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Development of an Analysis Toolkit, AnalysisFMO, to Visualize Interaction Energies Generated by Fragment Molecular Orbital Calculations.

Takaki TokiwaShogo NakanoYuta YamamotoTakeshi IshikawaSohei ItoVladimir SladekKaori FukuzawaYuji MochizukiHiroaki TokiwaFuminori MisaizuYasuteru Shigeta
Published in: Journal of chemical information and modeling (2018)
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.
Keyphrases
  • protein protein
  • density functional theory
  • healthcare
  • binding protein
  • mental health
  • small molecule
  • single cell
  • deep learning
  • data analysis