Application of computer simulation to soil bioremediation

Soil organic matter (SOM) is a key part in the composition of soil, playing a crucial role in the transport and absorption of plant nutrients as well as pollutants or other xenobiotic compounds. Given the increasing environmental pollution, development and implementation of effective soil remediation strategies is of utmost importance. Various engineering approaches have been applied based on different types of physical and chemical treatments. In particular, soil bioremediation, taking advantage of utilization of biological agents for pollutant degradation and removal, presents an appealing, cost-effective alternative and for that reason has gained a growing interest in recent years. Numerous enzymes, primarily of bacterial and fungal origin, have a great remediation potential. Peroxidases, laccases and oxygenases are only a few examples of enzymes involved in detoxification of various hazardous substances, including lignin, phenolic species, other organic compounds, etc. However, their efficiency greatly varies depending on the conditions at which they are applied and may be significantly lower at polluted sites than in laboratory conditions, greatly impeding their usability. SOM is largely made up of humic substances, such as humic acids and fulvic acids. We hypothesize that different conditions and compositions of SOM result in microscopically distinct local environments, directly affecting structure and dynamics of enzymes involved in remediation processes on the one hand and the distribution of pollutants on the other. Computer models of molecular systems allow us to zoom in at the microscopic level and to interpret the experimental findings in terms of atomistic interactions and motions, and are therefore ideally suited tools for addressing this problem. We have recently developed an automated online tool Vienna Soil-Organic-Matter Modeler (VSOMM) for generating physics-based SOM models. We will use the modeler to create various SOM models corresponding to realistic, experimentally available SOM samples with varying compositions and use molecular dynamics simulations in combination with free energy calculations to characterize the SOM models at the atomistic level. We aim (1) to study the effect of conditions and SOM composition in combination with the level, type and position of oxidative modifications on structure and dynamics of bioremediation enzymes, (2) to explore how sorption properties of selected pollutant compounds depend on the composition and conditions of SOM.

The chemistry of soil is very complex. It consists of all kinds of minerals, organic molecules, microbes, and waste from animal and plant products. In this project, we have created computer models of soil organic matter, because these can give insight into the molecular composition of soil components. Soil organic matter (SOM) plays a key part in the composition of soil, playing a crucial role in the transport and absorption of plant nutrients as well as pollutants or other xenobiotic compounds. Given the increasing environmental pollution, development and implementation of effective soil remediation strategies is of utmost importance. Various engineering approaches have been applied based on different types of physical and chemical treatments. In particular, soil bioremediation, taking advantage of utilization of biological agents for pollutant degradation and removal, presents an appealing, cost-effective alternative and for that reason has gained a growing interest in recent years. However, the question remains how proteins that may be used in bioremediation can function in the harsh environment the soil represents. Computer models of molecular systems allow us to zoom in at the microscopic level and to interpret the experimental findings in terms of atomistic interactions and motions, and are therefore ideally suited tools for answering questions about the interaction of pollutants and proteins with the soil. For this reason, we have developed an automated online tool "Vienna Soil-Organic-Matter Modeler" (VSOMM) to generate physics-based SOM models. We have used the modeler to create various SOM models corresponding to realistic, experimentally available SOM samples with varying compositions and have used molecular dynamics simulations in combination with free energy calculations to characterize the SOM models at the atomistic level. From this we could learn how the composition of SOM influences its macroscopic properties, and what parts of the SOM molecules interact most favorably with pollutants, proteins and mineral surfaces. This information supports our research to understand how soil works and how we can protect it.