Cheminformatics
My favorite programming language is Ruby as it is easy
to learn yet powerful.
I use lots of softwares to do my research; Chemistry related open source softwares including OpenBabel, CDK (and rcdk), mayachemtools, RDKit, and smi23d (3d conformation generation). Statistical software R and Spotfire (this is rather for visualization). Proprietary molecular modeling tools including Pipeline Pilot, Discovery Studio, and Sybyl. Descriptor calculation and ADME, toxicity prediction tool PreADMET, which is developed and commercialized by my institution, BMDRC.
For hit generation, my team utilizes many virtual screening technologies like pharmacophore generation, fingerprint-based similarity search, and protein-ligand docking. As BMDRC has no facility for synthetic works, we collaborate with many medicinal chemists and biologists.
Once getting experimental results, I usually do lots of QSAR research for hit-to-lead or lead optimization, a traditional medicinal chemistry research theme. As well, I made several pharmacokinetic parameters (hERG inhibition, volume of distribution, bioavailability, half life, etc) prediction system for internal use and support of collaborators.
To organize and manage various sorts of data, my team developed a chemical information management system called ChIPS2, which provide easy web interface for archiving, retrieving, and searching chemical-related data.
I use lots of softwares to do my research; Chemistry related open source softwares including OpenBabel, CDK (and rcdk), mayachemtools, RDKit, and smi23d (3d conformation generation). Statistical software R and Spotfire (this is rather for visualization). Proprietary molecular modeling tools including Pipeline Pilot, Discovery Studio, and Sybyl. Descriptor calculation and ADME, toxicity prediction tool PreADMET, which is developed and commercialized by my institution, BMDRC.
For hit generation, my team utilizes many virtual screening technologies like pharmacophore generation, fingerprint-based similarity search, and protein-ligand docking. As BMDRC has no facility for synthetic works, we collaborate with many medicinal chemists and biologists.
Once getting experimental results, I usually do lots of QSAR research for hit-to-lead or lead optimization, a traditional medicinal chemistry research theme. As well, I made several pharmacokinetic parameters (hERG inhibition, volume of distribution, bioavailability, half life, etc) prediction system for internal use and support of collaborators.
To organize and manage various sorts of data, my team developed a chemical information management system called ChIPS2, which provide easy web interface for archiving, retrieving, and searching chemical-related data.
Drug Discovery Projects
Drug discovery projects I involved include ;
In these projects, my job was mainly hit identification using virtual screening and support for lead optimization with QSAR research.
Recently, I started to join a new project for metabolism prediction, especially the induction of CYP450 by drug molecules.
- Neuropathic pain killer (sigma1 protein antagonists)
- Avian flu drug : IMPDH inhibitor, Polymerase inhibitor, Neuramidase inhibitor, etc.
- Anti-malarial compounds (Artemisinin derivatives)
- Anti-diabetes : natural products and synthetic libraries (PTP1B inhibitors)
- Anti-cancer agents
In these projects, my job was mainly hit identification using virtual screening and support for lead optimization with QSAR research.
Recently, I started to join a new project for metabolism prediction, especially the induction of CYP450 by drug molecules.
Natural Product Research
I had some experiences in separation of active compound
from plant extraction, structure elucidation, and
derivative synthesis during my Ph. D. course. And now,
I'm involved in a project supported by a company in
South Korea.
In this project, I'm trying to do a natural product research in a accelerated mode; fast separation, fast chemical structure elucidation, prediction of bioactivities from only chemical structure, confirmation using high-thoughput bioassay. When successfully completed, I think the resulting library (with single compounds) will be a highly valuable source of not only many researche areas but also commercial interests.
In this project, I'm trying to do a natural product research in a accelerated mode; fast separation, fast chemical structure elucidation, prediction of bioactivities from only chemical structure, confirmation using high-thoughput bioassay. When successfully completed, I think the resulting library (with single compounds) will be a highly valuable source of not only many researche areas but also commercial interests.