Yuzawa Satoshi
What I hope to achieve through my research is to establish a scientific technology that makes it possible to synthesize any compound, thereby making a significant contribution to the creation of a sustainable society. In particular, pharmaceuticals, if successfully developed, have the power to save many people at once, but its supply is unstable. Many pharmaceutical products are discontinued because the supply of raw materials cannot keep up with demand.
I want to solve such problems and build a system that can deliver sufficient quantities of medicines to those who need them in the future. While conventional chemical synthesis technology is superior in many respects, it still faces major challenges, such as its dependence on limited resources and the existence of compounds that are difficult to synthesize. That is why we hope to establish a new synthetic method that can efficiently utilize limited resources and lead to a stable supply of pharmaceuticals, industrial materials, and functional compounds.
The approach I am particularly interested in is bioproduction technology that utilizes enzymes derived from microorganisms. Enzymes can carry out chemical reactions under mild conditions and can be genetically engineered to enhance specific functions. Compared to conventional chemical processes, enzymes often do not require high temperatures, high pressure, or large amounts of organic solvents, making it possible to synthesize a wide range of compounds while minimizing environmental impact.
Especially, a group of enzymes called cytochrome P450 (P450) has the ability to catalyze a wide variety of chemical transformations, including oxidation reactions, and is showing increasing promise in such fields as drug synthesis and environmental remediation. However, because the activity and substrate specificity of P450s can be affected by small changes in their amino acid sequence, a great deal of trial and error was required to maximize their potential.
Therefore, I have adopted a method that combines machine learning and analysis of large-scale data to efficiently explore the relationship between sequence and function and predict promising mutation combinations. By repeating experiments and simulation results with feedback to the model, I believe we can approach areas that have been difficult to approach with conventional chemical synthesis. Ultimately, through the establishment of this bioproduction technology, we hope to build an industrial process that creates new compounds while using resources efficiently.
The central theme of this project is “AI-based search for enzymes that can catalyze non-natural reactions. Although a certain number of enzymes that synthesize compounds existing in nature already exist through a long evolutionary process, few enzymes that target so-called nonnatural compounds, such as drug candidates and functional molecules newly designed by humans, have been found.
Therefore, by evolving P450 to efficiently synthesize nonnatural compounds, we are opening up areas where high costs and large environmental burdens have been feared with conventional chemical methods. Specifically, we will establish a process to obtain P450 mutants with optimal reaction characteristics by building machine learning models utilizing large data sets, designing and predicting sequence mutations, and repeating experimental verification.
Through this research, I hope to create a world in which compounds that have been given up by conventional synthetic methods can be accessed, thereby laying the foundation for innovation in diverse industrial fields. In the future, I would like to contribute to the realization of a sustainable society by further understanding the catalytic functions of enzymes and developing nanocatalysts that mimic them.
Enzyme engineering with AI is a new field that has the potential to revolutionize the future of industry and drug production. However, research has just begun, and the investment in equipment, acquisition of gene sequences, and purchase of reagents necessary for validation experiments will cost not a few money. The laboratory to which I belong has just been established by Dr. Vavricka at the end of 2022, and although the number of members is small, we are discussing daily with high motivation and actively promoting the research project.
Your support will be used carefully as funds to accelerate these research activities. Specifically, I plan to use the funds to purchase promising gene sequences, to pay for travel expenses for conference presentations, and to improve experimental facilities to solidify the results of my research.
My vision is to build a society in which people who need medicines can receive them without difficulty in the future. I ask for your support and cooperation in creating a system that will enable us to produce as many compounds, including medicines, as needed while making wise use of limited resources. Through this project, we hope to exchange information and ideas with many people who aim for a sustainable society, and to open the way to the future by incorporating new knowledge.
We need better technologies to produce chemicals, pharmaceuticals, and other materials without polluting the environment. Bioengineering offers an excellent solution to produce the target materials we need with a low carbon footprint and without using harmful chemical processes. However, to biologically produce new chemicals, especially pharmaceuticals, it is essential to discover and design new enzymes that catalyze the necessary chemical transformations.
To accelerate the process of enzyme discovery and design, he has developed the first graph neural network that can predict enzyme activity directly from enzyme structural information. The ability to train his model with protein structural information is an important advance in enzyme prediction and directly reflects the fact that molecular structure is the foundation of molecular function. This project has great potential to discover and design new enzymes that can produce valuable materials without burdening the environment.
Enzymes are wonderful catalysts that accelerate chemical reactions more than one million times at room temperature and pressure, and have been used by humans for thousands of years to produce alcohol and fermented foods. However, there is a limit to the types of enzymes that can be used, and scientists and engineers around the world have expressed a desire for new enzymes with such functions.
Yuzawa's proposal aims to design and search for such new enzymes using AI, and I believe that his flexible thinking will create a revolutionary method that no one has come up with yet.
Enzyme reactions are expected to be a clean and efficient means of producing pharmaceuticals and agrochemicals, but natural enzymes (keyholes) react only with specific compounds (keys), which means they lack flexibility compared to chemical synthesis. We have high expectations for this research, which will realize the dream of life scientists to “create enzymes that reproduce arbitrary chemical reactions (new enzyme reactions)” as well as “create enzymes that adapt to arbitrary compounds” as needed by utilizing AI.
Date | Plans |
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July 2025 | Data acquisition |
September 2025 | Presented at a domestic academic conference |
November 2025 | Start writing the paper |
We will send you a thank you message by email.
This return implementation is scheduled for March 2025.
thank you message
return | scheduled date |
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お礼のメッセージ | March, 2025 |
25 supporters are supporting with this reward. (No quantity limit)
Your name will be published in research reports submitted to academic journals.
This return implementation is scheduled for March 2026.
Name published in research report / thank you message
return | scheduled date |
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研究報告レポートにお名前掲載 | March, 2026 |
お礼のメッセージ | March, 2025 |
14 supporters are supporting with this reward. (No quantity limit)
We invite you to a science cafe about this project! The event is scheduled to take place in June 2025, and will be held twice, in-person and online. I would like to talk to everyone about bioinformatics and enzymes, including my research content.
science cafe / thank you message / Name published in research report
return | scheduled date |
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サイエンスカフェ | June, 2025 |
お礼のメッセージ | March, 2025 |
研究報告レポートにお名前掲載 | March, 2026 |
12 supporters are supporting with this reward. (No quantity limit)
Acknowledgments will be included when submitting this research as a paper. We aim to publish in March 2026! There may be delays, but in that case we will share the situation in the activity report.
Name published in paper acknowledgments / thank you message / Name published in research report / science cafe
return | scheduled date |
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論文謝辞にお名前掲載 | March, 2026 |
お礼のメッセージ | March, 2025 |
研究報告レポートにお名前掲載 | March, 2026 |
サイエンスカフェ | June, 2025 |
5 supporters are supporting with this reward. (No quantity limit)
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thank you message
25
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Name published in research report and others
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supporters
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Science cafe and others
12
supporters
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(No quantity limit)
Name published in paper acknowledgments and others
5
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(No quantity limit)