Libraries of Extremely Localized Molecular Orbitals. 3. Construction and Preliminary Assessment of the New Databanks

The fast and reliable determination
of wave functions and electron
densities of macromolecules has been one of the goals of theoretical
chemistry for a long time, and in this context, several linear scaling
techniques have been successfully devised over the years. Different
approaches have been adopted to tackle this problem, and one of them
exploits the fact that, according to the traditional chemical perception,
molecules can be seen as constituted of recurring units (e.g., functional
groups) with well-defined chemical features. This has led to the development
of methods in which the global wave functions or electron densities
of macromolecules are obtained by simply transferring density matrices
or fuzzy electron densities associated with molecular fragments. In
this context, we propose an alternative strategy that aims at quickly
reconstructing wave functions and electron densities of proteins through
the transfer of extremely localized molecular orbitals (ELMOs), which
are orbitals strictly localized on small molecular units and, for
this reason, easily transferable from molecule to molecule. To accomplish
this task we have constructed original libraries of ELMOs that cover
all the possible elementary fragments of the 20 natural amino acids
in all their possible protonation states and forms. Our preliminary
test calculations have shown that, compared to more traditional methods
of quantum chemistry, the transfers from the novel ELMO databanks
allow to obtain wave function and electron densities of large polypeptides
and proteins at a significantly reduced computational cost. Furthermore,
notwithstanding expected discrepancies, the obtained electron distributions
and electrostatic potentials are in very good agreement with those
obtained at Hartree–Fock and density functional theory (DFT)
levels. Therefore, the results encourage to use the new libraries
as alternatives to the popular pseudoatom-databases of crystallography
in the refinement of crystallographic structures of macromolecules.
In particular, in this context, we have already envisaged the coupling
of the ELMO databanks with the promising Hirshfeld atom refinement
technique to extend the applicability of the latter to very large
systems.