122
periodic boundary conditions were implemented using the PME (particle mesh
Ewald) algorithm [140] and the cut-off values were 1.4 and 0.9 nm for the van der
Waals and electrostatic interactions, respectively. MD was carried out with Yasara
Dynamics 10 software [141]. The time step of 2 fs was used. The Amber03 force
field [142] was selected; the simulation box allowed at least 10 Å around all of
the atoms in 6,10,2′,6′-tetraacetyl-O-catalpol, and was filled with the TIP3 water
model. Periodic boundary conditions were used as implemented in the PME algorithm. Na
+
and Cl
−
ions were added in order to properly simulate the ion strength in
physiological solution. Two simulations of 300 productive nanoseconds each were
performed starting from the best energy conformation identified during the SA procedure and minimized with the Amber03 force field, and the same conformation
with the torsion angle α rotated 180° and minimized with the Amber03 force field.
Using docking simulations, the most probable binding mode was found, and the
stabilities of the docked solutions were tested in a series of molecular dynamics
experiments. The docking was performed with Autodock 4.0 software [118] using
two different modes—blind docking search and binding site restricted search. The
coordinates of the target molecule (including the Klentaq fragment and a short DNA
portion) were taken from the Protein Data Bank [126] deposited under the accession
code 2KTQ [143].
The ligand position with the lowest energy (the best energy solution of
− 4.45 kcal/mol) is located at the active site of the enzyme [134]. This result is in
line with previous experimental observations regarding the inhibitory mechanism of
catalpol [144], and supports the hypothesis of a competitive inhibitory mechanism
for 6,10,2′,6′-tetraacetyl-O-catalpol. Spatial microenvironment of catalpol in binding site consists of amino acids Asp610, Tyr611, Ser612, Gln613, Ile614, Glu615,
Leu616, Lys663, Phe667, Leu670, Tyr671, Asp785 and Glu786. All of them except
Leu616 participate in the incoming dNTP binding as well. The time stability of
calculated ‘Taq polymerase–catalpol’ complex was confirmed by a set of molecular
dynamics simulations [134]. Trajectory analysis indicated four time-stable hydrogen bonds between 6,10,2′,6′-tetraacetyl-O-catalpol and the enzyme that were present for > 20 % of the simulation time. Spatial structure of reconstructed complex can
be used as a starting point for directed optimization of DNA pol inhibitors based on
catalpol derivates.
Computational analysis is also applied to the investigation of structural mechanisms of actions of viral DNA polymerase inhibitors. So, Li et al. [145] have used
in silico approaches, including homology modeling, docking, MD simulation and
MM/PBSA free energy analysis, to study structural insights underlying the influence of DNA polymerase from different genotypes of hepatitis B virus (HBV) on
the binding affinity of acyclic nucleotide adefovir (ADV). An important feature of
HBV pol is its ability to act as a matrix for the complimentary DNA synthesis of
both DNA and RNA molecules. Spatial structure of HBV pols of B and C genotypes was reconstructed by the homology modeling using the automated modeling
module, MODELLER [146] in the Discovery Studio (DS) software 3.0 (Accelrys,
San Diego, CA, USA). After the energy minimization, the geometric quality of the
modeled structures was evaluated by PROCHECK [147].
A. Yu. Nyporko
periodic boundary conditions were implemented using the PME (particle mesh
Ewald) algorithm [140] and the cut-off values were 1.4 and 0.9 nm for the van der
Waals and electrostatic interactions, respectively. MD was carried out with Yasara
Dynamics 10 software [141]. The time step of 2 fs was used. The Amber03 force
field [142] was selected; the simulation box allowed at least 10 Å around all of
the atoms in 6,10,2′,6′-tetraacetyl-O-catalpol, and was filled with the TIP3 water
model. Periodic boundary conditions were used as implemented in the PME algorithm. Na
+
and Cl
−
ions were added in order to properly simulate the ion strength in
physiological solution. Two simulations of 300 productive nanoseconds each were
performed starting from the best energy conformation identified during the SA procedure and minimized with the Amber03 force field, and the same conformation
with the torsion angle α rotated 180° and minimized with the Amber03 force field.
Using docking simulations, the most probable binding mode was found, and the
stabilities of the docked solutions were tested in a series of molecular dynamics
experiments. The docking was performed with Autodock 4.0 software [118] using
two different modes—blind docking search and binding site restricted search. The
coordinates of the target molecule (including the Klentaq fragment and a short DNA
portion) were taken from the Protein Data Bank [126] deposited under the accession
code 2KTQ [143].
The ligand position with the lowest energy (the best energy solution of
− 4.45 kcal/mol) is located at the active site of the enzyme [134]. This result is in
line with previous experimental observations regarding the inhibitory mechanism of
catalpol [144], and supports the hypothesis of a competitive inhibitory mechanism
for 6,10,2′,6′-tetraacetyl-O-catalpol. Spatial microenvironment of catalpol in binding site consists of amino acids Asp610, Tyr611, Ser612, Gln613, Ile614, Glu615,
Leu616, Lys663, Phe667, Leu670, Tyr671, Asp785 and Glu786. All of them except
Leu616 participate in the incoming dNTP binding as well. The time stability of
calculated ‘Taq polymerase–catalpol’ complex was confirmed by a set of molecular
dynamics simulations [134]. Trajectory analysis indicated four time-stable hydrogen bonds between 6,10,2′,6′-tetraacetyl-O-catalpol and the enzyme that were present for > 20 % of the simulation time. Spatial structure of reconstructed complex can
be used as a starting point for directed optimization of DNA pol inhibitors based on
catalpol derivates.
Computational analysis is also applied to the investigation of structural mechanisms of actions of viral DNA polymerase inhibitors. So, Li et al. [145] have used
in silico approaches, including homology modeling, docking, MD simulation and
MM/PBSA free energy analysis, to study structural insights underlying the influence of DNA polymerase from different genotypes of hepatitis B virus (HBV) on
the binding affinity of acyclic nucleotide adefovir (ADV). An important feature of
HBV pol is its ability to act as a matrix for the complimentary DNA synthesis of
both DNA and RNA molecules. Spatial structure of HBV pols of B and C genotypes was reconstructed by the homology modeling using the automated modeling
module, MODELLER [146] in the Discovery Studio (DS) software 3.0 (Accelrys,
San Diego, CA, USA). After the energy minimization, the geometric quality of the
modeled structures was evaluated by PROCHECK [147].
A. Yu. Nyporko