Abstract
Density Functional Theory (DFT) has become the workhorse of applied computational chemistry. DFT has grown in a number of different directions depending on the applications concerned. In this chapter, we provide a broad review of a number of DFT and DFT-based methods, having in mind the accurate description of biological systems and processes. These range from pure "cluster" DFT studies of the structure, properties, and reactions of biochemical species (such as enzymatic catalysts) using either straight DFT or dispersion-corrected functionals (DFT-D), to Born-Oppenheimer-DFT dynamics of systems containing up to a hundred atoms or more (such as glycero-lipids), to hybrid DFT/Molecular Mechanical Molecular Dynamics methods which include protein and solvent environments (for enzymes or ion channels, for example), to constrained-DFT (working within the Marcus framework for electron-transfer reactions), to Interpretational-DFT (which provides the interpretational benefits of the Kohn-Sham DFT methodology).