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Design of metastable β-sheet oligomers from natively unstructured peptide.

ABSTRACT: Amyloid oligomers represent the primary pathological species for neurodegenerative diseases such as Alzheimer's and Parkinson's diseases. Toxic oligomers are formed by many different proteins and peptides, but their polydispersity makes them highly dynamic and heterogeneous. One way to stabilize these structures is to prepare constrained peptides that can be used to study amyloid intermediates, to identify oligomer-specific drugs, and to generate conformational antibodies. These conformational antibodies have demonstrated that oligomers share a common epitope. In this research, we used a 40-amino acid unstructured segment of prion protein (Prp) 109-148 with substitutions of methionine for glycine (Prp-G) residues to prepare a stable and homogeneous population of β-sheet oligomer mimics. These structures were characterized by multiple biophysical and biochemical techniques that show characteristic features of oligomers. Finally, this preparation was not detected by three different sequence dependent prion antibodies.

SUBMITTER: Guerrero-Munoz MJ

PROVIDER: S-EPMC3867962 | biostudies-literature | 2013 Dec

REPOSITORIES: biostudies-literature

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Design of metastable β-sheet oligomers from natively unstructured peptide.

Guerrero-Muñoz Marcos J MJ Castillo-Carranza Diana L DL Sengupta Urmi U White Mark A MA Kayed Rakez R

ACS chemical neuroscience 20131014 12

Amyloid oligomers represent the primary pathological species for neurodegenerative diseases such as Alzheimer's and Parkinson's diseases. Toxic oligomers are formed by many different proteins and peptides, but their polydispersity makes them highly dynamic and heterogeneous. One way to stabilize these structures is to prepare constrained peptides that can be used to study amyloid intermediates, to identify oligomer-specific drugs, and to generate conformational antibodies. These conformational a ...[more]

PMID: 24106878

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Project description:Natively unstructured or disordered protein regions may increase the functional complexity of an organism; they are particularly abundant in eukaryotes and often evade structure determination. Many computational methods predict unstructured regions by training on outliers in otherwise well-ordered structures. Here, we introduce an approach that uses a neural network in a very different and novel way. We hypothesize that very long contiguous segments with nonregular secondary structure (NORS regions) differ significantly from regular, well-structured loops, and that a method detecting such features could predict natively unstructured regions. Training our new method, NORSnet, on predicted information rather than on experimental data yielded three major advantages: it removed the overlap between testing and training, it systematically covered entire proteomes, and it explicitly focused on one particular aspect of unstructured regions with a simple structural interpretation, namely that they are loops. Our hypothesis was correct: well-structured and unstructured loops differ so substantially that NORSnet succeeded in their distinction. Benchmarks on previously used and new experimental data of unstructured regions revealed that NORSnet performed very well. Although it was not the best single prediction method, NORSnet was sufficiently accurate to flag unstructured regions in proteins that were previously not annotated. In one application, NORSnet revealed previously undetected unstructured regions in putative targets for structural genomics and may thereby contribute to increasing structural coverage of large eukaryotic families. NORSnet found unstructured regions more often in domain boundaries than expected at random. In another application, we estimated that 50%-70% of all worm proteins observed to have more than seven protein-protein interaction partners have unstructured regions. The comparative analysis between NORSnet and DISOPRED2 suggested that long unstructured loops are a major part of unstructured regions in molecular networks.

Dataset Information

Design of metastable β-sheet oligomers from natively unstructured peptide.

Publications

Design of metastable β-sheet oligomers from natively unstructured peptide.

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