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Fragment molecular orbital calculations for biomolecules
Institution:1. School of Pharmacy and Pharmaceutical Sciences, Hoshi University, 2-4-41 Ebara, Shinagawa, Tokyo, 142-8501, Japan;2. Department of Biomolecular Engineering, Graduate School of Engineering, Tohoku University, 6-6-11 Aoba, Aramaki, Aoba-ku, Sendai, 980-8579, Japan;3. Graduate School of System Informatics, Department of Computational Science, Kobe University, 1-1 Rokkodai, Nada-ku, Kobe, 657-8501, Japan;1. RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan;2. RIKEN Center for Biosystems Dynamics Research, 1-6-5 Minatojima-Minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan;3. Artificial Intelligence Center for Health and Biomedical Research, National Institutes of Biomedical Innovation, Health, and Nutrition 7-6-8, Saito-Asagi, Ibaraki, Osaka, 567-0085, Japan;4. RIKEN Center for Computational Science, 7-1-26 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan;1. Departments of Molecular Physiology and Biomedical Engineering, University of Virginia, Box 800886, Charlottesville, VA, 22908, USA;2. Department of Cell and Molecular Biology, Uppsala University, Box 256, Uppsala 75105, Sweden;1. Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA;2. Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
Abstract:Exploring biomolecule behavior, such as proteins and nucleic acids, using quantum mechanical theory can identify many life science phenomena from first principles. Fragment molecular orbital (FMO) calculations of whole single particles of biomolecules can determine the electronic state of the interior and surface of molecules and explore molecular recognition mechanisms based on intermolecular and intramolecular interactions. In this review, we summarized the current state of FMO calculations in drug discovery, virology, and structural biology, as well as recent developments from data science.
Keywords:Fragment molecular orbital (FMO) method  Computational structural biology  Interaction energy analysis  Machine learning
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