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Title: Prediction of sequence-dependent and mutational effects on the aggregation of peptides and proteins
Authors: Fernandez-Escamilla, AM ×
Rousseau, Frederic
Schymkowitz, Joost
Serrano, L #
Issue Date: Oct-2004
Publisher: Gale Group Inc.
Series Title: Nature Biotechnology vol:22 issue:10 pages:1302-1306
Abstract: We have developed a statistical mechanics algorithm, TANGO, to predict protein aggregation. TANGO is based on the physico-chemical principles of beta-sheet formation, extended by the assumption that the core regions of an aggregate are fully buried. Our algorithm accurately predicts the aggregation of a data set of 179 peptides compiled from the literature as well as of a new set of 71 peptides derived from human disease-related proteins, including prion protein, lysozyme and beta2-microglobulin. TANGO also correctly predicts pathogenic as well as protective mutations of the Alzheimer beta-peptide, human lysozyme and transthyretin, and discriminates between beta-sheet propensity and aggregation. Our results confirm the model of intermolecular beta-sheet formation as a widespread underlying mechanism of protein aggregation. Furthermore, the algorithm opens the door to a fully automated, sequence-based design strategy to improve the aggregation properties of proteins of scientific or industrial interest.
URI: 
ISSN: 1087-0156
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Non-KU Leuven Association publications
× corresponding author
# (joint) last author

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