Computational methods possess the capacity to provide atomic-level insights into the β-sheet structural organization of amyloid-forming self-assembled peptides, and peptide-based nanostructures. Our research aims at exploiting the self-assembly properties of self-assembling peptides and proteins to engineer novel peptide self-assembled bio-nanomaterials with promising applications in biomedicine, energy and environment.

 Designing inhibitors of amyloid formation as potential therapeutics of amyloid diseases

Amyloid deposition in human tissue is associated with a number of diseases including all common dementias and diabetes. A critical initial step to prevent amyloid fibril formation is to delineate the self-assembly properties and provide insights into the structure of amyloid fibrils of the associated peptide or protein in each disease. Our research aims at (i) elucidating the amyloid structures formed by amyloidogenic peptides and proteins, and (ii) designing peptidic and non-peptidic inhibitors of amyloid formation, as potential therapeutics for amyloid diseases, including Alzheimer’s, Parkinson’s and diabetes diseases.

Elucidating the biomolecular complex structures of ligand : protein complexes, and discovering novel molecules

Understanding the binding of small ligands to proteins is of significant importance, as ligand : protein interactions play a key role in living organisms’ processes. Our research aims to develop novel computational protocols investigating the molecular recognition of proteins (e.g., in bacteria proteins) by small-molecule ligands, and to discover novel organic compounds which can act as inhibitors or signaling molecules, with potential therapeutic applications. 

 Investigating interactions and between protein – RNA complexes, and redesigning RNA.

Our research aims to develop novel computational tools to investigate interactions between protein – RNA complexes, as well as to develop a novel pioneering computational framework for the design of such complexes.