What is the mechanism of formation of hydroxyaluminosilicates?

The formation of hydroxyaluminosilicates is integral to the biogeochemical cycles of aluminium and silicon. The unique inorganic chemistry which underlies their formation explains the non-essentiality in biota of both of these elements. However, the first steps in the formation of hydroxyaluminosilicates were hitherto only theoretical and plausibly only accessible in silico. Herein we have used computational chemistry to identify and define for the first time these unique and ultimately critically important reaction steps. We have used density-functional theory combined with solvent continuum models to confirm first, the nature of the reactants, an aluminium hydroxide dimer and silicic acid, second, the reaction products, two distinct hydroxyaluminosilicates A and B and finally, how these are the precursors to highly insoluble hydroxyaluminosilicates the role of which has been and continues to be to keep inimical aluminium out of biota.

Towards a model of non-equilibrium binding of metal ions in biological systems.

We have used a systems biology approach to address the hitherto insoluble problem of the quantitative analysis of non-equilibrium binding of aqueous metal ions by competitive ligands in heterogeneous media. To-date, the relative proportions of different metal complexes in aqueous media has only been modelled at chemical equilibrium and there are no quantitative analyses of the approach to equilibrium. While these models have improved our understanding of how metals are used in biological systems they cannot account for the influence of kinetic factors in metal binding, transport and fate. Here we have modelled the binding of aluminium, Al(III), in blood serum by the iron transport protein transferrin (Tf) as it is widely accepted that the biological fate of this non-essential metal is not adequately described by experiments, invitro and insilico, which have consistently demonstrated that at equilibrium 90% of serum Al(III) is bound by Tf. We have coined this paradox 'the blood-aluminium problem' and herein applied a systems biology approach which utilised well-found assumptions to pare away the complexities of the problem such that it was defined by a comparatively simple set of computational rules and, importantly, its solution assumed significant predictive capabilities. Here we show that our novel computational model successfully described the binding of Al(III) by Tf both at equilibrium and as equilibrium for Al(Tf) was approached. The model predicted significant non-equilibrium binding of Al by ligands in competition with Tf and, thereby, provided an explanation of why the distribution of Al(III) in the body cannot be adequately described by its binding and transport by Tf alone. Generically the model highlighted the significance of kinetic in addition to thermodynamic constraints in defining the fate of metal ions in biological systems.

A systems biology approach to the blood-aluminium problem: the application and testing of a computational model.

Transport and distribution of systemic aluminium are influenced by its interaction with blood. Current understanding is centred upon the role played by the iron transport protein transferrin which has been shown to bind up to 90% of serum total aluminium. We have coined what we have called the blood-aluminium problem which states that the proportion of serum aluminium which, at any one moment in time, is bound by transferrin is more heavily influenced by kinetic constraints than thermodynamic equilibria with the result that the role played by transferrin in the transport and distribution of aluminium is likely to have been over estimated. To begin to solve the blood-aluminium problem and therewith provide a numerical solution to the aforementioned kinetic constraints we have applied and tested a simple computational model of the time-dependency of a putative transferrin ligand (L) binding aluminium to form an Al-L complex with a probability of existence, K(E), between 0% (no complex) and 100% (complex will not dissociate). The model is based upon the principles of a lattice-gas automaton which when ran for K(E) in the range 0.1-98.0% demonstrated the emergence of complex behaviour which could be defined in the terms of a set of parameters (equilibrium value, E(V), equilibrium time, E(T), peak value, P(V), peak time, P(T), area under curve, AUC) the values of which varied in a predictable way with K(E). When K(E) was set to 98% the model predicted that ca. 90% of the total aluminium would be bound by transferrin within ca. 350 simulation timesteps. We have used a systems biology approach to develop a simple model of the time-dependency of the binding of aluminium by transferrin. To use this approach to begin to solve the blood-aluminium problem we shall need to increase the complexity of the model to better reflect the heterogeneity of a biological system such as the blood.