Background: The investigation of protein aggregation is of paramount importance in structural biology both for the formation of functional aggregates and for the development of diseases. Therefore, the development of new computational methods for predicting aggregation constitutes a very effective tool in this field. Currently, few methods exist for the prediction of pathological aggregates due to the lack of structural information regarding low-complexity regions, known to play a crucial role in the formation of pathological aggregates. However, both partially unfolded and misfolded proteins can give rise to aggregates such as amyloid fibrils. Therefore, the knowledge of new equilibrium structures prone to aggregation, as well as the investigation of the binding properties of homodimers, would open the doors to the development of new computational methods predicting amyloidogenic proteins.
Description: The main goal of this project is the investigation of the possible interactions between proteins, typically in misfolded or partially unfolded form, through computational methods based on analysis of the energetic organization of intermolecular interactions and the evaluation of shape complementarity in the binding regions. The energies of interaction between partner molecules will be investigated using a graph theory approach, while the complementarity between the two putative interfaces will be investigated through a recently developed method based on the Zernike polynomial formalism. The study can be applied to the case of amyloid light-chain amyloidosis (AL) which is a "protein misfolding disorder", where a group of plasma cells synthetizes misfolding light chains of antibodies able to bind themselves and to form amyloid fibrils. The formation of amyloid fibrils and the subsequent precipitation causes damage to organs and tissues. The analysis of the formation and characterization of homodimers, which are considered the seed of the pre-fibrillar phase, will aim to predict immunoglobulin sequences with a high probability of developing pathological aggregation.
 Computational and structural biotechnology journal 19, 29-36 (2020)
 Journal of chemical information and modeling, 60 (3), 1884-1891 (2018)
 Nature Reviews Disease Primers volume 4, Article number: 38 (2018).
Main Supervisor: Giancarlo Ruocco (Nanotechnologies for Neurosciences)
- Background in Biophysics and Biochemistry.
- Experience in data manipulation, visualization, and analysis)
- Experience in structural computational biology of biomolecules
- basic knowledge of programming (R and python).
- Bioinformatics tools for the analysis of protein structures
- Mathematical properties of the Zernike formalism
- knowledge of immunoglobulin structural properties and function.
- experience in Molecular Dynamics simulations
How to apply. Prospective students must submit, using the online form, the following documents
- 2-page CV, which includes studies, expertise and achievements.
- 1-page research statement, which includes the choice of a project from the list above and a justification of the choice. Only if robustly justified, the student may signal their interest also for a second project, but there is no guarantee that this will be taken into account by the selection panel.
- A transcript of undergraduate and postgraduate studies.
- A valid IELTS certificate, obtained no more than two years before the proposed registration date.
- Contact details of two referees.
Deadline for application: 8th of October 2021 .