From mechanistic modeling to AI-driven design: computational strategies for targeting the γ-secretase complex - PubMed
4 hours ago
- #Alzheimer's disease
- #γ-secretase
- #computational modeling
- Computational biology advancements are enabling more precise therapeutic targeting of complex membrane proteins.
- The γ-secretase complex, linked to Alzheimer's disease and many substrates, exemplifies this shift, as traditional inhibitors face off-target toxicity issues.
- Integrative modeling using cryo-EM and biophysical data provides atomic-resolution insights into γ-secretase dynamics and substrate recognition.
- All-atom molecular dynamics simulations with enhanced sampling techniques map conformational landscapes and substrate selectivity determinants.
- Computational modeling translates familial AD mutations into mechanistic understanding through structure-function mapping.
- AI integration, including deep generative models and machine learning, accelerates discovery of modulators that reduce Aβ production while preserving essential pathways.
- The review showcases how computational strategies are reshaping drug development for safer, more selective modulators across diseases.