In Silico Strategies To Identify Novel Dermatological Agents Targeting Elastase And Tyrosinase Enzymes

Skin disorders arise from dysregulation in the main molecular pathways responsible for maintaining the integrity of the extracellular matrix, pigmentation homeostasis, immune regulation, and cell transformation. Among the biological targets involved in these processes, elastase and tyrosinase play a key pathological role. Their overactivity contributes, respectively, to the deterioration of the extracellular matrix associated with skin aging and inflammation, and to the alteration of melanogenesis leading to hyperpigmentation. Consequently, the discovery of selective elastase and tyrosinase inhibitors represents a promising therapeutic strategy for the treatment of dermatological conditions. In recent years, computer-aided drug design (CADD) techniques have established themselves as powerful tools for simplifying the identification of effective compounds and accelerating the optimization of small bioactive molecules. By providing virtual screening of large compound libraries and rational design of new chemical patterns, CADD significantly reduces costs, trial times, and failure rates in new drug discovery. This doctoral research project focused on the computational exploration of these two enzyme targets, with the aim of identifying new inhibitory chemotypes with potential dermopharmaceutical applications. Additionally, the training period at Farmacia Marra srl. allowed me the opportunity to evaluate commercially available formulations, offering a practical perspective to complement the theoretical framework. The opening chapters provide an overview of CADD methodologies and summarize the structural, biological, and therapeutic relevance of elastase and tyrosinase, along with the current landscape of commercialized inhibitors. (Chapters 1 and 2). In the subsequent chapters, my experimental studies on the enzyme elastase (Case study 1) and on tyrosinase (Case study 2) are described, which led to the identification of novel inhibitors. Case study 1 focuses on the identification of new non-peptide elastase inhibitors. The first part reports on the research work accomplished during an experience at the University of Chemistry and Technology, Prague, Czech Republic, under the supervision of Prof. Andrea Brancale. A combination of structure-based drug modelling, alanine scanning, molecular docking, and molecular dynamics simulations guided the design and prioritization of candidate molecules. The selected compounds were synthesized, and their biological activity was assessed in collaboration with the research group of Prof. Antonella Fais (University of Cagliari), leading to the identification of promising structures. Furthermore, collaboration with the research group of Prof. Domenico Trombetta (University of Messina) enabled the evaluation of natural extracts as elastase inhibitors. (Chapter 3) Case study 2 focuses on the rational development of new tyrosinase inhibitors. Several series of compounds were designed and evaluated computationally to determine their binding affinity and interaction profile. Subsequent biological validation, performed in collaboration with the research groups of Prof. Antonella Fais (University of Cagliari), Prof. Scheuermann, Jörg (Institute of Pharmaceutical Sciences, ETH Zürich), and Prof. Maria Paola Germanò (University of Messina), confirmed the inhibitory activity against Agaricus bisporus tyrosinase and human tyrosinase. The antioxidant activity of the most promising derivatives was also evaluated. Furthermore, collaboration with Prof. Paola Bonaccorsi's group (University of Messina) has enabled the evaluation of derivatives that incorporate a well-established tyrosinase inhibitor pharmacophore conjugated to fluorophores, with the aim of studying their dual potential as therapeutic agents and imaging probes. (Chapter 4) Overall, this PhD thesis combines computational chemistry and experimental validation to promote the discovery of new modulators of enzymes relevant to dermatology, laying the basis for future optimization towards effective treatments for skin disorders.