Prediction of aggregation rate and aggregation‐prone segments in polypeptide sequences

Abstract

The reliable identification of β‐aggregating stretches in protein sequences is essential for the development of therapeutic agents for Alzheimer's and Parkinson's diseases, as well as other pathological conditions associated with protein deposition. Here, a model based on physicochemical properties and computational design of β‐aggregating peptide sequences is shown to be able to predict the aggregation rate over a large set of natural polypeptide sequences. Furthermore, the model identifies aggregation‐prone fragments within proteins and predicts the parallel or anti‐parallel β‐sheet organization in fibrils. The model recognizes different β‐aggregating segments in mammalian and nonmammalian prion proteins, providing insights into the species barrier for the transmission of the prion disease.