Computational approach to aluminum biochemistry and development of new chelation strategies

Resumen

Aluminum is the third most abundant element on Earth¿s crust, and the first metal. Nevertheless, its complex chemical features, mainly its low solubility, have prevented its utilization within the biological cycles of living organisms, leading to a not fully understood paradox from an evolutionary point of view1.In the last Century, the acidification of the environment due to the human intervention, has allowed Al(III) to become one of the main components of our daily lives. It has become so highly (bio)available that some authors state that we are currently living ¿The Aluminum Age¿2.As a consequence of such massive human exposure to this non-essential metal ion, detrimental neurological effects have been reported, raising concerns about the potential toxic role of aluminum in the biological environment3. In particular, the link between the presence of Al(III) in neuronal tissues and the development of Alzheimer¿s Disease is a matter of debate and controversy, despite all the many efforts made in order to unveil the pathogenic effects of Al(III)4,5.In this rather controversial context, the quest for reliable chelating agents that can efficiently remove Al(III) from the biological environment has attracted much interest in the last years6. The goal of chelation therapy is the development of chelating agents with a high affinity and specificity for a given metal ion, lack of toxicity and strong competitiveness with respect to endogenous metal ions and chelators. However, due to the complex chemistry of aluminum, a suitable and specific Al(III) chelating agent has not yet been found6.Accordingly, we believe that a computational approach to aluminum biochemistry, by using state-of-the-art computational tools and in collaboration with experimental partners, would allow for a strong help towards a clearer understanding of the role and the behavior of Al(III) in the human organism.In this sense, the present PhD project has covered three main areas: i) chelation therapy and development of new chelation strategies. ii) Understanding of the potential toxic role of aluminum in the biological environment, considering different bioligands. iii) Validation and calibration of the accuracy of theoretical methods (mainly DFT) with respect to available experimental data and other high level benchmarks, in order to improve the reliability of our computational approach. Moreover, the work was carried out in close collaboration with experimental partners from the University of Cagliari (Italy).A wide range of methods have been used for that purpose, such as cluster-continuum approaches atthe DFT level of theory, thermodynamics of metal-ligand complexes in solution, chemical bondanalysis, QM/MM simulations. The availability and fine understanding of experimental data hasallowed the setup of a reliable computational protocol suitable for the investigation of Low-Molecular-Mass (LMM) aluminum chelators. Additionally, other methodologies were used duringthe secondment at SmartLigs®, such as classic MD simulations, docking and MonteCarlo-basedconformational sampling techniques.All results achieved so far are contained in the publications list along with the scientific production(e.g. conferences, meetings etc.), and will be presented and discussed in this Thesis dissertation.