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Computational Biophysics (Ryuhei Harada) Lab
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A lab that uses computation to uncover how biomolecules such as proteins move.
AboutAbout the lab
Revealing how biomolecules function through computational science
The Harada Lab studies how biomolecules such as proteins function, using computational science including molecular dynamics.
While many labs in the College of Biological Sciences deal with subjects ranging from cells to ecosystems, this lab targets smaller molecules such as proteins, nucleic acids, and lipids.
Unusually for the college, the lab does not conduct experiments and carries out its research using supercomputers.
Students with no prior knowledge of computers or molecular simulation are supported so that they can learn from the basics.
Key terms
- Molecular dynamics
- A simulation method that calculates the interactions among many atoms and obtains atomic coordinates as time-series data
- Supercomputer
- A large computer that processes large-scale calculations at high speed. The lab uses the one at the Center for Computational Sciences
- Machine learning
- A method that lets a computer learn rules from data. In this lab, it is used to predict and analyze molecular dynamics time-series data
ResearchResearch themes
The Harada Lab clarifies how biomolecules such as proteins function through computational science, including molecular dynamics. From structural biology, epigenetics, the cytoskeleton, photosynthesis, and neuroscience to the development of computational methods, students can study the biological phenomena and biomolecules they are interested in using computational approaches.
*Illustrative imageThe protein folding problem
A protein's shape is largely determined by its amino acid sequence, but clarifying how it folds into the correct structure is an extremely difficult problem. The lab develops efficient computational methods itself and tries to solve the problem in a realistic amount of time.
*Illustrative imageMolecular dynamics and machine learning
The lab applies machine learning to time-series data of atomic coordinates obtained from molecular dynamics calculations. It predicts long time series from short data, and uses anomaly detection to capture infrequent structural changes.
*Illustrative imageDeveloping new computational methods
Structural changes related to protein function take milliseconds to seconds, but only a few microseconds can be calculated. The lab therefore devises computational approaches to follow structural changes efficiently, and develops such methods alongside its simulations.
MembersFaculty
The members of the Harada Lab consist of faculty, and doctoral, master's, and undergraduate students.As of 2025
- Associate ProfessorRyuhei Harada
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: “Anton supercomputer” Matt Simmons / CC BY 2.0 (cropped)
- The protein folding problem: “Platform for protein crystallography and X-ray scattering” Evgeny Pelevin / CC BY 4.0 (cropped)
- Molecular dynamics and machine learning: “Dutch national supercomputer "Huygens"” Dennis van Zuijlekom / CC BY-SA 2.0 (cropped)
- Developing new computational methods: “The catalyst high performance computing (HPC)” ENERGY.GOV / Public domain (cropped)
- Related lab (Molecular Phylogenetics Lab): “Darwin tree” Charles Darwin / Public domain (cropped)
- Related lab (Chiba Lab): “Stain for SDS-PAGE gel” Andra MIhali from New York City, United States / CC BY-SA 2.0 (cropped)
- Related lab (Structural Biology Lab): “Using X-ray diffractometer to solve the 3D structure of membrane proteins of the flagellar system ( )” OIST from Onna Village, Japan / CC BY 2.0 (cropped)
- Related lab (Biodiversity Informatics (Nozomi Ytow) Lab): “CSIRO ScienceImage 1332 Pinned Insect Specimens” division, CSIRO / CC BY 3.0 (cropped)
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