Dynamics and spectroscopical properties of biological photoreceptors
Modeling the catalytic site of enzymes
Molecular dynamics simulations of protein adsorption
Computation of spectroscopical properties of protein fragments
Density Functional Theory (DFT) is a powerful and elegant electronic structure method for calculating ground state properties of chemical systems. The main idea of DFT is to describe an interacting electronic system via its electron density instead of its many-body wave function. Although DFT is formally an exact theory, practical applications of DFT are based on approximations for the so-called exchange-correlation potential. The size and complexity of the systems that can be treated with DFT may range from a single atom to a complex system containing around 200 atoms including transition metals.
Thus, DFT provides, in combination with appropriate exchange-correlation potentials, accurate predictions for a variety of chemical properties at relatively low computational cost.
To accurately calculate vibrational spectra of cofactors embedded in a protein matrix, one has to combine DFT or quantum mechanics (QM) with a molecular mechanics (MM) force field into a hybrid QM/MM approach. This method treats the protein matrix with an empirical (MM) force field whereas the cofactor is typically treated with DFT. In this way, the effect of the protein matrix on the cofactors' vibrational spectrum is explicitly taken into account.
Molecular Dynamics Simulations
In molecular dynamics (MD) simulations, interactions between atoms and molecules and their resulting spatial movements are iteratively calculated and represented. Modeling complex systems with a large number of atoms relies mainly on force fields or semi-empirical methods, as the computational effort required to apply quantum mechanical methods (ab initio methods) would be too great. However, the steadily growing available computing power increasingly allows QM methods (ab initio MD) to be used even for medium-sized systems
Homology modeling, also known as comparative modeling of protein, refers to constructing an atomic-resolution model of the "target" protein from its amino acid sequence and an experimental three-dimensional structure of a related homologous protein (the "template"). Homology modeling relies on the identification of one or more known protein structures likely to resemble the structure of the query sequence, and on the production of an alignment that maps residues in the query sequence to residues in the template sequence.