TY - JOUR
T1 - Development of an Analysis Toolkit, AnalysisFMO, to Visualize Interaction Energies Generated by Fragment Molecular Orbital Calculations
AU - Tokiwa, Takaki
AU - Nakano, Shogo
AU - Yamamoto, Yuta
AU - Ishikawa, Takeshi
AU - Ito, Sohei
AU - Sladek, Vladimir
AU - Fukuzawa, Kaori
AU - Mochizuki, Yuji
AU - Tokiwa, Hiroaki
AU - Misaizu, Fuminori
AU - Shigeta, Yasuteru
N1 - Funding Information:
H.T. acknowledges the Rikkyo SFR project, 2014−2016, and the MEXT Supported Program for the Strategic Research Foundation at Private Universities, 2013−2018. V.S. thanks project VEGA 2/0035/16. The computations in this work were performed using the Research Center for Computational Science, Okazaki, Japan; the Center for Computational Sciences (CCS) at University of Tsukuba, Japan; and the facilities of the Supercomputer Center, the Institute for Solid State Physics, The University of Tokyo, Japan.
Funding Information:
⬢These authors contributed equally to this work. Funding This project was supported by the Japan Science and Technology Agency (JST) and the National Bioscience Database Center (NBDC). This project also was supported by JSPS KAKENHI grant number 16K18688, 17KT0010, and 18K14391. Notes The authors declare no competing financial interest. RbAnalysisFMO and the PyMOL plugins use Ruby and Python (including NumPy), respectively. This software is freely available at http://dfns.u-shizuoka-ken.ac.jp/labs/ proeng/custom20.html/.
Publisher Copyright:
© 2018 American Chemical Society.
PY - 2019/1/28
Y1 - 2019/1/28
N2 - 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.
AB - 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.
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U2 - 10.1021/acs.jcim.8b00649
DO - 10.1021/acs.jcim.8b00649
M3 - Article
C2 - 30517784
AN - SCOPUS:85059408415
SN - 1549-9596
VL - 59
SP - 25
EP - 30
JO - Journal of Chemical Information and Modeling
JF - Journal of Chemical Information and Modeling
IS - 1
ER -