Abstract
Many of the neurodegenerative disorders associated with aging, for example Alzheimer's disease, are thought to be associated with the large-scale self-assembly of nanoscale protein aggregates in the brain. A better understanding of this aggregation process might hold the key to improved therapies and even prevention. However, the individual peptide structures are so complex that molecular dynamics (MD) simulations of the entire aggregation process are impossible. Here we outline a novel approach to this many-protein problem, in which the goal is to extract the key interaction characteristics from large-scale MD simulations of few-peptide interactions, and then use these as the input to rule-based (i.e., agent-based) aggregation models. We investigate and discuss the likely consequences of such a procedure by examining a range of feasible aggregation processes.
| Original language | English |
|---|---|
| Pages (from-to) | 1338-1351 |
| Number of pages | 14 |
| Journal | Journal of Computational and Theoretical Nanoscience |
| Volume | 6 |
| Issue number | 6 |
| DOIs | |
| State | Published - Jun 1 2009 |
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Keywords
- Agent-Based Modeling
- Alzheimer's Disease (AD)
- Amyloid Beta (Aβ) Peptide
- Coalescence-Fragmentation Model
- Dimerization Process
- Molecular Dynamics (MD) Simulations
ASJC Scopus subject areas
- Condensed Matter Physics
- Electrical and Electronic Engineering
- Materials Science(all)
- Computational Mathematics
- Chemistry(all)
Cite this
Modeling the self-assembly dynamics of macromolecular protein aggregates underlying neurodegenerative disorders. / Zhao, Zhenyuan; Singh, Rajiv; Barman, Arghya; Johnson, Neil F; Prabhakar, Rajeev.
In: Journal of Computational and Theoretical Nanoscience, Vol. 6, No. 6, 01.06.2009, p. 1338-1351.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Modeling the self-assembly dynamics of macromolecular protein aggregates underlying neurodegenerative disorders
AU - Zhao, Zhenyuan
AU - Singh, Rajiv
AU - Barman, Arghya
AU - Johnson, Neil F
AU - Prabhakar, Rajeev
PY - 2009/6/1
Y1 - 2009/6/1
N2 - Many of the neurodegenerative disorders associated with aging, for example Alzheimer's disease, are thought to be associated with the large-scale self-assembly of nanoscale protein aggregates in the brain. A better understanding of this aggregation process might hold the key to improved therapies and even prevention. However, the individual peptide structures are so complex that molecular dynamics (MD) simulations of the entire aggregation process are impossible. Here we outline a novel approach to this many-protein problem, in which the goal is to extract the key interaction characteristics from large-scale MD simulations of few-peptide interactions, and then use these as the input to rule-based (i.e., agent-based) aggregation models. We investigate and discuss the likely consequences of such a procedure by examining a range of feasible aggregation processes.
AB - Many of the neurodegenerative disorders associated with aging, for example Alzheimer's disease, are thought to be associated with the large-scale self-assembly of nanoscale protein aggregates in the brain. A better understanding of this aggregation process might hold the key to improved therapies and even prevention. However, the individual peptide structures are so complex that molecular dynamics (MD) simulations of the entire aggregation process are impossible. Here we outline a novel approach to this many-protein problem, in which the goal is to extract the key interaction characteristics from large-scale MD simulations of few-peptide interactions, and then use these as the input to rule-based (i.e., agent-based) aggregation models. We investigate and discuss the likely consequences of such a procedure by examining a range of feasible aggregation processes.
KW - Agent-Based Modeling
KW - Alzheimer's Disease (AD)
KW - Amyloid Beta (Aβ) Peptide
KW - Coalescence-Fragmentation Model
KW - Dimerization Process
KW - Molecular Dynamics (MD) Simulations
UR - http://www.scopus.com/inward/record.url?scp=67449122449&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=67449122449&partnerID=8YFLogxK
U2 - 10.1166/jctn.2009.1183
DO - 10.1166/jctn.2009.1183
M3 - Article
AN - SCOPUS:67449122449
VL - 6
SP - 1338
EP - 1351
JO - Journal of Computational and Theoretical Nanoscience
JF - Journal of Computational and Theoretical Nanoscience
SN - 1546-1955
IS - 6
ER -