Your browser doesn't support javascript.
loading
Computational identification of potential tau tubulin kinase 1 (TTBK1) inhibitors: a structural analog approach.
Purushothaman, Kaathambari; Sivasankar, Esaimozhi; Krishnamoorthy, Monika; Karunakaran, Keerthana; Muniyan, Rajiniraja.
Afiliación
  • Purushothaman K; School of BioSciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu 632014 India.
  • Sivasankar E; School of BioSciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu 632014 India.
  • Krishnamoorthy M; School of BioSciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu 632014 India.
  • Karunakaran K; School of BioSciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu 632014 India.
  • Muniyan R; School of BioSciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu 632014 India.
In Silico Pharmacol ; 12(2): 66, 2024.
Article en En | MEDLINE | ID: mdl-39050776
ABSTRACT
Abnormal deposition or aggregation of protein alpha-synuclein and tau in the brain leads to neurodegenerative disorders. Excessive hyperphosphorylation of tau protein and aggregations destroys the microtubule structure resulting in neurofibrillary tangles in neurons and affecting cytoskeleton structure, mitochondrial axonal transport, and loss of synapses in neuronal cells. Tau tubulin kinase 1 (TTBK1), a specific neuronal kinase is a potential therapeutic target for neurodegenerative disorders as it is involved in hyperphosphorylation and aggregation of tau protein. TTBK inhibitors are now the subject of intense study, but limited numbers are found. Hence, this study involves structure-based virtual screening of TTBK1 inhibitor analogs to obtain efficient compounds targeting the TTBK1 using docking, molecular dynamics simulation and protein-ligand interaction profile. The initial analogs set containing 3884 compounds was subjected to Lipinski rule and the non-violated compounds were selected. Docking analysis was done on 2772 compounds through Autodock vina and Autodock 4.2. Data Warrior and SwissADME was utilized to filter the toxic compounds. The stability and protein-ligand interaction of the docked complex was analyzed through Gromacs and VMD. Molecular simulation results such as RMSD, Rg, and hydrogen bond interaction along with pharmacokinetic properties showed CID70794974 as the potential hit targeting TTBKl prompting the need for further experimental investigation to evaluate their potential therapeutic efficacy in Alzheimer's disease. Supplementary Information The online version contains supplementary material available at 10.1007/s40203-024-00242-z.
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: In Silico Pharmacol Año: 2024 Tipo del documento: Article Pais de publicación: Alemania

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: In Silico Pharmacol Año: 2024 Tipo del documento: Article Pais de publicación: Alemania