Sequence determinants of amyloid fibril formation

Abstract

The establishment of rules that link sequence and amyloid feature is critical for our understanding of misfolding diseases. To this end, we have performed a saturation mutagenesis analysis on the de novodesigned amyloid peptide STVIIE (1). The positional scanning mutagenesis has revealed that there is a position dependence on mutation of amyloid fibril formation and that both very tolerant and restrictive positions to mutation can be found within an amyloid sequence. In this system, mutations that accelerate ␤-sheet polymerization do not always lead to an increase of amyloid products. On the contrary, abundant fibrils are typically found for mutants that polymerize slowly. From these experiments, we have extracted a sequence pattern to identify amyloidogenic stretches in proteins. The pattern has been validated experimentally. In silico sequence scanning of amyloid proteins also supports the pattern. Analysis of protein databases has shown that highly amyloidogenic sequences matching the pattern are less frequent in proteins than innocuous amino acid combinations and that, if present, they are surrounded by amino acids that disrupt their aggregating capability (amyloid breakers). This study provides the potential for a proteome-wide scanning to detect fibril-forming regions in proteins, from which molecules can be designed to prevent and͞or disrupt this process.I t is accepted that misfolding of peptides and proteins cause the fibrillar aggregates that characterize the group of diseases known as amyloidoses (1, 2). Despite active research, a detailed understanding of the molecular principles underlying the transformation of soluble proteins into amyloid aggregates is still lacking (1-3).The group of peptides and proteins capable of forming amyloid fibrils is very diverse (4-8). This group does not only consist of proteins involved in amyloid deposits in vivo (4), but also of nonpathogenic (15, 16) and designed peptides and proteins (7,8). X-ray fiber diffraction data indicate that all amyloid fibrils share a cross-␤-structure, regardless of the sequence or native fold of the soluble precursor (1, 2). Thus, an increasingly adopted view is that the ability to form amyloid fibrils is a general property of the polypeptide backbone (6). Nevertheless, the propensity of a given polypeptide to form amyloid fibrils depends enormously on amino acid composition (7-10).A protein has to be partially or fully unfolded to aggregate (1, 2). Yet, mutations leading to aggregation can alter (9, 10), or not alter (11, 12), protein stability. Aggregation from some peptides and proteins involved in relevant amyloidoses, such as type II diabetes and Alzheimer's and Parkinson's disease, does not require, however, previous unfolding, because these molecules are largely unstructured under physiological conditions (2). Nevertheless, most of the natively unfolded proteins in vivo do not undergo aggregation (13), indicating that unfolding is necessary, but not sufficient, to promote aggregation. Hence, there must be some sequence motifs tha...

The AWSEM-Amylometer: predicting amyloid propensity and fibril topology using an optimized folding landscape model

“…27,32 Serrano and coworkers have also identified common patterns among amyloidogenic peptides by using mutation scanning experiments. 33 The X 1 X 2 V 3 I 4 I 5 X 6 pattern found in their experiments corresponds well with our computed sequence features of the class 7 topology.…”

Long-term memory consolidation: The role of RNA-binding proteins with prion-like domains

“…Short oligopeptide repeat sequences that reside within the PrDs also have role in the conformational plasticity. [123][124][125] Shuffled sequences of aminoacids from yeast prion domains remain capable of forming amyloids in vitro, indicating that the amino acid composition of prion domains, rather than their sequence alone, contributes importantly to amyloid assembly. 126 Recently synthetic prions have been made de novo enabled by the development of computer algorithms like PAPA (Prion Aggregation Prediction Algorithm) that uses amino acid composition to predict prion propensities of intrinsically disordered protein domains.…”

Hydrophobic Surface Burial Is the Major Stability Determinant of a Flat, Single-layer β-Sheet

“…6,7 DuBay et al found hydrophobicity to exhibit the strongest correlation with the aggregation rates among parameters tested in regression analysis. 45 Hydrophobic amino acids are consistently ranked high for cross-β aggregation in systematic mutation studies by Lopez de la Paz et al 6,50 The importance of hydrophobicity is generally interpreted as the driving force for β-sheet lamination that creates a "dry interface" between adjacent β-sheets. 51 Our finding of the dominant role of nonpolar surface burial for single-layer β-sheet stability suggest that nonpolar surface burial is also critical for the formation of each layer of β-sheets.…”