Academic crowdfunding platform "academist"
JP | EN
Share Tweet
SUCCESS
Yuzawa Satoshi
Tokyo University of Agriculture and Technology、fourth-year student
Pledged: 401,900 JPY
Target Amount: 400,000 JPY
Funded
100 %
Supporters
56
Days left
Closed
Support period closed
Profile

Yuzawa Satoshi

Hello, I am Satoshi Yuzawa, a fourth-year student in the Department of Biotechnology, Faculty of Engineering, Tokyo University of Agriculture and Technology. I have been conducting integrated research using data science on enzymes that can be used in the synthesis of pharmaceuticals. I became deeply interested in pharmaceuticals when I met an acquaintance who was suffering from a mental illness and saw him recover successfully after taking a therapeutic drug, and I strongly realized that “ pharmaceuticals can make a big contribution to changing people's lives”. In order to build a society that can deliver necessary compounds while making effective use of limited resources, we have launched this project. in the new laboratory established by Professor Vavricka at the end of 2022, all members, though small in number, are engaged in multifaceted discussions and are working aggressively to develop AI-driven enzymes.

What do you hope to accomplish through your research?

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.

What approach are you trying to implement?

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.

What is the research theme you will be conducting in this project?

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.

Why we need your support

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.

Recommender's comment

Vavricka, Christopher J
Associate Professor, Tokyo University of Agriculture and Technology

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.

Kazunori Ikebukuro
Professor, Department of Biofunctional Science, Faculty of Engineering, Tokyo University of Agriculture and Technology

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.

Hiromasa Kiyota
Professor, Faculty of Environmental and Life Science, Okayama University

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.

Project timeline

Date Plans
July 2025 Data acquisition
September 2025 Presented at a domestic academic conference
November 2025 Start writing the paper

Pledge Rewards

You may provide additional support in addition to the amount of your return. No sales tax will be charged on the additional support.
1,100 JPY tax included
Featured : thank you message

We will send you a thank you message by email.
This return implementation is scheduled for March 2025.

return details

thank you message

scheduled date details
return scheduled date
お礼のメッセージ March, 2025

25 supporters are supporting with this reward. (No quantity limit)

5,500 JPY tax included
Featured : Name published in research report

Your name will be published in research reports submitted to academic journals.
This return implementation is scheduled for March 2026.

return details

Name published in research report / thank you message

scheduled date details
return scheduled date
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)

11,000 JPY tax included
Featured : Science cafe

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.

return details

science cafe / thank you message / Name published in research report

scheduled date details
return scheduled date
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)

33,000 JPY tax included
Featured : Name published in paper acknowledgments

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.

return details

Name published in paper acknowledgments / thank you message / Name published in research report / science cafe

scheduled date details
return scheduled date
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)

Supporters will be charged the funding amount only if the project reaches the funding goal (JPY 400,000) before 17:00 on March 12, 2025 (JST: GMT+9).
Payment options
Credit cards, bank transfer, convenience store payment, Pay-easy and PayPal are available
Additional Support
You may provide additional support in addition to the amount of your return. No sales tax will be charged on the additional support.
Securities

SSL encryption communication is used in this Web site, and the informations filled out are safely transmitted.

1,100 JPY(tax included)

thank you message

25 supporters back
(No quantity limit)

5,500 JPY(tax included)

Name published in research report and others

14 supporters back
(No quantity limit)

11,000 JPY(tax included)

Science cafe and others

12 supporters back
(No quantity limit)

33,000 JPY(tax included)

Name published in paper acknowledgments and others

5 supporters back
(No quantity limit)

Featured projects
Copyright © academist, Inc. All rights Reserved.