conclusion of this study is that Hessian-based methods yield parameters which represent the geometry around the metal ion, but poorly reproduce energy variance with geometrical changes. On the other hand, the energy-based method yields parameters accurately reproducing energy-structure relationships, but with bad performance in geometry optimization. Preliminary tests show that admixing geometrical criteria to energy-based methods may allow to derive parameters with acceptable performance for both energy and geometry.

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