Michał Burdukiewicz, Visiting scientist at CBS, DTU

Challenges in the computational prediction of peptide amyloidogenicity

Aggregation-prone regions of amyloids cannot be described by exact amino acid motifs, but rather motifs of residues with specific physiochemical properties. Henceforth, we created AmyloGram, a software suitable for the detection of amyloids. The simplified amino acid alphabet, based on the physicochemical properties of amino acids, allows AmyloGram to handle the diversity of amyloid proteins. Our software is sensitive enough to detect amyloid proteins that were falsely assigned as non-amyloidogenic in public databases. AmyloGram is available as a web-server (www.smorfland.uni.wroc.pl/amylogram/) and the R package (https://cran.r-project.org/package=AmyloGram).

Host: Professor Daniel Otzen, iNANO & Dept. of Molecular Biology and Genetics, Aarhus University