Development of computational approach to study the mechanisms of microbe-induced amyloidogenesis – MICROIDOSIS

Amyloid fibrils are linked to the serious diseases, referred to as “amyloidosis” including Alzheimer's disease, type II diabetes and heart diseases. Although significant progress has been made in the characterization of some proteins involved in the disease-related amyloid formation, the elements triggering their accumulation within the human body remain poorly understood. In the last decade, an increasing number of cases of microbe-induced amyloidosis have been described. Despite the increasing acknowledgment of the concept of microbe-induced amyloidosis, the underlying mechanism of this process still remains elusive. Based on the existing knowledge, we hypothesize that some microbial proteins can trigger amyloid fibrillation of human proteins via axial co-aggregation within amyloid fibrils. Our main objective of this project is to test this hypothesis. The bottleneck of all experimental projects aimed at proving this hypothesis is identification of the most probable protein candidates among the microbe-human pairs as targets for further comprehensive investigation. This challenge can be overcome by developing bioinformatics tools capable of predicting protein coaggregation and subsequent large-scale scans of microbial proteomes versus human one. Here, using structure-based and artificial intelligence methods we aim to develop bioinformatics predictors for the co-aggregation leading to a list of top candidates. This will pave the way for subsequent experimental tests. This project integrates multiple disciplines, including structural biology and digital science, and leverages omics data to address a high-impact public health challenge. It brings out a new concept and bioinformatics methods accelerating research in the fields of life sciences and health. It aligns with strategic priorities defined by the State which include Artificial intelligence and Translational research on rare diseases.