Challenges in Modelling Metalloenzymes
Tomasz Borowski and Maciej Szaleniec
Abstract Modelling structure and/or reaction mechanism of a metalloenzyme
requires constructing reliable computational models. This process usually starts with
crystal structure and involves several steps, each potentially influencing the accuracy
of the constructed model. In this chapter, we provide an account, from our own works
and from the literature, on how one can check the quality of the crystal structure,
predict protonation states of titratable residues, including the metal ligands, perform molecular dynamics simulations, chose representative snapshots, and finally,
construct a QM cluster model that can be used for mechanistic studies.
1 Introduction
Enzymes catalyse a wide range of reactions making life possible in a variety of
environmental conditions. A great majority of enzymes are proteins built from Lα amino acids; however, the range of chemical tools used by nature to assemble
efficient catalysts goes significantly beyond residues of amino acids and includes
small organic molecules as well as metal ions or metal-containing organic complexes
in the role of cofactors or co-enzymes. The latter group of enzymes is referred to
as metalloenzymes, which may be one of the first groups of biological catalysts
that evolved on Earth, especially in the context of bioenergetic systems [1]. Now
metalloenzymes are involved in many biological processes such as nitrogen fixation,
respiration, hydrocarbon oxidation, generation of radicals for subsequent catalysis
and dismutation of superoxide or oxygenic photosynthesis [2].
The bioinformatic analysis of available protein databases estimates that 30–40%
of all proteins require metal ion(s) to carry out their biological functions [3, 4]. These
T. Borowski (B) · M. Szaleniec (B)
Jerzy Haber Institute of Catalysis and Surface Chemistry, Polish Academy of Sciences,
Niezapominajek 8, 30-239 Kraków, Poland
e-mail: ncborows@cyf-kr.edu.pl
M. Szaleniec
e-mail: ncszalen@cyf-kr.edu.pl
© Springer Nature Switzerland AG 2019
E. Broclawik et al. (eds.), Transition Metals in Coordination Environments,
Challenges and Advances in Computational Chemistry and Physics 29,
https://doi.org/10.1007/978-3-030-11714-6_17
503
Tomasz Borowski and Maciej Szaleniec
Abstract Modelling structure and/or reaction mechanism of a metalloenzyme
requires constructing reliable computational models. This process usually starts with
crystal structure and involves several steps, each potentially influencing the accuracy
of the constructed model. In this chapter, we provide an account, from our own works
and from the literature, on how one can check the quality of the crystal structure,
predict protonation states of titratable residues, including the metal ligands, perform molecular dynamics simulations, chose representative snapshots, and finally,
construct a QM cluster model that can be used for mechanistic studies.
1 Introduction
Enzymes catalyse a wide range of reactions making life possible in a variety of
environmental conditions. A great majority of enzymes are proteins built from Lα amino acids; however, the range of chemical tools used by nature to assemble
efficient catalysts goes significantly beyond residues of amino acids and includes
small organic molecules as well as metal ions or metal-containing organic complexes
in the role of cofactors or co-enzymes. The latter group of enzymes is referred to
as metalloenzymes, which may be one of the first groups of biological catalysts
that evolved on Earth, especially in the context of bioenergetic systems [1]. Now
metalloenzymes are involved in many biological processes such as nitrogen fixation,
respiration, hydrocarbon oxidation, generation of radicals for subsequent catalysis
and dismutation of superoxide or oxygenic photosynthesis [2].
The bioinformatic analysis of available protein databases estimates that 30–40%
of all proteins require metal ion(s) to carry out their biological functions [3, 4]. These
T. Borowski (B) · M. Szaleniec (B)
Jerzy Haber Institute of Catalysis and Surface Chemistry, Polish Academy of Sciences,
Niezapominajek 8, 30-239 Kraków, Poland
e-mail: ncborows@cyf-kr.edu.pl
M. Szaleniec
e-mail: ncszalen@cyf-kr.edu.pl
© Springer Nature Switzerland AG 2019
E. Broclawik et al. (eds.), Transition Metals in Coordination Environments,
Challenges and Advances in Computational Chemistry and Physics 29,
https://doi.org/10.1007/978-3-030-11714-6_17
503