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Assessing the Stability of Alzheimer’s Amyloid Protofibrils Using Molecular Dynamics
Abstract
Amyloid fibrils represent a stable form of many misfolded proteins associated with numerous diseases. Among these are Parkinson's disease (alpha-synuclein), Type II diabetes (islet amyloid polypeptide), and Alzheimer's disease (amyloid beta-peptide, Abeta). The appearance of Abeta fibrils in neural tissue is a hallmark of Alzheimer's disease, and many studies have been conducted to determine and analyze the structure of these protein aggregates. The principal toxic species in Alzheimer's disease are believed to be soluble, oligomeric aggregates of Abeta, but numerous studies have found that the insoluble fibrillated form of the peptide also contributes to neurotoxicity. Thus, to design therapeutic agents to combat the progression of Alzheimer's disease, it is worthwhile to understand the thermodynamics of destabilizing these aggregates and the features that contribute to their stability. In this work, we present a systematic study of several factors that influence the stability of Abeta(42) fibrils following in silico mutation. We have employed standard molecular dynamics, as well as center-of-mass pulling and umbrella sampling, to study the thermodynamics of peptide dissociation from the core of a model protofibril at physiological temperature. Results indicate that a finite level of hydration around the Asp23-Lys28 salt bridge is crucial to protofibril stability, while mutation of Phe19 to glycine has no effect on the binding free energy of the terminal peptide. Packing between Ile32 and the aliphatic portion of the Lys28 side chain serves to regulate the level of hydration in the core of the protofibril and thus rigidify the Asp23-Lys28 salt bridge. These observations are important for designing compounds that target Abeta aggregates; interrupting these native interactions may destabilize these assemblies and ameliorate their toxicity.
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1 retracted
RETRACTED ARTICLE: A specific amyloid-β protein assembly in the brain impairs memory
Lesné, S., Koh, M. T., Kotilinek, L., Kayed, R., Glabe, C. G., Yang, A., Gallagher, M., & Ashe, K. H. (2006) · Nature · doi:10.1038/nature04533 · Cited by 2,769
RetractedMolecular dynamics with coupling to an external bath
Berendsen, H. J. C., Postma, J. P. M., van Gunsteren, W. F., DiNola, A., & Haak, J. R. (1984) · The Journal of Chemical Physics · doi:10.1063/1.448118 · Cited by 30,700
Particle mesh Ewald: An N ⋅log( N ) method for Ewald sums in large systems
Darden, T., York, D., & Pedersen, L. (1993) · The Journal of Chemical Physics · doi:10.1063/1.464397 · Cited by 30,546
Canonical dynamics: Equilibrium phase-space distributions
Hoover, W. G. (1985) · Physical Review A · doi:10.1103/physreva.31.1695 · Cited by 23,465
A smooth particle mesh Ewald method
Essmann, U., Perera, L., Berkowitz, M. L., Darden, T., Lee, H., & Pedersen, L. G. (1995) · The Journal of Chemical Physics · doi:10.1063/1.470117 · Cited by 22,514
Polymorphic transitions in single crystals: A new molecular dynamics method
Parrinello, M., & Rahman, A. (1981) · Journal of Applied Physics · doi:10.1063/1.328693 · Cited by 19,790
A unified formulation of the constant temperature molecular dynamics methods
Nosé, S. (1984) · The Journal of Chemical Physics · doi:10.1063/1.447334 · Cited by 19,152
The PyMOL Molecular Graphics System
DeLano, W. L. (2002) · Medical Entomology and Zoology · Cited by 18,147
GROMACS 4: Algorithms for Highly Efficient, Load-Balanced, and Scalable Molecular Simulation
Hess, B., Kutzner, C., van der Spoel, D., & Lindahl, E. (2008) · Journal of Chemical Theory and Computation · doi:10.1021/ct700301q · Cited by 15,908
Alzheimer's disease: the amyloid cascade hypothesis
Hardy, J. A., & Higgins, G. A. (1992) · Science · doi:10.1126/science.1566067 · Cited by 7,484
THE weighted histogram analysis method for free‐energy calculations on biomolecules. I. The method
Kumar, S., Rosenberg, J. M., Bouzida, D., Swendsen, R. H., & Kollman, P. A. (1992) · Journal of Computational Chemistry · doi:10.1002/jcc.540130812 · Cited by 6,808
