Amyloids and amyloid-related disorders
Proteins are very important biomolecules that are involved in almost every biological process. In order to function, these biomolecules have to acquire their native structural conformation. Under certain circumstances, however, peptides and proteins can fail to adopt, or remain, in their native functional conformation, and can acquire misfolded conformations that are susceptible to form nonfunctional and potentially harmful aggregates termed amyloids. The onset and progression of more than 50 human disorders including Alzheimer’s disease, Parkinson’s disease, type II diabetes, and prion diseases are associated with the failure of a specific peptide or protein to adopt or remain in its native functional conformational state, and their subsequent conversion into insoluble fibrillar aggregates. In recent years, the process of amyloid formation has emerged as a subject of fundamental importance as it was recognised that many disorders associated with amyloid formation are no longer rare and are rapidly becoming some of the most common medical conditions in the ageing society. Millions of people around the world suffer from amyloid-related disorders, Alzheimer's and Parkinson's diseases alone afflict more than 50 million patients worldwide. Despite significant and sustained efforts, however, the molecular and mechanistic links between protein aggregation and toxicity remain challenging to characterise. In addition, there are still no effective disease modifying drugs or treatment modalities available for amyloid-related disorders. One of the main reasons for this are the complex nature of the peptide and protein aggregation and self-replication, and relatively poor understanding of these processes. Prevention and treatment of a given disease generally require a deep understanding of its underlying causes.
Schematic representation of the amyloid aggregation process
With our research, we aim to contribute to the greater understanding of amyloid aggregation process. In our research we exploit a variety of biophysical, molecular biology and bioinformatic methods to obtain mechanistic insights into amyloid aggregation process, investigate effects of various environmental factors on the aggregation process and the structure of aggregates. Also, we search for the potential inhibitors of amyloid aggregation.
Amyloid proteins we are studying
- Amyloid-beta peptide (related to Alzheimer's disease);
- S100 protein family (related to Alzheimer's disease);
- Alpha-synuclein (related to Parkinson's disease)
- Tau protein (related to Alzheimer's disease and tauopathies);
- Prion proteins (related to mad cow disease and other prion-related disorders);
- Human superoxidase dismutase(related to amyotrophic lateral sclerosis);
- Insulin (amyloid fibrils-forming model protein, also related to local injection amyloidosis);
- Lysozyme (amyloid fibrils-forming model protein, also related to familial systemic amyloidosis);
- ß2-microglobulin (related to dialysis-related amyloidosis);
- Huntingtin (related to Huntington's disease).
Methods and technologies applied in our research
- Gene engineering;
- Protein and nucleic acid electrophoresis;
- Production of recombinant proteins in bacteria;
- Chromatographic methods (e.g. ion exchange chromatography, affinity chromatography, size exclusion chromatography, high-performance liquid chromatography (HPLC)) to purify proteins and other molecules of interest;
- Monitoring of the amyloid aggregation process by measuring the absorption or dynamic light scattering of the solution, or the intensity of amyloid-specific dye fluorescence emission. Subsequently, we analyse aggregation kinetics using chemical kinetics tools;
- Infrared spectroscopy to obtain insights into the secondary structure of amyloid proteins and their aggregates;
- Atomic force microscopy to obtain insights into aggregate morphology and physical parameters (height, length, width, periodicity);
- Mass spectrometry to determine mass of the protein;
- Mechanistic insights into amyloid aggregation process are obtained by exploiting bioinformatic tools such as rModeler or AmyloFit.