Archives

  • 2018-07
  • 2019-04
  • 2019-05
  • 2019-06
  • 2019-07
  • 2019-08
  • 2019-09
  • 2019-10
  • 2019-11
  • 2019-12
  • 2020-01
  • 2020-02
  • 2020-03
  • 2020-04
  • 2020-05
  • 2020-06
  • 2020-07
  • 2020-08
  • 2020-09
  • 2020-10
  • 2020-11
  • 2020-12
  • 2021-01
  • 2021-02
  • 2021-03
  • 2021-04
  • 2021-05
  • 2021-06
  • 2021-07
  • 2021-08
  • 2021-09
  • 2021-10
  • 2021-11
  • 2021-12
  • 2022-01
  • 2022-02
  • 2022-03
  • 2022-04
  • 2022-05
  • 2022-06
  • 2022-07
  • 2022-08
  • 2022-09
  • 2022-10
  • 2022-11
  • 2022-12
  • 2023-01
  • 2023-02
  • 2023-03
  • 2023-04
  • 2023-05
  • 2023-06
  • 2023-07
  • 2023-08
  • 2023-09
  • 2023-10
  • 2023-11
  • 2023-12
  • 2024-01
  • 2024-02
  • 2024-03
  • At the second step blind docking simulation of independent r

    2022-05-16

    At the second step, blind docking simulation of 150 independent runs was performed with smaller grid box. Structures of open (1v4t.pdb), semi-closed (4dch.pdb) and two structures of closed configuration of GK (pdb codes are 1v4s and 3vev) were used for simulation (for detailed explanations on can see section 3.2). Grid maps were calculated with 90×90×90 points using a grid spacing of 0.375Å centered at the allosteric site. Other parameters of simulation were similar to step one. The convergence of 150 runs was checked, and only the result with the best AutoDock score was retained for further analysis. At the third step, a constraint was used for docking simulation. Analysis of the crystallographic structures of complexes GK with activators shows that Arg63 residue is a key residue in GK-GKA interactions and it forms hydrogen bonds with all known small allosteric activators (Kamata et al., 2004, Liu et al., 2012). At the third step, hydrogen bond between the oxygen RNase Inhibitor of Arg63 residue and the hydrogen atom of NH groups of GKAs was set as constraint and an additional grid map (Z) centered on the oxygen atom of Arg63 residue was constructed using the Gaussian function. This function with the half-width of 5Å and with the energy barrier with height equal to 30kcal/mol was constructed with zero energy at the site of attachment and steep energetic penalties at surrounding areas. Hydrogen atoms of NH groups of GKAs were labeled as Z atom and control/governing docking was performed. At the fourth step, the structure of the complex with the lowest binding energy obtained during the third step was optimized using Local Search Algorithm. For the local search, the pseudo-Solis and Wets algorithm was applied with a maximum of 300 iterations (Solis and Wets, 1981). For local search, 50 independent docking runs were carried out. The highest ranked conformation from the fourth step was selected as the best docked conformation. AutoDock Vina is a more recent release of AutoDock program, which uses own scoring function in combination with an Iterated Local Search Global Optimizer (Baxter, 1981). The Vina scoring function is a weighted sum of distance-dependent atom pair interactions, which are defined relative to the surface distance (Trott and Olson, 2010): Here is a function of the interatomic distance () and the van der Waals radii of the atoms in the pair ( and ). Every pair of atoms (i and j) interacts through a steric interaction given by the sum of three terms:where Depending on the atom type, hydrophobic and H-bonding interactions are taking in account. Hydrophobic effect is described as: H-bond term is: For Vina program, default values of parameters were used (Trott and Olson, 2010). Optimal binding sites were searched in a box of 22×22×22Å3. The box had 1.0Å grid spacing and centered at the allosteric site of the protein. Docking of glucose to the active site of glucokinase was performed for three conformations of GK: closed, apo and semi-open conformations using AutoDock and Vina programs. Docking of glucose molecule was performed in one step. For modeling by AutoDock program, docking grid map with 90×90×90 points and grid point spacing 0.375Å was centered on the active site of glucokinase. Blind docking simulation of 150 independent runs was performed; other AutoDock parameters were set to their default values. For Vina program default values of parameters were used (Trott and Olson, 2010). Optimal binding sites were searched in a box of 22×22×22Å3 centered on the active site of glucokinase. The predicted complexes were ranked according to the binding energy. Ligand docking poses were compared to the crystallographic poses using the RMSD. The figures were prepared using the VMD program (Humphrey et al., 1996).
    Results and discussions
    Acknowledgments We thank Moscow State University for providing the access to SKIF-MGU “Lomonosov” supercomputer. This work was supported by grant from the Russian Foundation for Basic Research and the Government of Tatarstan Republic (No. 15-44-02309).