Predicting the environmental fate of novel munitions compounds requires data for the key properties that control contaminant fate, and the most common way to predict these properties is with empirical quantitative structure-activity relationships (QSARs). However, the traditional approach to QSAR development (calibration with experimental data) is challenging for new explosives compounds because of limitations to the availability of these materials. Some of the necessary environmental fate properties can be calculated directly from molecular structure theory, but reliable calculations of this type require considerable theoretical expertise and computational effort. To overcome this combination of challenges, we used a hybrid, partially in silico approach to QSAR development, where some of the calibration data (both the target variable and the descriptor variables) were calculated from molecular structure theory.
The technical approach of the project was divided into three objectives, corresponding to the three reaction pathways that contribute most to the overall fate of explosives in the environment. These include: (i) hydrolysis and associated elimination reactions, which are ubiquitous in water; (ii) nitro reduction by outer-sphere electron transfer, which are dominant in soils in sediments; and (iii) oxidation of the amino products soil minerals like manganese dioxide.
After extensive analysis of prior work, it was concluded that mechanism(s) of hydrolysis of the nitro aromatic energetic compounds, TNT and DNAN was not sufficiently advanced to support conventional QSAR development. The possible difference in mechanisms means that predicting the reaction mechanism for one based on the other may lead to unreliable predictions of environmental fate. This, along with uncertainties in the consistency of the calculated results with experimental values, presents a challenge for developing QSARs calibrated “in silico” that predict the hydrolysis behavior of the diverse range of energetic NACs. However, new experimental and computational results reported here provide insight into these mechanisms.
In contrast to the hydrolysis pathway, the effect of complexity in the nitro reduction pathway was effectively captured by contrasting two approaches: theory-based correlations to E1 and empirical correlations to ELUMO. The former provides a variety of insights into the fundamental processes controlling nitro reduction and the latter provides simple QSARs that should be useful for estimating relative reduction rates of nitro aromatic compounds. The models were calibrated and/or tested with a variety of model and actual energetic compounds, including TNT and DNAN. An overall conclusion of this aspect of the study is that most alternative energetic compounds will react by nitro reduction more slowly than TNT.
For oxidation of anilines a variety of QSARs were developed that represent a range of convenience and accuracy. The QSARs based on the most convenient descriptors (e.g., pKa) were less accurate and models based on the more specialized descriptors (e.g., E1ox) were the most accurate. Comparison of the model for MnO2 to other environmentally-relevant oxidants showed that the former was more sensitive to substituent effects than the latter.
The QSARs provided by this project can be used to predict the relative rates of major transformation processes that contribute to the environmental fate of energetic compounds. The models are flexible enough to handle some of the diverse molecular structures that are found in candidate compounds for new explosives. They are being integrated into models developed by others to predict the overall fate of energetic compounds.
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