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Electron Transfer in Carbo Nanotubes


Numerical computations are more and more being established as a third scientific approach besides theoretical and experimental works. Modern computers are able to accurately describe systems from a huge variety of fields, such as molecular biology, chemistry, cosmology, evolution, climate science and particle physics. Especially important for chemists and life scientists are quantum mechanical calculations of molecular electron structure and force field based molecular dynamics simulations to describe the conformational dynamics of biomolecules. Our group at the institute of physical chemistry is working on the continuous development of the Amber Molecular Modeling suite (http://www.ambermd.org/). The main focus here is the application of modern computational methods on two important questions: The electron structure and dynamics of large systems and the study of protein-ligand interactions for rational drug design.


Electron structure and dynamics of large systems

Carbo Nano Tube in Water The electrical properties of nanomaterials are of extraordinary interest for designers of new materials and miniaturized electronic components. Since such systems are difficult or expensive to study experimentally, computer simulations can contribute meaningfully to the elucidation of their properties. To model the electron structure of molecular assemblies containing thousands of atoms, like e.g. carbon nanotubes, simplified quantum mechanical methods, coupled to molecular dynamics simulations, can be employed. This allows for example the study of polarisation phenomena and the prediction of conductive properties.




Protein-ligand interactions and drug design and development

Ligand boundA central problem in the design of new drugs is to find novel compounds that efficiently and specifically target metabolic and signaling biochemical pathways. Since it is not feasible to synthesize every substance of interest, it is useful to study potential new ligands theoretically at first. Such "virtual screenings" aim at predicting the binding geometries and affinities of new molecules towards drug targets. Ideally, new improved inhibitors can be designed in silico through selective changes in molecular structure. These improved high-value lead molecules then serve as the starting point for the development of new medications.