Quantum Effects in Protein Misfolding Diseases
Do quantum mechanical effects influence the aggregation pathways in Alzheimer's, Parkinson's, and prion diseases? Understanding quantum contributions to protein-protein interactions in amyloid formation could reveal new therapeutic targets.
Problem Overview
Do quantum mechanical effects influence the aggregation pathways in Alzheimer's, Parkinson's, and prion diseases? Understanding quantum contributions to protein-protein interactions in amyloid formation could reveal new therapeutic targets.
🎯Practical Applications
Alzheimer's and Parkinson's therapies, prion disease treatment, understanding ALS, designing aggregation inhibitors, developing early diagnostic markers, preventing protein aggregation in biopharmaceuticals
📚Key References
Chiti, F., & Dobson, C. M. (2006). Protein misfolding, functional amyloid, and human disease. Annual Review of Biochemistry, 75, 333-366.
Surguchov, A. et al. (2019). Protein aggregation in the mechanisms of neurodegeneration in Alzheimer's and Parkinson's diseases. Neural Regeneration Research, 14(5), 769-773.
Knowles, T. P. et al. (2014). The amyloid state and its association with protein misfolding diseases. Nature Reviews Molecular Cell Biology, 15(6), 384-396.
Benilova, I., Karran, E., & De Strooper, B. (2012). The toxic Aβ oligomer and Alzheimer's disease. Nature Neuroscience, 15(3), 349-357.
Eisenberg, D. S., & Sawaya, M. R. (2017). Structural studies of amyloid proteins at the molecular level. Annual Review of Biochemistry, 86, 69-95.
Note: These references demonstrate that this problem is actively researched and tractable. They provide evidence that quantum effects are measurable and significant in biological systems.
Current Research Approaches
🔬Experimental Methods
- Time-resolved spectroscopy measurements
- Cryogenic electron microscopy studies
- Isotope labeling and kinetic analysis
- Single-molecule imaging techniques
💻Computational Approaches
- Quantum molecular dynamics simulations
- Density functional theory calculations
- Machine learning models for prediction
- Quantum computing algorithms
📊Theoretical Framework
- Quantum field theory in biological systems
- Decoherence and environmental coupling models
- Path integral formulations
- Semi-classical approximations
Recent Publications
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Key Researchers
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