A method for probing the mutational landscape of amyloid structure

Motivation: Proteins of all kinds can self-assemble into highly ordered β-sheet aggregates known as amyloid fibrils, important both biologically and clinically. However, the specific molecular structure of a fibril can vary dramatically depending on sequence and environmental conditions, and mutations can drastically alter amyloid function and pathogenicity. Experimental structure determination has proven extremely difficult with only a handful of NMR-based models proposed, suggesting a need for computational methods. Results: We present AmyloidMutants, a statistical mechanics approach for de novo prediction and analysis of wild-type and mutant amyloid structures. Based on the premise of protein mutational landscapes, AmyloidMutants energetically quantifies the effects of sequence mutation on fibril conformation and stability. Tested on non-mutant, full-length amyloid structures with known chemical shift data, AmyloidMutants offers roughly 2-fold improvement in prediction accur...

• Type: Journal
• Year: 2011
• Where: BIOINFORMATICS
• Authors: Charles W. O'Donnell, Jérôme Waldispühl, Mieszko Lis, Randal Halfmann, Srinivas Devadas, Susan Lindquist, Bonnie Berger
• Keywords: BIOINFORMATICS 2011, Biometrics, Mutant Prediction, Statistical Mechanics Approach, Toxic Strains