Approcci In Silico per il riposizionamento di farmaci e la scoperta di nuove molecole attive contro l’Inflammasoma NLRP3

Atherosclerosis, diabetes, arthritis, cancer, Alzheimer’s, and Parkinson’s disease are, among many others, some of the more common diseases that affects our times. All these conditions are characterised by the presence of inflammation that contributes to their onset and development. Involvement of an inflammatory complex known as NLRP3 Inflammasome is in line with several studies which demonstrated that this complex is triggered by many signals known as Pathogen Associated Molecular Patterns (PAMPs) and Damage Associated Molecular Patterns (DAMPs), which are common in these pathologies. NLRP3, also known as NOD-, LRR- and pyrin domain-containing protein 3, is an immunological sensor, part of the NLRP3 Inflammasome complex that, when hyperactivated, sets off a series of events that disrupt cells and enhance the release of inflammatory mediators. In fact, once activated NLRP3 leads to the formation of a nucleation platform for the processing of an enzyme known as Caspase-1, via proximity-induced autoproteolysis. Activated Caspase-1 triggers, in turn, the activation of various cytokines, in particular IL-1β and IL-18, as well as a protein called Gasdermin-D. The latter, once activated in GSDMD-N, is the effector of pyroptosis, a programmed type of cell death, leading cells to break up and release cytokines, the Inflammasome itself and other inflammatory mediators such as ATP and ROS. Inflammasomes are then phagocytized by nearby immune cells, restarting the cycle and spreading inflammation throughout the body. These factors make the NLRP3 inflammasome an intriguing target for the development of first-line therapies for a range of conditions where levels of this protein are excessive. Repurposing "old" and known medications to treat both common and uncommon diseases is rapidly emerging as an appealing idea due to the usage of compounds with lower risk, potential for reduced total development costs and shorter development timing. Additionally, in silico methods can facilitate the screening of large libraries of compounds and the consequent identification of specific inhibitors. Here we have applied structure-based simulations to screen libraries of drugs from preclinical to approved, for the possible identification and repurposing, of new NLRP3 inhibitors.