“Towards Rational Molecular Design for Reduced Chronic Aquatic Toxicity” Voutchkova-Kostal, A. M.; Kostal, J.; Connors, K. A.; Brooks, B. W.; Anastas, P. T.; Zimmerman, J. B. Green Chem. 2012, 14, 1001-1008. DOI: 10.1039/C2GC16385C
As a synthetic chemist with little (actually zero) training in toxicology, it’s difficult for me to imagine how to design safer chemicals at the start of a project. I can avoid nasty solvents, use safer reagents, but when designing a new molecule I haven’t a clue of its potential toxicological impact. This is frustrating and as the authors of the above paper in Green Chemistry point out, “with the growing number of new chemicals being introduced into the market, it is not economically or ethically reasonable to assume that each can undergo systematic toxicological testing […]”. Thus, possessing a set of easy-to-implement synthetic guidelines to reduce the toxicity of a synthetic target during the design stage, while maintaining (or better yet, augmenting) its function, is of high importance.
Recently, the Zimmerman group reported on guidelines for reducing acute aquatic toxicity and have now extended their work to chronic aquatic toxicity. This is an important next step because chronic toxicity studies are necessarily longer-term (and thus more resource intensive) than acute toxicity studies.
In the current work, they explore the relationships between 38 physicochemical properties of 865 chemicals with chronic aquatic toxicity toward three model organisms: the Japanese medaka, a cladoceran, and a green algae. The 38 properties include, for example, molecular weight, number of freely rotatable bonds, aqueous solubility, and number of hydrogen bond donors and acceptors. They first measure the correlation of single properties to toxicity and find the highest correlation (as judged by the correlation coefficient; see table below) between toxicity and the octanol-water partition coefficient (log Po-w) for both the medaka (O. latipes) and cladoceran D. magna), with a less strong correlation for the algae (P. subcapitata). Additionally, the authors found a correlation between toxicity and the HOMO/LUMO gap (ΔE) for the algae. High correlations also exist between toxicity and the energies of the frontier molecular orbitals of the compounds (HOMO/LUMO).
These correlations are not too surprising, as the log Po-w relates to how well a given molecule can partition from water to an organic medium (or across lipophilic biological membranes into an organism). The frontier molecular orbital energies, of course, relate to how reactive a molecule is (for example, a compound with a low-lying LUMO would be expected to react with nucleophilic amino acid side chains).
They next perform a multivariate analysis and find that for a 2-property model, the two most important properties are log Po-w and either ΔE or the HOMO energy for all three species. Interestingly, for a 3 property model, the third property depends on the species. For the medaka and cladoceran, the third most important property for toxicity prediction is the number of H-bond acceptors, while for the algae it is the LUMO energy.
To see how the four key properties impacted aquatic toxicity, the researchers explore their distribution (see the box plot below) against compounds grouped according to the EPA’s three levels of toxicity concern (high in red, medium in black and low in green). Consistent with the correlations described above, both log Po-w and ΔE exhibit strong trends, with lower partition coefficients and larger ΔEs corresponding to lower levels of toxicity concern. In contrast, the HOMO and LUMO energies show a much less significant trend, suggesting ΔE is a better guideline than either the HOMO or LUMO energies when designing a molecule.
More powerfully, scatter plots of log Po-w vs ΔE provide threshold values for chronic aquatic toxicity. For all three species, the compounds of low chronic toxicity lie within one quadrant of the plot with boundary values of log Po-w of less than 2 and ΔE values greater than 9 eV. For the three species, applying these guidelines eliminates 90 % of the investigated compounds classified in the highest category of concern by the EPA!
Lastly, the authors explore the outliers – for example, highly chronically toxic compounds that are wrongly classified by these new guidelines as ‘safe’. The discussion of the outliers is very detailed and worth reading (shown below are the results for the D. magna 504 hr assay), but one compound that caught my eye was hydrazine.
The guidelines place hydrazine in the ‘safe’ region of the plot, whereas the EPA level of concern for this compound is high (hydrazine is a known carcinogen in mammals). As the authors point out, there are a few possible explanations for any incorrect classification: (i) the computed log Po-w or ΔE values are incorrect, (ii) the experimental toxicity threshold is inaccurate, or (iii) the design guidelines are inadequate for certain modes of action (MOAs) of certain toxicants. In the case of hydrazine, according to the authors, the MOAs are poorly understood in aquatic organisms making the last explanation potentially the correct one. They also note that the acute toxicity of hydrazine makes measuring chronic toxicity difficult.
These guidelines are obviously very exciting and easy to use (I think I could handle measuring log Po-w and computing ΔE!). Going forward, I’m interested to see how the authors change the guidelines to include the outliers. In particular, I’m excited to see how they incorporate the biodegradation products of the compounds and whether that impacts the number of outliers using their guidelines.