Identification of Novel Tau-Tubulin Kinase 2 Inhibitors Using Computational Approaches

Abstract

Tau tubulin kinase 2 (TTBK2) associated with multiple diseases is one of the kinases which phosphorylates tau and tubulin. Numerous efforts have been made to understand the role of TTBK2 in protein folding mechanisms and misfolding behavior. The misfolded protein intermediates form polymers with unwanted aggregation properties that initiate several diseases, including Alzheimer's. The availability of TTBK2 inhibitors can enhance the understanding of the molecular mechanism of action of the kinase and assist in developing novel therapeutics. In the quest for TTBK2 inhibitors, this study focuses on screening two chemical libraries (ChEMBL and ZINC-FDA). The molecular docking, RO5/absorption, distribution, metabolism, and excretion/toxicity, density functional theory, molecular dynamics (MD) simulations, and molecular mechanics with generalized Born and surface area solvation techniques enabled shortlisting of the four most active compounds, namely, ChEMBL1236395, ChEMBL2104398, ChEMBL3427435, and ZINC000000509440. Moreover, 500 ns MD simulation was performed for each complex, which provided valuable insights into the structural changes in the complexes. The relative fluctuation, solvent accessible surface area, atomic gyration, compactness covariance, and free energy landscapes revealed that the compounds could stabilize the TTBK2 protein. Overall, this study would be valuable for the researchers targeting the development of novel TTBK2 inhibitors.

Figure 1

Cellular processes and diseases associated with TTBK2 (A). Computational study workflow (B).

Figure 2

Representation of the binding poses, H-bonds, and amino acid residues toward the active pocket of TTBK2. (A,B) Ligand interaction site of cocrystal–ligand representing H-bond residues and the 2D plot displaying vdW residues around the 4 Å region, (C,D) ChEMBL1236395-TTBK2-docked complex and representation of the 2D plot, and (E,F) ChEMBL2104398 and 2D plot.

Figure 3

MD simulation-allied parameters of the four drug complexes and reference molecule (ADP)-docked complex. (A) RMS deviation graph plotted against the cocrystal ligand, ZINC000000509440, ChEMBL1236395, ChEMBL2104398, and ChEMBL3427435. (B) The dynamic energy fluctuation graph plotted between eigenvector 1 and eigenvector 2 shows the conformational space of Cα-atoms for all five docked complexes. (C) SASA analysis plot of five TTBK2-docked complexes. (D) Comparative R_g plot of five docked complexes during 500 ns MD simulations.

Figure 4

Relative residue fluctuation plot of TTBK2 (A) ZINC000000509440, (B) CHEMBL1236395, (C) CHEMBL2104398, and (D) CHEMBL3427435 complexes during MD simulations.

Figure 5

H-bond plots of five docked complexes analyzed during the entire simulation time of 500 ns. (A) Number of H-bonds between TTBK2 and the co-crystal-ligand, (B) H-bond between TTBK2 and the ZINC000000509440-docked complex, (C) TTBK2-ChEMBL1236395-docked complex, (D) TTBK2-ChEMBL2104398-docked complex, and (E) TTBK2-ChEMBL3427435-docked complex.

Figure 6

FEL and density distribution analysis. (A) Free energy wells revealing the folding behavior, the direction of motions, and magnitude of dynamics of the docked complexes and (B) density distribution of docked complexes obtained in the MD trajectories during simulation timeframes: (i) co-crystal ligand, (ii) ZINC000000509440, (iii) ChEMBL1236395, (iv) ChEMBL2104398, and (v) ChEMBL3427435.

Figure 7

(A) HOMO/LUMO orbitals and the energy potential map of ChEMBL1236395. (B) HOMO/LUMO orbitals and the energy potential map of ChEMBL2104398. (C) HOMO/LUMO orbitals and the energy potential map of ChEMBL3427435. The color of the potential is shown between −200 (red) and +289 kJ/mol (blue). The ESP surface area of the mesh model. The DFT calculations were performed using the Spartan’20 package with B3LYP/6-31G* in the gas phase.