Hirotomo Moriwaki

ORCID: 0000-0002-3122-8580
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About
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Research Areas
  • Computational Drug Discovery Methods
  • Protein Structure and Dynamics
  • Molecular spectroscopy and chirality
  • Enzyme Structure and Function
  • Machine Learning in Materials Science
  • Genomics, phytochemicals, and oxidative stress
  • Bioinformatics and Genomic Networks
  • Light effects on plants
  • Protein Kinase Regulation and GTPase Signaling
  • Anomaly Detection Techniques and Applications
  • Mass Spectrometry Techniques and Applications
  • Chemistry and Chemical Engineering
  • Phosphodiesterase function and regulation
  • Statistical Methods in Clinical Trials
  • Video Surveillance and Tracking Methods
  • Human Pose and Action Recognition
  • Medical Imaging Techniques and Applications
  • Nitrogen and Sulfur Effects on Brassica
  • Pharmaceutical studies and practices
  • Radioactive Decay and Measurement Techniques
  • RNA and protein synthesis mechanisms
  • PI3K/AKT/mTOR signaling in cancer
  • Inorganic and Organometallic Chemistry
  • Radiopharmaceutical Chemistry and Applications
  • Synthesis and biological activity

RIKEN Center for Biosystems Dynamics Research
2021-2024

Osaka University
1990-2019

Kindai University
2016

Molecular descriptors are widely employed to present molecular characteristics in cheminformatics. Various molecular-descriptor-calculation software programs have been developed. However, users of those must contend with several issues, including bugs, insufficient update frequencies, and licensing constraints. To address these we propose Mordred, a developed descriptor-calculation application that can calculate more than 1800 two- three-dimensional descriptors. It is freely available via...

10.1186/s13321-018-0258-y article EN cc-by Journal of Cheminformatics 2018-02-06

We developed the world's first web-based public database for storage, management, and sharing of fragment molecular orbital (FMO) calculation data sets describing complex interactions between biomacromolecules, named FMO Database (https://drugdesign.riken.jp/FMODB/). Each entry in contains relevant background information on how was compiled as well total energy each system interfragment interaction (IFIE) pair decomposition analysis (PIEDA) values. Currently, more than 13 600 sets, a...

10.1021/acs.jcim.0c01062 article EN cc-by-nc-nd Journal of Chemical Information and Modeling 2021-01-29

Abstract Several basic leucine zipper (bZIP) transcription factors have accessory motifs in their DNA-binding domains, such as the CNC motif of family or EHR small Maf (sMaf) proteins. proteins heterodimerize with sMaf to recognize CNC–sMaf binding DNA elements (CsMBEs) competition homodimers, but functional role remains elusive. In this study, we report crystal structures Nrf2/NFE2L2, a protein regulating anti-stress transcriptional responses, complex MafG and CsMBE. The restricts...

10.1093/nar/gkac1102 article EN cc-by Nucleic Acids Research 2022-11-02

Abstract Fragment molecular orbital (FMO) method is a powerful computational tool for structure‐based drug design, in which protein–ligand interactions can be described by the inter‐fragment interaction energy (IFIE) and its pair decomposition analysis (PIEDA). Here, we introduced dynamically averaged (DA) FMO‐based approach dynamics simulations were used to generate multiple complex structures FMO calculations. To assess this approach, examined correlation between experimental binding free...

10.1002/jcc.26940 article EN Journal of Computational Chemistry 2022-06-09

The fragment molecular orbital (FMO) method is an efficient quantum chemical calculation technique for large biomolecules, dividing each into smaller fragments and providing inter-fragment interaction energies (IFIEs) that support our understanding of recognition. ab initio MO program (ABINIT-MP), FMO processing software, can automatically divide typical proteins nucleic acids. In contrast, small molecules such as ligands hetero systems must be manually divided. Thus, we developed a...

10.26434/chemrxiv-2024-2xk5n preprint EN cc-by-nc-nd 2024-02-08

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 recognition.

10.1021/acs.jcim.4c01169 article EN Journal of Chemical Information and Modeling 2024-09-05

In drug discovery, the prediction of activity and absorption, distribution, metabolism, excretion, toxicity parameters is one most important approaches in determining which compound to synthesize next. recent years, methods based on deep learning as well non-deep have been established, a number applications discovery reported by various companies organizations. this research, we performed using in-house assay data for several hundred kinases compared discussed results. We found that accuracy...

10.1021/acsomega.2c00664 article EN cc-by-nc-nd ACS Omega 2022-05-23

Quantitative structure-activity relationship (QSAR) techniques, especially those that possess three-dimensional attributes, such as the comparative molecular field analysis (CoMFA), are frequently used in modern-day drug design and other related research domains. However, requirement for accurate alignment of compounds CoMFA increases difficulties encountered its use. This has led to development several techniques-such VolSurf, Grid-independent descriptors (GRIND), Anchor-GRIND-which do not...

10.1248/cpb.c18-00757 article EN Chemical and Pharmaceutical Bulletin 2019-04-30

The fragment molecular orbital (FMO) method is an efficient quantum chemical calculation technique for large biomolecules, dividing each into smaller fragments and providing inter-fragment interaction energies (IFIEs) that support our understanding of recognition. ab initio MO program (ABINIT-MP), FMO processing software, can automatically divide typical proteins nucleic acids. In contrast, small molecules such as ligands hetero systems must be manually divided. Thus, we developed a...

10.26434/chemrxiv-2024-2xk5n-v2 preprint EN 2024-07-08
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