Nonphysical sampling distributions in Monte Carlo free-energy estimation: Umbrella sampling
Torrie, G. M., & Valleau, J. P. (1977) · Journal of Computational Physics · doi:10.1016/0021-9991(77)90121-8 · Cited by 6,091
Interaction Models for Water in Relation to Protein Hydration
Berendsen, H. J. C., Postma, J. P. M., van Gunsteren, W. F., & Hermans, J. (1981) · The Jerusalem Symposia on Quantum Chemistry and Biochemistry · doi:10.1007/978-94-015-7658-1_21 · Cited by 5,654
Nonequilibrium Equality for Free Energy Differences
Jarzynski, C. (1997) · Physical Review Letters · doi:10.1103/physrevlett.78.2690 · Cited by 5,293
Soluble protein oligomers in neurodegeneration: lessons from the Alzheimer's amyloid β-peptide
Haass, C., & Selkoe, D. J. (2007) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm2101 · Cited by 4,744
Common structure of soluble amyloid oligomers implies common mechanism of pathogenesis
Kayed, R., Head, E., Thompson, J. L., McIntire, T. M., Milton, S. C., Cotman, C. W., & Glabe, C. G. (2003) · Science · doi:10.1126/science.1079469 · Cited by 4,064
Kaminski, G. A., Friesner, R. A., Tirado-Rives, J., & Jorgensen, W. L. (2001) · The Journal of Physical Chemistry B · doi:10.1021/jp003919d · Cited by 4,060
Oostenbrink, C., Villa, A., Mark, A. E., & Van Gunsteren, W. F. (2004) · Journal of Computational Chemistry · doi:10.1002/jcc.20090 · Cited by 3,719
Constant pressure molecular dynamics for molecular systems
Nosé, S., & Klein, M. L. (1983) · Molecular Physics · doi:10.1080/00268978300102851 · Cited by 3,260
3D structure of Alzheimer's amyloid-β(1–42) fibrils
Lührs, T., Ritter, C., Adrian, M., Riek-Loher, D., Bohrmann, B., Döbeli, H., Schubert, D., & Riek, R. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506723102 · Cited by 1,996
Self-Propagating, Molecular-Level Polymorphism in Alzheimer's ß-Amyloid Fibrils
Petkova, A. T., Leapman, R. D., Guo, Z., Yau, W.-M., Mattson, M. P., & Tycko, R. (2005) · Science · doi:10.1126/science.1105850 · Cited by 1,687
Torrie, G. M., & Valleau, J. P. (1974) · Chemical Physics Letters · doi:10.1016/0009-2614(74)80109-0 · Cited by 1,404
The metallobiology of Alzheimer's disease
Bush, A. I. (2003) · Trends in Neurosciences · doi:10.1016/s0166-2236(03)00067-5 · Cited by 1,315
Translating cell biology into therapeutic advances in Alzheimer's disease
Selkoe, D. J. (1999) · Nature · doi:10.1038/399a023 · Cited by 1,166
Kayed, R., Sokolov, Y., Edmonds, B., McIntire, T. M., Milton, S. C., Hall, J. E., & Glabe, C. G. (2004) · Journal of Biological Chemistry · doi:10.1074/jbc.c400260200 · Cited by 902
Deshpande, A., Mina, E., Glabe, C., & Busciglio, J. (2006) · The Journal of Neuroscience · doi:10.1523/jneurosci.1189-06.2006 · Cited by 494
Sgourakis, N. G., Yan, Y., McCallum, S. A., Wang, C., & Garcia, A. E. (2007) · Journal of Molecular Biology · doi:10.1016/j.jmb.2007.02.093 · Cited by 457
Izrailev, S., Stepaniants, S., Isralewitz, B., Kosztin, D., Lu, H., Molnar, F., Wriggers, W., & Schulten, K. (1999) · Lecture Notes in Computational Science and Engineering · doi:10.1007/978-3-642-58360-5_2 · Cited by 451
Paravastu, A. K., Qahwash, I., Leapman, R. D., Meredith, S. C., & Tycko, R. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0812033106 · Cited by 322
Molecular Dynamics Simulations of Alzheimer's β-Amyloid Protofilaments
Buchete, N.-V., Tycko, R., & Hummer, G. (2005) · Journal of Molecular Biology · doi:10.1016/j.jmb.2005.08.066 · Cited by 256
Amyloid β-Protein Monomer Folding: Free-Energy Surfaces Reveal Alloform-Specific Differences
Yang, M., & Teplow, D. B. (2008) · Journal of Molecular Biology · doi:10.1016/j.jmb.2008.09.039 · Cited by 247
Insights into the Amyloid Folding Problem from Solid-State NMR
Tycko, R. (2003) · Biochemistry · doi:10.1021/bi027378p · Cited by 216
Dynamics of Asp23−Lys28 Salt-Bridge Formation in Aβ10-35Monomers
Tarus, B., Straub, J. E., & Thirumalai, D. (2006) · Journal of the American Chemical Society · doi:10.1021/ja064872y · Cited by 211
Zheng, J., Jang, H., Ma, B., Tsai, C.-J., & Nussinov, R. (2007) · Biophysical Journal · doi:10.1529/biophysj.107.110700 · Cited by 182
Does CO2 Permeate through Aquaporin-1?
