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7 Density Functional Theory Calculations of Enzyme–Inhibitor …
an unique selectivity for the target enzyme and exert their biological effect at low
doses. Nowadays, enzyme inhibition is one of the key approaches to the drug design
in the research and industry [5]. As reported in the recent review devoted to drug
predictions methods [6], the drugs using the enzymes as targets amount to 24 %
from the total number of small-molecule medicaments. Currently the computational
techniques and software have become suitable for the theoretical analysis of the enzyme–substrate interactions [2]. The molecular docking [7], based on the molecular
mechanics/molecular dynamics techniques, and quantitative structure–activity relationship (QSAR) methods [8], are widely used for this purpose.
An efficient enzyme–inhibitor interaction is usually characterized by a negative
free binding energy, ∆G. This is equivalent to the reaction free energy, widely used
in the quantum chemical description of chemical processes. Therefore, a maximization of the enzyme–substrate negative interaction energy under control of classical quantum-mechanical methods, ab initio or density functional theory (DFT),
would probably be the most direct way to discover new efficient drug substances
and to modify the existing drugs. The detailed outlook of using the DFT for calculations of ligand–protein complexes is given in the recent review of Utkov et al. [9].
However, despite the rapid development observed in computational techniques and
routines, the quantum-mechanical methods ( ab initio and DFT approaches) are still
too slow and size-restricted or too inexact (molecular mechanics or semi-empirical
methods) to provide a quantitative description for kinetics and thermodynamics of
enzyme inhibition processes. One way to overcome the size problem in DFT calculations is to consider the interactions with every amino acid in the polypeptide
chain separately and then to sum all the contributions. This approach is realized, for
example, in the molecular fractionation with conjugate caps (MFCC) approach [10,
11]. In the other approaches, such as QM/MM calculations [12–14] or ONIOM routine implemented in the Gaussian sets of programs [12], the DFT calculations are
used only for the small fragments of the active site and inhibitor structure, whereas
the other part is described semi-empirically or by a classic force field [15]. The
enzyme–inhibitor interactions investigated by using QM/MM methods are analyzed
in the several recent reviews [16–18]. DFT calculations of the enzyme inhibition
processes can be also performed for the truncated (up to several hundreds atoms)
enzyme binding sites [19]. Recently some important steps have been undertaken for
the rapid development of DFT-based drug chemistry. First of all, several efficient
linear-scaling techniques [20] such as the Resolution of the Identity ( RI) [21–27]
have been proposed as an efficient solution of the size problem by quantum chemistry calculations and implemented into several popular quantum mechanic program
sets (see, for example Ref. [28, 29]). Other well known indirect applications of the
DFT methods in medicinal chemistry and drug design should be mentioned here: (a)
evaluation of structure, conformation and properties, which can directly correlate
with the inhibition activity of a molecules-candidate, such as molecular orbitals
(MOs) [30, 31], electron density distribution, dipole moments [32], electrostatic
potential surfaces (EPS) [33–36] etc.; (b) calculations of properties of structures,
subsequently used as descriptors for QSAR analysis [8, 31–39].
7 Density Functional Theory Calculations of Enzyme–Inhibitor …
an unique selectivity for the target enzyme and exert their biological effect at low
doses. Nowadays, enzyme inhibition is one of the key approaches to the drug design
in the research and industry [5]. As reported in the recent review devoted to drug
predictions methods [6], the drugs using the enzymes as targets amount to 24 %
from the total number of small-molecule medicaments. Currently the computational
techniques and software have become suitable for the theoretical analysis of the enzyme–substrate interactions [2]. The molecular docking [7], based on the molecular
mechanics/molecular dynamics techniques, and quantitative structure–activity relationship (QSAR) methods [8], are widely used for this purpose.
An efficient enzyme–inhibitor interaction is usually characterized by a negative
free binding energy, ∆G. This is equivalent to the reaction free energy, widely used
in the quantum chemical description of chemical processes. Therefore, a maximization of the enzyme–substrate negative interaction energy under control of classical quantum-mechanical methods, ab initio or density functional theory (DFT),
would probably be the most direct way to discover new efficient drug substances
and to modify the existing drugs. The detailed outlook of using the DFT for calculations of ligand–protein complexes is given in the recent review of Utkov et al. [9].
However, despite the rapid development observed in computational techniques and
routines, the quantum-mechanical methods ( ab initio and DFT approaches) are still
too slow and size-restricted or too inexact (molecular mechanics or semi-empirical
methods) to provide a quantitative description for kinetics and thermodynamics of
enzyme inhibition processes. One way to overcome the size problem in DFT calculations is to consider the interactions with every amino acid in the polypeptide
chain separately and then to sum all the contributions. This approach is realized, for
example, in the molecular fractionation with conjugate caps (MFCC) approach [10,
11]. In the other approaches, such as QM/MM calculations [12–14] or ONIOM routine implemented in the Gaussian sets of programs [12], the DFT calculations are
used only for the small fragments of the active site and inhibitor structure, whereas
the other part is described semi-empirically or by a classic force field [15]. The
enzyme–inhibitor interactions investigated by using QM/MM methods are analyzed
in the several recent reviews [16–18]. DFT calculations of the enzyme inhibition
processes can be also performed for the truncated (up to several hundreds atoms)
enzyme binding sites [19]. Recently some important steps have been undertaken for
the rapid development of DFT-based drug chemistry. First of all, several efficient
linear-scaling techniques [20] such as the Resolution of the Identity ( RI) [21–27]
have been proposed as an efficient solution of the size problem by quantum chemistry calculations and implemented into several popular quantum mechanic program
sets (see, for example Ref. [28, 29]). Other well known indirect applications of the
DFT methods in medicinal chemistry and drug design should be mentioned here: (a)
evaluation of structure, conformation and properties, which can directly correlate
with the inhibition activity of a molecules-candidate, such as molecular orbitals
(MOs) [30, 31], electron density distribution, dipole moments [32], electrostatic
potential surfaces (EPS) [33–36] etc.; (b) calculations of properties of structures,
subsequently used as descriptors for QSAR analysis [8, 31–39].