In Silico Methods for Inhibitor Binding Analysis on Human Carbonic Anhydrase Isoforms And Tyrosinase Enzyme Aimed To The Development of New Therapeutics.

The rising of computational methods applied to life science, as well as the increase of computer performance determined a considerable growth in the speed and accuracy of drug discovery accompanied by a reduction in cost when compared to the traditional high throughput screening approach. Metalloenzymes represents one of the widest classes of enzymes present in nature. Indeed, they cover several classes of enzymes playing a crucial role in the survival of living organisms. Conversely, as for other enzymes, their overexpression leads to various disorders, spanning from metabolic disorder to cancer and infection. Thus, a plethora of metalloenzymes are nowadays attractive drug targets, being subject of study since decades. It is not possible to provide an in depth and comprehensive review on all the present metalloenzymes due to their number. Therefore, in this work the attention is focused on two metalloenzyme families: human Carbonic anhydrases (hCAs), involved in several kinds of diseases according to the isoform examined, and Tyrsosinases, which catalyze the rate-limiting steps in melanin production. Indeed, the PhD thesis presented here is articulated in two parts. Part I deals with two subsets of hCAs, specifically, hCAs V (Chapter 1), with a major attention on hCA VA which configures as anti – obesity target, and hCA IX and XII (Chapter 2) which are established anti – cancer targets, especially in the context of hypoxic tumors. Part II concerns Tyrosinase inhibition, focusing on the inhibition of two isoenzymes: mushroom Tyrosinase (AbTYR, Chapter 4) and human Tyrosinase (hTYR, Chapter 5). For each of the three topics discussed the state of art is given (Section 1.1. and 1.2 of Chapter 1, Section 2.1. and 2.2 of Chapter 2, respectively for hCA VA, and hCA IX/XII and Chapter 3 for Tyrosinases), providing an overview on the structure, the catalysis and the general features required for the inhibition of the five enzymes examined. This is done in order to provide a proper understanding of our contribution to the three topics (Section 1.3; 2.3; Chapter 4 and Chapter 5) concerning the inhibitor design, made through in – silico techniques that span from homology modelling to docking, pharmacophore Virtual screening (VS) and Molecular dynamics (MD) simulations. As result, the computational workflows described in the four sections led to i) the discovery of 30 hCA VA inhibitors (VAME 1 – 30), out of which 20 were showing ki values below 100 nM and one of them (VAME 28) selectively inhibited hCA VA; ii) the identification of hot 4 – spot residues responsible for ligand selectivity towards hCA XII, starting from the retrospective analysis on hCA XII, IX – mimic and II of two in - house selective hCA XII inhibitors; iii) the identification and binding – mode depiction of potent AbTYR inhibitors (compounds 19p, 19s and 19t); iv) the discovery of a potent dual AbTYR/hTYR inhibitor (Compound 7) by means of comparative docking studies of two inhibitors showing potent inhibition of the single isoenzymes. Several collaborators were involved the three projects which are listed in Acknowledgements.