Abstract
We introduce a database containing peptides related to diseases arising from protein aggregation. The general database AmyLoad includes all experimentally studied protein fragments that could be involved in erroneous protein folding, leading to amyloid formation. The database has been extended since its first release with regard to new instances of peptides or their fragments. Moreover, information of related diseases has been added to all entries, whenever available. Currently the database includes all available peptides tested for their potential amyloid properties, obtained from diverse resources, creating the largest dataset available at one place. This enables comparison between properties of amyloid and non-amyloid peptides. We could also select candidates for the most pathogenic peptides, involved in several diseases related to protein aggregation. We also discuss a need for sub-databases of different structures, such as related to \(\beta \gamma \)-crystallins - a protein family occurring in the eye lens. Misfolding of these proteins may lead to various forms of cataract. Those freely available internet services can facilitate finding the link between a protein sequence, its propensity to aggregation and the resulting disease, as well as support research on their pharmacological treatment and prevention.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Garbuzynskiy, S.O., Lobanov, M.Y., Galzitskaya, O.V.: FoldAmyloid: a method of prediction of amyloidogenic regions from protein sequence. Bioinformatics 26(3), 326–332 (2010)
Goldschmidt, L., Tenga, P.K., Riek, R., Eisenberg, D.: Identifying the amylome, proteins capable of forming amyloid-like fibrils. PNAS 107, 3487–3492 (2010)
Bryan Jr., A.W., O’Donnell, C.W., Menke, M., Cowen, L.J., Lindquist, S., Berger, B.: STITCHER: dynamic assembly of likely amyloid and prion -structures from secondary structure predictions. Proteins, vol. 80, pp. 410–420 (2011)
O’Donnell, C.W., Waldispühl, J., Lis, M., Halfmann, R., Devadas, S., Lindquist, S., Berger, B.: A method for probing the mutational landscape of amyloid structure. Bioinformatics 27, i34–i42 (2011)
Beerten, J., Van Durme, J., Gallardo, R., Capriotti, E., Serpell, L., Rousseau, F., Schymkowitz, J.: WALTZ-DB: a benchmark database of amyloidogenic hexapeptides. Bioinformatics 31(10), 1698–1700 (2015)
Stanislawski, J., Kotulska, M., Unold, O.: Machine learning methods can replace 3D profile method in classification of amyloidogenic hexapeptides. BMC Bioinformatics 14, 21 (2013)
Gasior, P., Kotulska, M.: FISH Amyloid - a new method for finding amyloidogenic segments in proteins based on site specific co-occurrence of aminoacids. BMC Bioinformatics 15, 54 (2014)
Zambrano, R., Jamroz, M., Szczasiuk, A., Pujols, J., Kmiecik, S., Ventura, S.: AGGRESCAN3D (A3D): server for prediction of aggregation properties of protein structures. Nucleic Acids Res. (2015). doi:10.1093/nar/gkv359
Wozniak, P.P., Kotulska, M.: AmyLoad - website dedicated to amyloidogenic protein fragments. Bioinformatics (2015). doi:10.1093/bioinformatics/btv375, http://comprec-lin.iiar.pwr.edu.pl/amyload/
Thompson, M.J., Sievers, S.A., Karanicolas, J., Ivanova, M.I., Baker, D., Eisenberg, D.: The 3D profile method for identifying fibril-forming segments of proteins. Proc. Natl. Acad. Sci. U.S.A. 103(11), 4074–4078 (2006)
Fernandez-Escamilla, A.M., Rousseau, F., Schymkowitz, J., Serrano, L.: Prediction of sequence-dependent and mutational effects on the aggregation of peptides and proteins. Nat. Biotechnol. 22(10), 1302–1306 (2004)
Conchillo-Sol, O., de Groot, N.S., Avils, F.X., Vendrell, J., Daura, X., Ventura, S.: AGGRESCAN: a server for the prediction and evaluation of “hot spots” of aggregation in polypeptides. BMC Bioinformatics 8, 65 (2007)
Acknowledgements
This work was in part supported by the grant N N519 643540 from National Science Centre of Poland.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wozniak, P.P., Nebel, JC., Kotulska, M. (2016). Database of Peptides Susceptible to Aggregation as a Tool for Studying Mechanisms of Diseases of Civilization. In: Nguyen, N.T., Trawiński, B., Fujita, H., Hong, TP. (eds) Intelligent Information and Database Systems. ACIIDS 2016. Lecture Notes in Computer Science(), vol 9621. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49381-6_30
Download citation
DOI: https://doi.org/10.1007/978-3-662-49381-6_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-49380-9
Online ISBN: 978-3-662-49381-6
eBook Packages: Computer ScienceComputer Science (R0)