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Masahito Ohue Lab
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A lab that takes on innovation in drug discovery and life sciences through the power of information science.
AboutAbout the lab
Life innovation through cutting-edge information science.
The Masahito Ohue Lab is a bioinformatics lab that works to accelerate life innovation.
The lab makes full use of AI, machine learning, big data analysis, supercomputing, and large-scale simulation.
It develops technologies that support predicting how proteins bind to each other and designing small-molecule, antibody, and peptide drugs.
Since its founding in 2020, the lab has carried out its research in collaboration with researchers in biology, chemistry, and medical, dental, and pharmaceutical sciences, as well as with companies, local governments, and patient groups.
Key terms
- Bioinformatics
- A research field that uses information science methods to interpret the large amounts of data obtained in life sciences
- Protein-protein interaction
- The connections by which proteins bind to each other and function in the body
- Binding free energy calculation
- A method of computationally estimating how strongly a candidate drug molecule binds to its intended target
NewsLab news
A master's student received the Best Presentation Award at the Information Processing Society of Japan
Associate Professor Masahito Ohue received the 10th Bioindustry Encouragement Award
A doctoral student received the Excellent Presentation Award at a research meeting on bioinformatics
A doctoral student received the Convention Excellence Award at the 88th National Convention of the Information Processing Society of Japan
A student team from the lab ranked 1st in the world in an international machine learning competition
ResearchResearch themes
The lab makes full use of AI, machine learning, big data analysis, supercomputing, and large-scale simulation to take on the creation of innovation in life sciences, drug discovery, and medicine. With information science as its core, it actively pursues joint research with researchers and companies in biology, chemistry, and medical, dental, and pharmaceutical sciences.
*Illustrative imagePredicting protein-protein interactions
The lab develops MEGADOCK, software that predicts how proteins bind to each other from their three-dimensional structures. Its distinguishing feature is that it can run a large number of predictions quickly using GPUs and many computers.
*Illustrative imageComputational support for small-molecule drug discovery
The lab develops computational technologies for designing small-molecule drugs. It works on methods for predicting the efficacy and activity of compounds, and on methods for performing binding free energy calculations accurately and efficiently.
*Illustrative imageComputational support for chemical synthesis
The lab develops computational technologies for the chemical synthesis used to actually make drugs and other products. It also works on generative models that design and optimize catalysts according to reaction conditions.
*Illustrative imageComputational support for antibody drug discovery
The lab develops computational technologies that support the design and manufacture of antibody drugs. It works on methods for predicting antibody properties from amino acid sequences and on methods for optimizing antibodies.
MembersFaculty
The Masahito Ohue Lab consists of faculty members, researchers, technical support staff, administrative staff, joint researchers from industry and other organizations, and doctoral, master's, and undergraduate students.As of 2026
- Associate ProfessorMasahito Masahito OhuePublications ↗
- Project Assistant ProfessorYuta KikuchiPublications ↗
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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: “Protein Crystal Structure of the human Sec23a-24a heterodimer, complexed with the SNARE protein Sec22b PDB 2nup” Emw / CC BY-SA 3.0 (cropped)
- Predicting protein-protein interactions: “Muscarinic receptor M2 coupled to protein G - 6OIK” Vcilleros / CC BY-SA 4.0 (cropped)
- Computational support for small-molecule drug discovery: “Thioridazine ball-and-stick model from xtal 1975” Fuse809 / CC BY-SA 4.0 (cropped)
- Computational support for chemical synthesis: “Lanthanide nanoparticle solvothermal synthesis apparatus” BekosVonNimmerland / CC0 (cropped)
- Computational support for antibody drug discovery: “Structure of the intact human IgG B12 antibody (PDB 1hzh)” Elisa Fadda / CC BY 4.0 (cropped)
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