Abstract
The main cause of several neurodegenerative diseases such as Alzhemier, Parkinson and spongiform encephalopathies is the formation of amyloid fibrils in proteins. The systematic analysis of amyloid and non-amyloid sequences provide deep insights on the preference of amino acid residues at different locations of amyloid and non-amyloid peptides. In this work, we have systematically analyzed 139 amyloid and 168 non-amyloid hexapeptides and revealed the preference of residues at six different positions. We observed that Glu, Ile, Ser, Thr and Val are dominant at positions six, five, one, two and three, respectively in amyloid peptides. In non-amyloids, similar trend is noticed for few residues whereas the residues Ala in position 2, Asn in position 4, Gly in position 6 etc, showed different trends to that of amyloids. Utilizing the positional preference of 20 amino acid residues, we devised a statistical method for discriminating amlyloids and non-amyloids, which showed an accuracy of 89% and 54%, respectively. Further, we have examined various machine learning techniques, and a method based on Random Forest showed an overall accuracy of 99.7% and 83% using self-consistent and 10-fold cross-validation, respectively using the positional preference of amyloids and non-amyloids along with three selected amino acid properties.
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
Preview
Unable to display preview. Download preview PDF.
References
Wurth, C., Guimard, N.K., Hecht, M.H.: Mutations that Reduce Aggregation of the Alzheimer’s Aβ42 Peptide: an Unbiased Search for the Sequence Determinants of Aβ Amyloidogenesis. J. Mol. Biol. 319(3), 1279–1290 (2004)
Groot, N.S., Aviles, F.X., Vendrell, J., Ventura, S.: Mutagenesis of the Central Hydrophobic Cluster in Aβ42 Alzheimer’s Peptide. Side-chain Properties Correlate with Aggregation Propensities. FEBS J. 273, 658–668 (2006)
Kim, W., Hecht, M.H.: Generic Hydrophobic Residues are Sufficient to Promote Aggregation of the Alzheimer’s Aβ42 Peptide. Proc. Natl. Acad. Sci. USA 103(4), 15824–15829 (2003)
Luheshi, L.M.: Systematic in Vivo Analysis of the Intrinsic Determinants of Amyloid β Pathogenicity. PLoS Biol. 5(11), e290 (2007)
Winkelmann, J., Calloni, G., Campioni, S., Mannini, B., Taddei, N., Chiti, F.: Low-level Expression of a Folding-incompetent Protein in Escherichia Coli: Search for the Molecular Determinants of Protein Aggregation in Vivo. J. Mol. Biol. 398, 600–613 (2010)
Thangakani, A.M., Kumar, S., Velmurugan, D., Gromiha, M.M.: How do Thermophilic Proteins Resist Aggregation? Proteins 80, 1003–1015 (2012)
Fernandez-Escamilla, A.M., Rousseau, F.: Prediction of Sequence-dependent and Mutational Effects on the Aggregation of Peptides and Proteins. Nat. Biotechnol. 22, 1302–1306 (2004)
Conchillo-Solé, O., Avilés, 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(3), 65 (2007)
Maurer-Stroh, S.: Exploring the Sequence Determinants of Amyloid Structure Using Position-specific Scoring Matrices. Nat. Methods 7, 237–242 (2010)
Agrawal, N.J., Kumar, S., Helk, B., Singh, S.K., Trout, B.L.: Aggregation in Protein-based Biotherapeutics: Computational Studies and Tools to Identify Aggregation-prone Regions. J. Pharm. Sci. 100(12), 5081–5095 (2010)
Belli, M., Ramazzotti, M., Chiti, F.: Prediction of Amyloid Aggregation in Vivo. EMBO Rep. 12(7), 657–663 (2011)
Lopez de la Paz, M., Serrano, L.: Sequence Determinants of Amyloid Fibril Formation. Proc. Natl. Acad. Sci. 101, 87–92 (2004)
Gromiha, M.M., Suwa, M.: A Simple Statistical Method for Discriminating Outer Membrane Proteins with Better Accuracy. Bioinformatics 21, 961–968 (2004)
Witten, I.H., Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques, 2nd edn., San Francisco (2005)
Gromiha, M.M., Suwa, M.: Discrimination of Outer Membrane Proteins Using Machine Learning Algorithms. Proteins 63, 1031–1037 (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Gromiha, M.M., Thangakani, A.M., Kumar, S., Velmurugan, D. (2012). Sequence Analysis and Discrimination of Amyloid and Non-amyloid Peptides. In: Huang, DS., Gupta, P., Zhang, X., Premaratne, P. (eds) Emerging Intelligent Computing Technology and Applications. ICIC 2012. Communications in Computer and Information Science, vol 304. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31837-5_65
Download citation
DOI: https://doi.org/10.1007/978-3-642-31837-5_65
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31836-8
Online ISBN: 978-3-642-31837-5
eBook Packages: Computer ScienceComputer Science (R0)