Computational Ecotoxicology
Abstract: Human society has progressed by polluting ecosystems since the early industrial revolution. Thus, large amounts of harmful chemical compounds have been dispersed in soils, seas, groundwaters and wildlife habitats, leading to a persistent toxicological load on the environment. Pollution is a threat to biodiversity, to the health of ecosystems, and to all living organisms. Advances in environmental sciences are needed so that pollutants can be distinguished from harmless compounds. New methods could ease the enormous task of sorting out hazardous chemicals and also facilitate the study of existing problems in toxicology, which are often hampered by insufficient data. In our research, we apply several methods in computational chemistry to predict the interactions of various toxins, carcinogens, nanoparticles and xenobiotics with proteins, DNA, and cell membranes. Methods such as molecular dynamics simulations, docking, partition coefficient- and quantum chemistry-calculations are at the core of these studies, each having its role in facilitating the enormous task of transforming in vitro toxicology to in silico toxicology. We perform detailed studies of a few compounds and receptors as well as larger, more inclusive groups of compounds. We also outline approaches for drawing computational conclusions about the molecular behavior of various potential environmental toxins by modeling their interactions with DNA and proteins, and we use partition coefficients to describe their ability to permeate the cell membrane. Methods for studying the purification of pollutants from essential sources, such as water, are proposed. We also investigate the emerging problem of nanoparticle pollution and propose computational approaches to model the formation of nanoparticles from combustion emissions and the interactions of such particles with atmospheric components.
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