Distortion/Interaction Analysis in Explicit Surroundings

To investigate and understand interactions between molecules is one of the central challenges in chemistry. Such an understanding allows us to predict properties of molecules and develop theories explaining their characteristics. Computer simulations are extremely helpful in this regard, as they allow us to gain insights that are not possible even with elaborate experiments. Such simulations can be used to investigate interactions between molecules in detail. In particular, we can identify different factors that influence the interaction. For this we use so-called Energy Decomposition Methods. These methods allow us to break down the strength of the interaction into different, easy to understand, contributions. For example, we can determine how much the attraction between negatively and positively charged parts of different molecules contribute to the interaction, or how much the effect of the repulsion between negatively charged electrons of both molecules is. This allows us to understand the difference in properties of molecules in detail. A big limitation of these methods is that only interactions between two molecules can be investigated. However, many chemical reactions occur in solution. Here the interacting molecules are surrounded by countless solvent molecules, which influence the molecules of interest as well. Common Energy Decomposition methods ignore these solvent molecules. This can lead to highly simplified or sometimes even wrong insights. In this project we introduce a new method which allows us to include solvent molecules in our analysis. We can therefor investigate and understand the influence of the solvent on our system.

Chemical reactions are strongly influenced by their surroundings. In the real world, reactions almost never happen in isolation but take place in liquids, near solid surfaces, or inside large biological molecules such as proteins. This project developed new computer-based simulation methods that make it possible to study how these surroundings influence how fast a reaction occurs, how much energy it requires, and how efficiently it proceeds. The aim of the project was to create simulation tools that allow chemists to examine the role of the surrounding environment in chemical reactions in much greater detail than was previously possible. Instead of treating the environment as a simplified background effect, the methods developed in this project made it possible to directly include surrounding molecules in computer simulations and analyze their influence in a systematic way. The project was based on Energy Decomposition Analysis (EDA), a computational approach that helps explain chemical reactions by breaking down the total energy of a system into understandable parts. A central concept used in this project was distortion/interaction analysis, which is a specific form of EDA. A central concept used in this project was distortion/interaction analysis, which is a specific form of EDA. In simple terms, this approach looks separately at how hard it is to bend molecules into the shape needed for a reaction and how much energy is released when the reacting molecules come together. This separation provides an intuitive way to understand why some reactions are easy to initiate while others require more energy. One major outcome of the project was the development of a new method that extended distortion/interaction analysis to explicitly include solvent molecules in computer simulations. This meant that individual solvent molecules, such as water, were directly taken into account rather than being represented only as an average effect. As a result, the method allows researchers to study how liquids influence chemical reactions by stabilizing certain molecular arrangements or by changing preferred reaction pathways. In addition to liquid environments, the project achieved a further methodological advance that enabled the analysis of complex biological surroundings, such as proteins. Proteins consist of many different regions that can influence a chemical reaction in different ways. The methods developed in this project made it possible to assess how specific parts of a protein contributed to a reaction, allowing researchers to identify regions that promoted reactivity as well as regions that hindered it. Overall, the project established general computational frameworks for applying distortion/interaction analysis to chemical reactions in realistic environments. The simulation methods developed provide new tools for studying reactions in liquids and biological systems and lay the groundwork for the rational design of improved catalysts and functional molecules in the future.