Molecular descriptors as proxies for the modeling of the materials and their environmental impact

Abstract

For the prediction of material's properties and of interaction of molecules with the surroundings, one needs to know their properties. Usually, the molecular properties are revealed through experimental measurements. It can be a tedious, time-consuming, and costly work. On the other hand, computational chemistry readily generates a huge number of data which can provide various molecular descriptors. These can be various observable properties (bond lengths and angles, dipole moments, etc...), but also the unobservable properties (partial atomic charges, electronegativity, various latent variables ....). There is an urgent need to develop accurate and economical screening tools that predict potential toxicity and environmental burden of various chemicals. Equally important is the design of safer alternatives. Molecular modeling methods offer one of several complementary approaches to evaluate the risk to human health and the environment as a result of exposure to environmental chemicals. These tools can streamline the hazard assessment process by simulating possible modes of action and providing virtual screening tools that can help prioritize bioassay requirements. Tailoring these strategies to the particular challenges presented by environmental chemical interactions make them even more effective. Advances in the fields of computational chemistry and molecular toxicology in recent decades allow the development of predictive models that inform the design of molecules with reduced potential to be toxic to humans or to the environment. As an example we present the novel methodology for the computational evaluation of pKa values of various organic bases, based on calculation of partial atomic charges by a simple semiempirical QM method.