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Sekijima Lab
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The lab uses computer science to create new drugs and materials.
AboutAbout the lab
Making drugs with the power of computers.
The Sekijima Lab aims to create drugs and materials using computer science methods such as machine learning and supercomputing.
These fields are called cheminformatics and materials informatics.
Using deep learning and molecular simulation, the lab searches for drug candidates based on the three-dimensional structures of disease-related proteins and compounds, and develops methods to generate compounds that did not exist before.
Students in the lab come from a wide range of backgrounds, including computer science, applied mathematics, organic synthesis, and pharmaceutical sciences.
Key terms
- Cheminformatics
- A research field that handles chemical information with computers to efficiently search for candidate drugs and materials.
- Molecular simulation
- A method that reproduces the motion of atoms and molecules on a computer to study, for example, how a protein and a compound bind.
- Mixed reality (MR)
- A technology that overlays computer-generated 3D objects on the view in front of you. Also called Mixed Reality or MR.
ResearchResearch themes
The lab aims to develop platforms for smart drug discovery and materials development using machine learning and large-scale computer simulation, and to apply them. It uses a wide range of computer science technologies, including deep learning, generative models, supercomputers, and virtual reality.
*Illustrative imageImproving compounds step by step
The lab developed MERMAID, a method that modifies drug-candidate compounds along an evaluation function. Rather than building compounds from scratch, it starts from hit compounds and edits the string representation of molecules using reinforcement learning and deep learning.
*Illustrative imageGenerating compounds tailored to target proteins
Previous generative models aimed at properties such as molecular weight and lipophilicity, and did not take the all-important target protein into account. Using readily available amino acid sequence information as a condition, the lab generates compounds with a conditional variational autoencoder.
*Illustrative imageFinding hit compounds with smart drug discovery
By combining docking simulation and molecular dynamics simulation on supercomputers with in vitro experiments, the lab found four hit compounds that inhibit the activity of spermidine synthase.
*Illustrative imageViewing 3D structures in mixed reality
The lab believes that viewing the three-dimensional structures of proteins and compounds in 3D, rather than on a 2D screen, is more useful for considering interactions and compound optimization. It developed HoloMol, a system that displays 3D structures on a mixed reality device and can share them with remote locations.
MembersFaculty
The Sekijima Lab consists of faculty, researchers, and PhD, master's, and undergraduate students.As of 2022
- Associate ProfessorMasakazu SekijimaPublications ↗
- Project LecturerNobuaki YasuoPublications ↗
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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: “Bedaquiline 3D” Jovan.gec / CC BY-SA 4.0 (cropped)
- Improving compounds step by step: “Caffeine molecule ball from xtal (1)” Jynto / CC0 (cropped)
- Generating compounds tailored to target proteins: “Amobarbital ball-and-stick” MarinaVladivostok / CC0 (cropped)
- Finding hit compounds with smart drug discovery: “Aripiprazole bound to Dopamine D2 Receptor docking model” EpsilonVisuals / CC BY-SA 4.0 (cropped)
- Viewing 3D structures in mixed reality: “ISS-46 Scott Kelly with HoloLens in the Destiny lab” NASA / Public domain (cropped)
- Related lab (Masahito Ohue Lab): “Protein Crystal Structure of the human Sec23a-24a heterodimer, complexed with the SNARE protein Sec22b PDB 2nup” Emw / CC BY-SA 3.0 (cropped)
- Related lab (Akiyama Lab): “Protein filament” Opabinia Regalis / CC BY-SA 3.0 (cropped)
- Related lab (Takashi Ishida Lab): “4xhe pinnatoxin pentamer” Opabinia regalis / CC BY-SA 4.0 (cropped)
- Related lab (Saito Lab): “Utah teapot surreal” Dhatfield / CC BY-SA 3.0 (cropped)
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