Employing an integrated computational simulation strategy to identify high-affinity ligands for TDP-43 amyloid...

Area of Science:

• Biochemistry
• Computational Biology
• Neuroscience

Background:

• Amyotrophic lateral sclerosis (ALS) is linked to TDP-43 protein aggregation.
• Targeting TDP-43 amyloid species is a promising therapeutic strategy for ALS.

Purpose of the Study:

• To develop an integrated computational simulation strategy for identifying high-affinity ligands against TDP-43 amyloid species.
• To identify and characterize novel ligands with therapeutic potential for ALS.

Main Methods:

• Integrated computational simulations including virtual screening, molecular dynamics (MD) simulations, and binding free energy evaluations.
• In vitro affinity assays to validate computational predictions.
• Steered molecular dynamics (SMD) simulations to assess ligand-induced disruption of amyloid structures.

Main Results:

• Successfully identified TDPL1 as a high-affinity ligand for TDP-43 amyloid proteins.
• In vitro assays confirmed the binding affinity predicted by computational methods.
• TDPL1 demonstrated the potential to disrupt the stability of TDP-43 amyloid aggregates.

Conclusions:

• The integrated computational strategy is effective for discovering high-affinity ligands targeting protein aggregates.
• TDPL1 shows potential as a therapeutic agent or diagnostic tool for ALS by targeting TDP-43 amyloid species.
• Findings provide a molecular basis for developing novel treatments for ALS and related proteinopathies.