FMOe: Preprocessing and Visualizing Package of the Fragment Molecular Orbital Method for Molecular Operating Environment and Its Applications in Covalent Ligand and Metalloprotein Analyses
The fragment molecular orbital (FMO) method is an efficient quantum chemical calculation technique for large biomolecules, dividing each into smaller fragments and providing interfragment interaction energies (IFIEs) that support our understanding of molecular recognition. The <i>ab initio</i> fragment MO method (ABINIT-MP), an FMO processing program, can automatically divide typical proteins and nucleic acids. In contrast, small molecules such as ligands and heterosystems must be manually divided. Thus, we developed a graphical user interface to easily handle such manual fragmentation as a library for the Molecular Operating Environment (MOE) that preprocesses and visualizes FMO calculations. We demonstrated fragmentation with IFIE analyses for the two following cases: (1) covalent cysteine-ligand bonding inside the SARS-CoV-2 main protease (M<sup>pro</sup>) and nirmatrelvir (Paxlovid) complex and (2) the metal coordination inside a zinc-bound cyclic peptide. IFIE analysis successfully identified the key amino acid residues for the molecular recognition of nirmatrelvir with M<sup>pro</sup> and the details of their interactions (e.g., hydrogen bonds and CH/π interactions) via ligand fragmentation of functional group units. In metalloproteins, we found an efficient and accurate scheme for the fragmentation of Zn<sup>2+</sup> ions with four histidines coordinated to the ion. FMOe simplifies manual fragmentation, allowing users to experiment with various fragmentation patterns and perform in-depth IFIE analysis with high accuracy. In the future, our findings will provide valuable insight into complicated cases, such as ligand fragmentation in modality drug discovery, especially for medium-sized molecules and metalloprotein fragmentation around metals.
Authors
- Hirotomo Moriwaki (ORCID: https://orcid.org/0000-0002-3122-8580)
- Teruki Honma (ORCID: https://orcid.org/0000-0003-3761-9504)
- Kikuko Kamisaka (ORCID: https://orcid.org/0000-0002-1215-2525)
- Chiduru Watanabe (ORCID: https://orcid.org/0000-0002-0742-3896)
- Kaori Fukuzawa (ORCID: https://orcid.org/0000-0001-5357-8250)
- Yoshio Okiyama
- Yusuke Kawashima (ORCID: https://orcid.org/0000-0001-8465-6848)
Institutions
- Hoshi University (JP)
- Japan Science and Technology Agency (JP)
- RIKEN Center for Biosystems Dynamics Research (JP)
- Kobe University (JP)
- Ebara (Japan) (JP)
- The University of Osaka (JP)
Publication Details
- Journal
- Journal of Chemical Information and Modeling
- Published
- 2024-09-05
- DOI
- https://doi.org/10.1021/acs.jcim.4c01169
- Citations
- 7
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 2.53
Funders
- Japan Agency for Medical Research and Development
- RIKEN
- Precursory Research for Embryonic Science and Technology