Characterization of recently identified gelsolin variants responsible for a novel renal amyloidosis and in silico screening of drug candidates

Proteins are long, linear, polymers that adopt defined three-dimensional structures (folding) to properly play their role in the organism. A growing number of diseases are caused by protein misfolding, where the toxicity stems from a non-correct protein structure. Amyloidosis belongs to this broad family of maladies, which are characterized by deposit of fibrillar protein aggregates in different parts of the body. Gelsolin amyloidosis (GA) is relatively rare and caused by mutations in the gelsolin protein. Both a systemic (sGA) and renal form (rGA) of GA exist. Patients affected by sGA start to show symptoms in the third decade of life: usually eye, cutaneous and neurological symptoms are the first appearing, later, kidney and blood vessels are affected leading eventually to the death. Conversely, in rGA patients, deposits are found only in the kidney but the molecular and pathological features leading to these differences in the clinical picture are not known. Due to its rarity and complex clinical picture, GA is believed to be often mis-diagnosed. To date, there is neither a diagnostic test for GA nor an efficient treatment against the disease. Treatment of GA patients is solely based on ameliorations of its symptoms and requires often multiple surgeries and other invasive and expensive medical procedures. Therefore it is urgently sought to design novel drugs blocking gelsolin amyloid deposition, which is at the base of GA symptoms. For these reasons, this project focuses on the understanding of the molecular aspects of the disease. We will employ techniques able to visualize the mutated proteins at an atomic level of detail. Moreover, we will complement structural information with experiments to understand the role of the mutations in the disease. The acquired knowledge will be finally used to start a process for the discovery of novel compounds against GA, using computational biology tools