Novel and Potential Small Molecule Scaffolds as DYRK1A Inhibitors by Integrated Molecular Docking-Based Virtual...

Area of Science:

• Biochemistry
• Neuroscience
• Computational Chemistry

Background:

• Dual-specificity tyrosine phosphorylation-regulated kinase 1A (DYRK1A) is an emerging therapeutic target for neurodegenerative diseases, particularly Alzheimer's disease (AD).
• Identifying selective inhibitors for DYRK1A is crucial for developing effective AD treatments.

Purpose of the Study:

• To perform virtual screening of the molMall database to identify potential DYRK1A inhibitors.
• To assess the selectivity and binding stability of identified compounds against DYRK1A and related kinases.
• To evaluate the drug-likeness and toxicity profiles of potential inhibitors.

Main Methods:

• Molecular docking was employed to screen the molMall database against the DYRK1A protein.
• Glide XP docking was used to assess selectivity against twelve related protein kinases.
• MM/GBSA calculations, physicochemical property prediction, and ProTox-II toxicity assessment were performed.
• 100 ns molecular dynamics (MD) simulations were conducted to validate binding stability.

Main Results:

• Six hit compounds (molmall IDs 9539, 11352, 15938, 19037, 21830, 21878) showed favorable interactions with key DYRK1A residues, particularly Leu241.
• Selected ligands demonstrated stability within the DYRK1A ATP binding pocket across 100 ns MD simulations.
• Predicted physicochemical and pharmacokinetic properties suggest potential for oral activity in the central nervous system (CNS).

Conclusions:

• The study successfully identified six stable DYRK1A inhibitors from the molMall database using computational methods.
• These compounds represent promising candidates for further development as therapeutic agents for Alzheimer's disease.
• The findings highlight the utility of integrated computational approaches for drug discovery against neurodegenerative targets.