@article{oai:nagasaki-u.repo.nii.ac.jp:00002248,
 author = {Taguchi, Yuzuru and Nishida, Noriyuki},
 issue = {2},
 journal = {PLOS ONE},
 month = {Feb},
 note = {Prions are unique infectious agents, consisting solely of abnormally-folded prion protein (PrPSc). However, they possess virus-like features, including strain diversity, the ability to adapt to new hosts and to be altered evolutionarily. Because prions lack genetic material (DNA and RNA), these biological phenomena have been attributed to the structural properties of PrPSc. Therefore, many structural models of the structure of PrPSchave been proposed based on the limited structural information available, regardless of the incompatibility with high-resolution structural analysis. Recently hypothesized models consist solely of β- sheets and intervening loops/kinks; i.e. parallel in-register β-sheet and β-solenoid models. Owing to the relative simplicity of these structural models of PrPSc, we hypothesized that numerical conversion of the primary structures with a relevant algorithm would enable quantitative comparison between PrPs of distinct primary structures. We therefore used the theoretical values of β-sheet (Pβ) and random-coil (Pc) propensity calculated by secondary structure prediction with a neural network, to analyze interspecies transmission of prions. By reviewing experiments in the literature, we ascertained the biological relevance of Pβ and Pc and found that these classical parameters surprisingly carry substantial information of amyloid structures. We also demonstrated how these parameters could aid in interpreting and explaining phenomena in interspecies transmissions. Our approach can lead to the development of a versatile tool for investigating not only prions but also other amyloids., PLOS ONE, 12(2), e0171974; 2017},
 title = {Secondary-structure prediction revisited: Theoretical β-sheet propensity and coil propensity represent structures of amyloids and aid in elucidating phenomena involved in interspecies transmission of prions},
 volume = {12},
 year = {2017}
}