Drug Discovery and Pharmacogenomics
In silico methods for identifying, screening, and optimizing drug candidates including virtual screening, QSAR modeling, and pharmacogenomics
Overview
Computational drug discovery accelerates the identification of therapeutic candidates by using simulations, statistical models, and databases to prioritize compounds before experimental testing.
Key Topics
- Virtual screening and molecular docking
- Quantitative structure-activity relationship (QSAR) modeling
- Pharmacophore modeling
- Drug-target interaction prediction
- ADMET property prediction (absorption, distribution, metabolism, excretion, toxicity)
- Repurposing approved drugs for new indications
Applications
- Antibacterial and antiviral drug design
- Kinase inhibitor development
- Natural product-based drug discovery
- Precision oncology target identification
Faculty in This Area (6)
Assistant Professor
Chompoonik Kanchanabanca, Ph.D.
Department of Microbiology, Faculty of Science
Associate Professor
Natapol Pornputtapong, Pharm.D., Ph.D.
Department of Biochemistry and Microbiology, Faculty of Pharmaceutical Sciences
Assistant Professor
Pajaree Chariyavilaskul, M.D., Ph.D.
Department of Pharmacology, Faculty of Medicine
Lecturer
Pasrawin Taechawattananant, Ph.D.
Professor
Taninee Sahakitrungruang, M.D., Ph.D.
Department of Pediatrics, Faculty of Medicine
Associate Professor
Thanyada Rungrotmongkol, Ph.D.
Department of Biochemistry, Faculty of Science