Fractional nuclear charge approach to isolated anion densities for Hirshfeld partitioning methods

Atoms in molecules methods that rely on reference promolecular densities typically require that one define, or otherwise determine, the densities of unbound atomic anions. Whereas the isolated atomic polyanions are always physically and computationally unbound, monoanions can be either physically bound but computationally unbound (like the oxygen anion at the Hartree-Fock level of theory), or physically unbound but computationally bound (like the nitrogen anion usingmany DFT methods with a basis set including diffuse functions). Depending on the level of theory and basis set used, the densities of negatively charged atomic ions can decay very slowly and even be nonmonotonically decreasing. These delocalized anionic densities induce ill-behaved atomic properties for compounds containing highly reduced atoms. To treat the problem of unphysical proatom densities in iterative Hirshfeld methods, we compute the smallest (typically fractional) nuclear charge to bind all electrons, called the effective nuclear charge Z(A)(eff) of an atom A. When Z(A)(eff) > Z(A) at a given level of theory, the scaled density corresponding to the effective nuclear charge is used as the negatively charged proatom density. This novel approach dramatically improves the computational robustness of the iterative Hirshfeld partitioning scheme

Recent Progress in Density Functional Methodology for Biomolecular Modeling

International audienceDensity 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)