Chitinase proteins are expressed in most of reigns, from fungi to mammals. This kind of proteins can cleave the chitin, the second most abundant polysaccharide in nature. Mammals do not synthesize nor are able to use it, but they express Chitinase proteins. It has been proved that this kind of proteins are involved in several pathologies. Human Acidic Mammalian Chitinase is involved in the development of pathologies related to the Th2 inflammation. It has been discovered that the inhibition of this protein allowed the reduction of the inflammation. This effect makes this protein a very interesting target for the treatment of this kind of pathologies. In this PhD thesis, the first subject is the target fishing procedure applied to a series of macrocyclic compounds endowed with antifungal activity. The result of the target fishing has been the chitinase protein, and it has been rationally designed a new derivative able to inhibit the chitinase protein with higher potency. The second theme of this work has been the computational study the complex between the rationally designed chitinase inhibitor and the human Acidic Mammalian Chitinase, to identify the most reliable binding mode of the compound inside the binding pocket. The identification of the binding mode has been followed by the design of a library of derivatives, using the information acquired after the study, to improve the activity of the series of compounds towards the Acidic Mammalian Chitinase. The last topic has been the Structure Based Virtual Screening on the Acidic Mammalian Chitinase to find novel scaffolds active as AMCase inhibitor. A first screening based on pharmacophoric filtration and docking calculations has been done, identifying a preliminary hit, on which it has been performed a substructure search, that allowed the discovery of a more active derivative. This molecule has been examined with Molecular Dynamics simulations observing modification in the binding mode during each replica. It has been done a cluster analysis used for the generation of a new pharmacophoric model. The selected cluster representatives have been used as receptors for an ensemble docking calculation that allowed the identification of a third molecule biologically active as AMCase inhibitor.
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