Hub, J. S., & de Groot, B. L. (2006) · Biophysical Journal · doi:10.1529/biophysj.106.081406 · Cited by 150
The free energy of spheres with dipoles: Monte Carlo with multistage sampling
Patey, G. N., & Valleau, J. P. (1973) · Chemical Physics Letters · doi:10.1016/0009-2614(73)80139-3 · Cited by 143
Structure of the 21–30 fragment of amyloid β‐protein
Baumketner, A., Bernstein, S. L., Wyttenbach, T., Lazo, N. D., Teplow, D. B., Bowers, M. T., & Shea, J. (2006) · Protein Science · doi:10.1110/ps.062076806 · Cited by 139
Nordihydroguaiaretic acid potently breaks down pre‐formed Alzheimer's β‐amyloid fibrils in vitro
Ono, K., Hasegawa, K., Yoshiike, Y., Takashima, A., Yamada, M., & Naiki, H. (2002) · Journal of Neurochemistry · doi:10.1046/j.1471-4159.2002.00904.x · Cited by 122
Metabolism of amyloid β peptide and pathogenesis of Alzheimer's disease
Saido, T. C., & Iwata, N. (2006) · Neuroscience Research · doi:10.1016/j.neures.2005.12.015 · Cited by 102
Replica Exchange Simulations of the Thermodynamics of Aβ Fibril Growth
Takeda, T., & Klimov, D. K. (2009) · Biophysical Journal · doi:10.1016/j.bpj.2008.10.008 · Cited by 96
Melquiond, A. S. J., Dong, X., Mousseau, N., & Derreumaux, P. (2008) · Current Alzheimer Research · doi:10.2174/156720508784533330 · Cited by 96
Miller, Y., Ma, B., & Nussinov, R. (2009) · Biophysical Journal · doi:10.1016/j.bpj.2009.05.042 · Cited by 94
In Silico Study of Full-Length Amyloid β 1−42 Tri- and Penta-Oligomers in Solution
Masman, M. F., Eisel, U. L. M., Csizmadia, I. G., Penke, B., Enriz, R. D., Marrink, . J., & Luiten, P. G. M. (2009) · The Journal of Physical Chemistry B · doi:10.1021/jp901057w · Cited by 82
Tarus, B., Straub, J. E., & Thirumalai, D. (2008) · Journal of Molecular Biology · doi:10.1016/j.jmb.2008.04.028 · Cited by 68
Protofibril Assemblies of the Arctic, Dutch, and Flemish Mutants of the Alzheimer's Aβ1–40 Peptide
Fawzi, N. L., Kohlstedt, K. L., Okabe, Y., & Head-Gordon, T. L. (2007) · Biophysical Journal · doi:10.1529/biophysj.107.121467 · Cited by 59
Misfolding of the amyloid β‐protein: A molecular dynamics study
Flöck, D., Colacino, S., Colombo, G., & Nola, A. D. (2005) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.20683 · Cited by 58
Interpeptide interactions induce helix to strand structural transition in Aβ peptides
Takeda, T., & Klimov, D. K. (2009) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.22406 · Cited by 55
Synaptic Retrogenesis and Amyloid-β in Alzheimer's Disease
Wasling, P., Daborg, J., Riebe, I., Andersson, M., Portelius, E., Blennow, K., Hanse, E., & Zetterberg, H. (2009) · Journal of Alzheimer s Disease · doi:10.3233/jad-2009-0918 · Cited by 53
Amyloid β-Protein: Experiment and Theory on the 21−30 Fragment
Murray, M. M., Krone, M. G., Bernstein, S. L., Baumketner, A., Condron, M. M., Lazo, N. D., Teplow, D. B., Wyttenbach, T., Shea, J., & Bowers, M. T. (2009) · The Journal of Physical Chemistry B · doi:10.1021/jp808384x · Cited by 53
All-atom molecular dynamics studies of the full-length β-amyloid peptides
Luttmann, E., & Fels, G. (2005) · Chemical Physics · doi:10.1016/j.chemphys.2005.08.071 · Cited by 37
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Metadata
- Authors
- Lemkul, J. A., & Bevan, D. R.
- Venue
- The Journal of Physical Chemistry B
- Publisher
- American Chemical Society (ACS)
- Published
- 2010-01-07
- Volume
- 114
- Issue
- 4
- Pages
- 1652-1660
- ISSN
- 1520-5207 (ISSN-L)
- 1520-6106
- OpenAlex
- W2043812489
- Cited by
- 508
- References
- 50
- FWCI
- 9.13
- Type
- journal article
- Language
- en
- Open access
- closed
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