posted on 2018-12-05, 00:00authored byTakaki Tokiwa, Shogo Nakano, Yuta Yamamoto, Takeshi Ishikawa, Sohei Ito, Vladimir Sladek, Kaori Fukuzawa, Yuji Mochizuki, Hiroaki Tokiwa, Fuminori Misaizu, Yasuteru Shigeta
In modern praxis,
a knowledge-driven design of pharmaceutical compounds
relies heavily on protein structure data. Nonetheless, quantification
of the interaction between protein and ligand is of great importance
in the theoretical evaluation of the ability of a pharmaceutical compound
to comply with certain expectations. The FMO (fragment molecular orbital)
method is handy in this regard. However, the physical complexity and
the number of the interactions within a protein–ligand complex
renders analysis of the results somewhat complicated. This situation
prompted us to develop the 3D-visualization of interaction energies
in protein (3D-VIEP) method; the toolkit AnalysisFMO, which should
enable a more efficient and convenient workflow with FMO data generated
by quantum-chemical packages such as GAMESS, PAICS, and ABINIT-MP.
AnalysisFMO consists of two separate units, RbAnalysisFMO, and the
PyMOL plugins. The former can extract interfragment interaction energies
(IFIEs) or pair interaction energies (PIEs) from the FMO output files
generated by the aforementioned quantum-chemical packages. The PyMOL
plugins enable visualization of IFIEs or PIEs in the protein structure
in PyMOL. We demonstrate the use of this tool on a lectin protein
from Burkholderia cenocepacia in which
FMO analysis revealed the existence of a new interaction between Gly84
and fucose. Moreover, we found that second-shell interactions are
crucial in forming the sugar binding site. In the case of bilirubin
oxidase from Myrothecium verrucaria (MvBO), we predict that interactions between Asp105 and three His
residues (His401, His403, and His136) are essential for optimally
positioning the His residues to coordinate Cu atoms to form one Type
2 and two Type 3 Cu ions.