440
M. G. Quesne and S. P. de Visser
stratospheric expansion of modeling techniques in the decades that followed, three
main broad strategies emerged, namely: quantum mechanical cluster approach, quantum mechanics/molecular mechanics (QM/MM), and the study of biomimetic model
systems. Since a subsequent chapter in this book will discuss biomimetic models,
here we will focus specifically on the QM/MM and QM cluster model techniques on
enzymes only.
QM cluster models focus on the active site region of the enzyme and study the
active site alone, i.e., the active site and its immediate surrounding but without the rest
of the protein and solvent. These cluster models can range in size from several dozen
to hundreds of atoms, but are treated with high-accuracy computational methods
such as wave function or DFT approaches. In general, all models typically include
the (metal) co-factor and its first coordination sphere as well as the substrate(s).
In addition, often close-lying hydrophylic residues that donate hydrogen bonds or
that are involved in salt-bridges or π -stacking interactions are included. Often these
cluster models contain geometric constraints that force residues (or part of them)
to stay in a specific orientation, which may lead to convergence problems of the
calculation. However, they do contain the coordination features of the central metal
ion as well as a part of or the complete substrate-binding pocket. Therefore, they
should mimic substrate approach and catalysis as good as a full enzyme model. One
of the first applications of the QM cluster technique to metalloenzymes was reported
in 1997 and focused on the enzyme methane monooxygenase [10].
QM/MM protocols split the metalloenzyme into both a small active core region,
which is to be treated using QM methods, and apply classical mechanical techniques
to everything else. Figure 1 shows an example of prolyl-4-hydroxylase [11, 12],
where the QM/MM structure is split into a QM region (in the amber circle) and an
MM region (in the green circle). A major difficulty with QM/MM involves obtaining
a good description of the border between the QM and MM region and the interaction
of the MM with the QM. Several reviews that give a very good overview of the early
applications of QM/MM techniques are available [13–16]. While the underlying
concept of the QM/MM method has been around since the 1970s [17], it was not
until the aforementioned improvement in the QM methodology that the results of
these studies became widely applied to metalloenzymes [18]. Therefore, the first full
QM/MM study into a transition metal-dependent enzyme was undertaken in 2000
on galactose oxidase [19].
There are several very detailed reviews into the various advantages and drawbacks
of QM/MM and cluster model techniques, with a focus on metalloenzymes [8, 9, 20,
21]. Therefore, in this chapter we intend to highlight some of the latest developments
in both techniques as well as to describe some of the most useful applications of each,
using several case studies.
M. G. Quesne and S. P. de Visser
stratospheric expansion of modeling techniques in the decades that followed, three
main broad strategies emerged, namely: quantum mechanical cluster approach, quantum mechanics/molecular mechanics (QM/MM), and the study of biomimetic model
systems. Since a subsequent chapter in this book will discuss biomimetic models,
here we will focus specifically on the QM/MM and QM cluster model techniques on
enzymes only.
QM cluster models focus on the active site region of the enzyme and study the
active site alone, i.e., the active site and its immediate surrounding but without the rest
of the protein and solvent. These cluster models can range in size from several dozen
to hundreds of atoms, but are treated with high-accuracy computational methods
such as wave function or DFT approaches. In general, all models typically include
the (metal) co-factor and its first coordination sphere as well as the substrate(s).
In addition, often close-lying hydrophylic residues that donate hydrogen bonds or
that are involved in salt-bridges or π -stacking interactions are included. Often these
cluster models contain geometric constraints that force residues (or part of them)
to stay in a specific orientation, which may lead to convergence problems of the
calculation. However, they do contain the coordination features of the central metal
ion as well as a part of or the complete substrate-binding pocket. Therefore, they
should mimic substrate approach and catalysis as good as a full enzyme model. One
of the first applications of the QM cluster technique to metalloenzymes was reported
in 1997 and focused on the enzyme methane monooxygenase [10].
QM/MM protocols split the metalloenzyme into both a small active core region,
which is to be treated using QM methods, and apply classical mechanical techniques
to everything else. Figure 1 shows an example of prolyl-4-hydroxylase [11, 12],
where the QM/MM structure is split into a QM region (in the amber circle) and an
MM region (in the green circle). A major difficulty with QM/MM involves obtaining
a good description of the border between the QM and MM region and the interaction
of the MM with the QM. Several reviews that give a very good overview of the early
applications of QM/MM techniques are available [13–16]. While the underlying
concept of the QM/MM method has been around since the 1970s [17], it was not
until the aforementioned improvement in the QM methodology that the results of
these studies became widely applied to metalloenzymes [18]. Therefore, the first full
QM/MM study into a transition metal-dependent enzyme was undertaken in 2000
on galactose oxidase [19].
There are several very detailed reviews into the various advantages and drawbacks
of QM/MM and cluster model techniques, with a focus on metalloenzymes [8, 9, 20,
21]. Therefore, in this chapter we intend to highlight some of the latest developments
in both techniques as well as to describe some of the most useful applications of each,
using several case studies.