Article ; Online: Identification of Novel Tau-Tubulin Kinase 2 Inhibitors Using Computational Approaches.
ACS omega
2023 Volume 8, Issue 14, Page(s) 13026–13037
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 ... ...
| 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. |
|---|---|
| Language | English |
| Publishing date | 2023-03-28 |
| Publishing country | United States |
| Document type | Journal Article |
| ISSN | 2470-1343 |
| ISSN (online) | 2470-1343 |
| DOI | 10.1021/acsomega.3c00225 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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