Space-filling models arise out of a desire to represent molecules in ways that reflect the electronic surfaces that molecules present, that dictate how they interact, one with another (or with surfaces, or macromolecules such as enzymes, etc.). Crystallographic data are the starting point for understanding static molecular structure, and these data contain the information rigorously required to generate space-filling representations (e.g., see
these crystallographic models); most often, however, crystallographers present the locations of atoms derived from crystallography via "
thermal ellipsoids" whose cut-off parameters are set for convenience both to show the atom locations (with
anisotropies), and to allow representation of the covalent bonds or other interactions between atoms as lines. In short, for reasons of utility, crystallographic data historically have appeared in presentations closer to ball-and-stick models. Hence, while crystallographic data contain the information to create space-filling models, it remained for individuals interested in modeling an effective static shape of a molecule, and the space it occupied, and the ways in which it might present a surface to another molecule, to develop the formalism shown above. In 1952, Robert Corey and Linus Pauling described accurate scale models of molecules which they had built at
Caltech. , SO2, showing the
electrostatic potential surface, computed for the molecule using the
Spartan software suite of
computational chemistry tools. It is shaded from blue for
electropositive areas to red for
electronegative areas. The surface was generated by calculating the energy of interaction of a spherical point positive charge (e.g., a proton, H+,) with the molecule's atoms and bonding electrons, in a series of discrete computational steps. Here, the electrostatic surface emphasizes the electron deficiency of the sulfur atom, suggesting interactions in which it might engage, and
chemical reactions it might undergo. , a
protein, the
cell membrane-spanning
β2 adrenoreceptor, a
G protein-coupled receptor, in this image, viewed as if looking down onto the extracellular surface. The
electrostatic potential surface was applied to a model with atom positions determined by crystallography (
PDB code 2RH1); the electrostatic surface was computed using
Adaptive Poisson-Boltzmann Solver (APBS) freeware. It is again shaded blue for
electropositive areas to red for
electronegative areas. Somewhat apparent, in stick representation in yellow, red and blue, in a groove at the top of the
receptor, is a small molecule ligand
bound to it, the agent
carazolol, a partial
inverse agonist which, through this binding,
antagonizes binding of the normal ligand, the
neurotransmitter/hormone
epinephrine. In response to
binding epinephrine, this receptor, in conjunction with an
L-type calcium channel, mediates physiologic responses such as
smooth muscle relaxation and
bronchodilation. All of such binding interactions and the function of the receptor in
signal transduction are mediated by electrostatic effects, and in modern structure work they are often studied using similar space filling models. In 1965,
Walter L. Koltun designed and patented a simplified system with molded plastic atoms of various
colours, which were joined by specially designed snap connectors; this simpler system accomplished essentially the same ends as the Corey-Pauling system, and allowed for the development of the models as a popular way of working with molecules in training and research environments. Such colour-coded, bond length-defined, van der Waals-type space-filling models are now commonly known as CPK models, after these three developers of the specific concept. In modern research efforts, attention returned to use of data-rich crystallographic models in combination with traditional and new computational methods to provide space-filling models of molecules, both simple and complex, where added information such as which portions of the surface of the molecule were readily
accessible to solvent, or how the electrostatic characteristics of a space-filling representation—which in the CPK case is almost fully left to the imagination—could be added to the visual models created. The two closing images give examples of the latter type of calculation and representation, and its utility. == See also ==