Computational Simulation of Alzheimer’s Amyloid Fibril Assembly
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Transcript of Computational Simulation of Alzheimer’s Amyloid Fibril Assembly
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Computational Simulation of Alzheimer’s Amyloid Fibril Assembly
Phil LoCascioPavan Ghattyvenkatakrishna
Ed UberbacherGenome Analysis and Systems Modeling
Biosciences Division
Research supported by the Department of Energy’s Office of ScienceOffice of Advanced Scientific Computing Research
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Amyloid peptides
Ordered fibrils and plaques
Chain extension
Aggregates
Goal: understanding B-amyloid self-assembly
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Fundamental amyloid assembly questions remain
What interactions and energies drive initial aggregation
How do initial aggregates achieve regular structures
How does chain growth occur
Where are the strategic steps and places where effective drugs could be attached
Assembly questions remain
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Visualize B-aggregate assembly by MD
ORNL research program
Visualize the assembly of amyloid B 40 and 42 to protofibrils: followed by growth
Look at forces that cause aggregation and key steps
Look at process of structure regularization to protofiber
Look at fiber growth mechanisms and potential for growth repression
Contrast assembly in B 40 with B 42
Expect to reach the 100-nanosecond regime for multiple runs
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Initial amyloid folding
Hydrophobic interactions cause the amyloid peptide to fold into a hairpin-like structure in about 1 nanosecond
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Initial amyloid peptide contact
Hydrophobic interactions and hydrogen bonds are formed in initial contact between amyloid peptides
These virtually always keep the peptides from coming apart
The process takes about 5 nanoseconds
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Amyloid aggregation
Hydrophobic interactions and hydrogen bonds are formed in initial contact between amyloid peptides
These virtually always keep the peptides from coming apart
This process takes about 15 nanoseconds
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Preventing fibril assembly in simulation
Drug and natural compounds are being evaluated using their effects on fibril assembly
Ab initio methods are used to build drug structure
Empirical model is placed in standard molecular mechanics code
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Summary
Unique capability to simulate amyloid molecular assemblies
Tools and infrastructure for partnering with other researchers using computational modeling
Advanced computational drug binding studies
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Philip F. LoCascioBiological and Environmental Sciences,Genome Analysis and Systems Modeling(865) [email protected]
Pavan GhattyvenkatakrishnaBiological and Environmental Sciences,Genome Analysis and Systems Modeling(865) [email protected]
Edward C. UberbacherBiological and Environmental Sciences,Genome Analysis and Systems Modeling(865) [email protected]
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Contacts