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A serendipitous survey of prediction algorithms for amyloidogenicity
Article first published online: 26 NOV 2013
Copyright © 2013 Wiley Periodicals, Inc.
Special Issue: Peptide Engineering Meeting 6
Volume 100, Issue 6, pages 780–789, November 2013
How to Cite
Roland, B. P., Kodali, R., Mishra, R. and Wetzel, R. (2013), A serendipitous survey of prediction algorithms for amyloidogenicity. Biopolymers, 100: 780–789. doi: 10.1002/bip.22305
- Issue published online: 26 NOV 2013
- Article first published online: 26 NOV 2013
- Accepted manuscript online: 26 JUL 2013 11:49AM EST
- Manuscript Accepted: 28 MAY 2013
- Manuscript Received: 30 MAR 2013
- NIH . Grant Number: R01 GM099718
The 17- amino acid N-terminal segment of the Huntingtin protein, httNT, grows into stable α-helix rich oligomeric aggregates when incubated under physiological conditions. We examined 15 scrambled sequence versions of an httNT peptide for their stabilities against aggregation in aqueous solution at low micromolar concentration and physiological conditions. Surprisingly, given their derivation from a sequence that readily assembles into highly stable α-helical aggregates that fail to convert into β-structure, we found that three of these scrambled peptides rapidly grow into amyloid-like fibrils, while two others also develop amyloid somewhat more slowly. The other 10 scrambled peptides do not detectibly form any aggregates after 100 h incubation under these conditions. We then analyzed these sequences using four previously described algorithms for predicting the tendencies of peptides to grow into amyloid or other β-aggregates. We found that these algorithms—Zyggregator, Tango, Waltz, and Zipper—varied greatly in the number of sequences predicted to be amyloidogenic and in their abilities to correctly identify the amyloid forming members of this scrambled peptide collection. The results are discussed in the context of a review of the sequence and structural factors currently thought to be important in determining amyloid formation kinetics and thermodynamics. © 2013 Wiley Periodicals, Inc. Biopolymers (Pept Sci) 100: 780–789, 2013.