Background, Aim and Scope:
Metal ions generally share the ability/tendency to interact with biological material by forming complexes, except possibly for the heavy alkali metals K, Rb and Cs. This is unrelated to the metals being either essential for sustaining life and its reproduction, apparently insignificant for biology though perhaps undergoing bioconcentration or outright toxic even at low admission levels. Yet, those different kinds of metal-biomass interactions should in some way depend on properties describing coordination chemistries of these very metals; whereas both ubiquitously essential metals and others being sometimes used in biology should share these properties in numeric terms, it can be anticipated that they will be distinguished from non-essential and/or toxic ones. These above features include all bioconcentration, the involvement of metal ions such as Zn, Mg, Cu, Fe etc. in biocatalysis as crucial components of metalloenzymes and the introduction of a certain set of essential metals common to (almost) all living beings (K, Mg, Mo, Mn, Fe, Cu and Zn) which occurred probably very early in biological evolution by “natural selection of the chemical elements” (more exactly speaking, of the metallome).
Main Features:
For this purpose, a method is outlined to calculate a pair of parameters (called c and x) which describe properties of the corresponding metal ion from electrochemical ligand properties (redox potential shifts) and complex stabilities by linear regression; ligand and metal ion properties together control complex stabilities. Since neither the gross composition of biological matter nor the set of principal metabolic substrates vary wildly, it is but these parameters for metal ions which control their possible (functional) roles in biomass. Thus, after producing the parameters from complex stability constants, a mapping of biological functions or effects vs. the parameters c and x is undertaken.
Results:
These maps show some “window of essentiality”, a small, contrived range/area of c and x parameters in which essential metal ions gather almost exclusively. c and x thus control the possibility of a metal ion becoming essential by their influencing details of metal-substrate- or (in cases of catalytic activities) metal-product interactions. Exceptions are not known to be involved in biocatalysis anyhow.
Discussion:
Effects of ligands secreted from e.g. tree roots or agaric mycelia to the soil on the respective modes (selectivities) of metal bioconcentration can be calculated by the equation giving complex stability constants, with obvious ramifications for a thorough, systematic interpretation of biomonitoring data. Eventually alterations of C-, N- and P-compounds during chemical evolution are investigated – which converted f.e. CH4 or CO2, N2 and other non-ligands to amino acids etc. behaving as efficient chelating ligands: did they cause metal ions to accumulate in what was going to become biological matter and was there a selectivity, a positive bias in favour of now-essential metals (see above) in this process? Though there was no complete selectivity of this kind, neither a RNA world in which early ribozymes effected most of biocatalysis, nor a paleoatmosphere containing substantial amounts of CO could have paved way to the present biochemistry and metallome.
Conclusions:
This way of reasoning provides a causal account for abundance distributions earlier described in the Biological System of Elements (BSE; MARKERT 1994; FRÄNZLE & MARKERT 2000, 2002). There is a pronounced cxhange from chemical evolution where but few transformations depended on metal ion catalysis to biology.
Perspectives:
The application of this numerical approach can be used for modified, weighted evaluation of biomonitoring analytical data, likewise for prediction of bioconcentration hazards due to a manifold of metal ions including organometallic ones. This is relevant in ecotoxicology and biomonitoring. In combining apoproteins or peptides synthesized from scratch for purposes of catalyzing certain transformations, the map and numerical approaches might prove useful for selection of central ions which are even more efficient than the 'natural' ones, like is Co2+ in many Zn enzymes.
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