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Theoretical Drug Discovery Lab
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The lab combines computational science with organic chemistry and biochemistry to develop drugs in a rational way.
AboutAbout the lab
Making drug discovery efficient through computation and theory.
The Theoretical Drug Discovery Lab combines computational science, organic chemistry, and biochemistry to conduct research on developing drugs rationally and efficiently.
Drug development is said to have a low success rate and to require a great deal of cost and time.
The lab focuses in particular on developing drugs for cancer and infectious diseases, and also works on antibody therapeutics.
Its goal is to become a successful example of university-based drug discovery.
Key terms
- Molecular dynamics
- A simulation that calculates the motion of atoms and molecules on a computer to reproduce how proteins and other molecules move
- Lead compound
- A compound selected as a drug candidate that serves as the starting point for further structural optimization
- Antibody therapeutics
- A drug that uses the mechanism of antibodies produced by the body's immune system, engineered to act only on a target molecule involved in a disease
ResearchResearch themes
The lab takes on the challenge of developing drugs rationally and efficiently by integrating computational science, organic chemistry, and biochemistry. It focuses in particular on developing drugs for cancer and infectious diseases.
*Illustrative imageStructural Analysis of Disease-Related Proteins
The lab determines protein structures by X-ray crystallography and cryo-electron microscopy, and analyzes how the proteins function using methods such as molecular dynamics simulations. It is also developing theory-based techniques for obtaining high-quality protein crystals.
*Illustrative imageDesigning Drug Candidate Molecules with Computational Science
The lab runs a cycle of compound design, organic synthesis, activity evaluation, and structural analysis within the lab to search for lead compounds with stronger activity. Drawing on its experience in computational science and in protein expression and purification, it also works on developing molecules for antibody therapeutics.
*Illustrative imageDeveloping Software to Support Drug Discovery
The lab has developed its own software that predicts how drug candidate molecules bind to proteins. It is now developing a program that uses machine learning to predict protein-protein interactions.
*Illustrative imageDeveloping Treatments for Rare Cancers
The lab focuses on rare cancers, which have few patients and for which molecular targeted therapy has been slow to be introduced. It is developing treatments for brain tumors and neuroblastoma (a childhood cancer), as well as biomarkers that could lead to early detection of cancer.
MembersFaculty
The members of the Theoretical Drug Discovery Lab consist of faculty, doctoral, master's, and undergraduate students, and research students.
- Associate ProfessorTyuji Hoshino
VoicesStudent voices
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “CSIRO ScienceImage 1788 Molecular model of a protein” division, CSIRO / CC BY 3.0 (cropped)
- Structural Analysis of Disease-Related Proteins: “Platform for protein crystallography and X-ray scattering” Evgeny Pelevin / CC BY 4.0 (cropped)
- Designing Drug Candidate Molecules with Computational Science: “8 Śląski Festiwal Nauki, MCK, Katowice,, , 1256” Krzysztof Popławski / CC BY-SA 4.0 (cropped)
- Developing Software to Support Drug Discovery: “CERN Server 03” Florian Hirzinger - www.fh-ap.com / CC BY-SA 3.0 (cropped)
- Developing Treatments for Rare Cancers: “Disposable Pipette Tips in Laboratory Tip Boxes 02” Gannu03 / CC BY-SA 4.0 (cropped)
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