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Computational modeling of the relationship between amyloid and disease

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Abstract

Amyloid is the name given to a special type of linear protein aggregate that exhibits a common set of structural features and dye binding capabilities. The formation of amyloid is associated with over 27 distinct human diseases which are collectively referred to as the amyloidoses. Although there is great diversity amongst the amyloidoses with regard to the polypeptide monomeric precursor, targeted tissues, and the nature and time course of disease development, the common underlying link of a structurally similar amyloid aggregate has prompted the search for a unified theory of disease progression in which amyloid production is the central element. Computational modeling has allowed the formulation and testing of scientific hypotheses for exploring this relationship. However, the majority of computational studies on amyloid aggregation are pitched at the atomistic level of description, in simple ideal solution environments, with simulation time scales of the order of microseconds and system sizes limited to 100 monomers (or fewer). The experimental reality is that disease-related amyloid aggregation processes occur in extremely complex reaction environments (i.e. the human body), over time scales of months to years with monitoring of the reaction achieved using extremely coarse or indirect experimental markers that yield little or no atomistic insight. Clearly, a substantial gap exists between computational and experimental communities with a deficit of ‘useful’ computational methodology that can be directly related to available markers of disease progression. This review will place its focus on the development of these latter types of computational models and discuss them in relation to disease onset and progression.

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Notes

  1. SAP is an acute-phase serum protein that recognizes microbial polysaccharides and matrix components which also binds DNA, chromatin, and histones [Pepys et al. 1979; Mold et al. 2001]

  2. A model was developed (Hall et al. 2005; Hall and Hirota 2008) which examined the effect of peptide position and flanking regions on the the amyloidogenicity of a peptide fragment. A model reaching similar conclusions was also later developed (Abeln and Frenkel 2008). These models place a new light on the effect of position which was previously considered unimportant and is only now starting to be appreciated.

  3. An interesting point not pursued by Carulla et al. (2005) was the finding that the SH3 amyloid fibers would always (slowly) dissolve to yield the same critical concentration of free soluble SH3 monomers if the supernatant was removed after centrifugation and then replaced with fresh buffer.

  4. Although this dogma is not without exceptions and may depend upon the amyloid conformation. For instance the existence of amyloid based yeast prion strains/variants formed from the same protein can dramatically exert different effects on the cell—from relatively harmless to lethal (McGlinchey et al. 2011). Similarly a strain- and size-dependent cytotoxicity was found in different APrP strains (Lee et al. 2011).

  5. But not all—see, for example, the probabilistic modeling of plaque growth done in the laboratory of Hyman (Urbanc et al. 1999)

  6. This assumption is important to understand as it implies that there are no structural transitions or alternately multiple non-interconverting independent species, thus making the generalized kinetic mechanism a set of elementary steps involving addition or breakage. Obviously, when this assumption does not hold, the kinetic mechanism must be modified!

  7. For such systems, all excess protein above the critical concentration of monomer will form amyloid, whilst systems with total concentrations below the critical concentration will form very small amounts of amyloid.

  8. This was the original title of our paper in an earlier submitted form and the one by which we still refer to it between ourselves.

  9. Due to the fact the proteins in the body are capable of being synthesized as required.

  10. i.e. what happens to the product, are more fiber ends produced by phagocytic attack?

  11. Also known as the loss of heterozygosity model.

  12. In Mendelian genetics, people may be born with either two dominant copies of the allelle (homozygous dominant), AA, one dominant and one recessive allele (heterozygous), Aa, or two incompetent allelles (homozygous recessive), aa. With regard to the cancer progression studied by Knudson, for the (healthy) AA case, disease manifestation would require sequential injury or mutation to both of the two healthy copies of the gene over the lifetime of the individual (with each injury effecting an A→a transition). In the (healthy) Aa case, disease occurrence would require only a single mutation in one healthy copy. For the unhealthy, aa case no additional mutation is required and disease would occur at a young age. Thus, in Knudson’s two hit model, dependent on the genetic state of the patient, cancer could progress by suffering two, one, or no additional injuries to the underlying genetic material.

  13. This last case has recently been called infrangible (Cohen et al. 2011).

  14. And quickly reviewed (Xue et al. 2010)

  15. Recently a more realistic polymer model has been developed (Schmit et al. 2011)

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Acknowledgments

The research of H.E. is supported by the Intramural Research Program of the NIH, National Institute of Diabetes Digestive and Kidney Diseases. The research of D.H. is supported by the Japanese Science and Technology Agency (JST) and the University of Tsukuba under the special coordinated scheme ‘Funds in Aid for the Promotion of Young Scientists’ Independent Research’. Dr. Nami Hirota for helpful comments. D.H. would like to acknowledge the help of Ms. L. Sayuri, Ms. M. Satoko and Ms. I. Sakura for their kind help in preparing this Review article.

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Special issue: Computational Biophysics.

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Hall, D., Edskes, H. Computational modeling of the relationship between amyloid and disease. Biophys Rev 4, 205–222 (2012). https://doi.org/10.1007/s12551-012-0091-x

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