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Bioinformatics Advance Access originally published online on June 28, 2007
Bioinformatics 2007 23(17):2218-2225; doi:10.1093/bioinformatics/btm325
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© The Author 2007. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Identification of amyloid fibril-forming segments based on structure and residue-based statistical potential

Zhuqing Zhang 1,2, Hao Chen 1,2 and Luhua Lai 1,2,*

1Beijing National Laboratory for Molecular Sciences, State Key Laboratory for Structural Chemistry of Unstable and Stable Species, College of Chemistry and Molecular Engineering and 2Center for Theoretical Biology, Peking University, Beijing 100871, China

*To whom correspondence should be addressed.


  Abstract

Motivation: Experimental evidence suggests that certain short protein segments have stronger amyloidogenic propensities than others. Identification of the fibril-forming segments of proteins is crucial for understanding diseases associated with protein misfolding and for finding favorable targets for therapeutic strategies.

Result: In this study, we used the microcrystal structure of the NNQQNY peptide from yeast prion protein and residue-based statistical potentials to establish an algorithm to identify the amyloid fibril-forming segment of proteins. Using the same sets of sequences, a comparable prediction performance was obtained from this study to that from 3D profile method based on the physical atomic-level potential ROSETTADESIGN. The predicted results are consistent with experiments for several representative proteins associated with amyloidosis, and also agree with the idea that peptides that can form fibrils may have strong sequence signatures. Application of the residue-based statistical potentials is computationally more efficient than using atomic-level potentials and can be applied in whole proteome analysis to investigate the evolutionary pressure effect or forecast other latent diseases related to amyloid deposits.

Availability: The fibril prediction program is available at ftp://mdl.ipc.pku.edu.cn/pub/software/pre-amyl/

Contact: lhlai{at}pku.edu.cn

Supplementary information: Supplementary data are available at Bioinformatics online.

Associate Editor: Dmitrij Frishman

Received on December 6, 2006; revised on May 29, 2007; accepted on June 15, 2007

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