{"id":2091,"date":"2026-04-10T00:07:16","date_gmt":"2026-04-10T00:07:16","guid":{"rendered":"https:\/\/www.europesays.com\/ai\/2091\/"},"modified":"2026-04-10T00:07:16","modified_gmt":"2026-04-10T00:07:16","slug":"ai-designed-proteins-built-from-scratch-can-recognize-specific-compounds","status":"publish","type":"post","link":"https:\/\/www.europesays.com\/ai\/2091\/","title":{"rendered":"AI-designed proteins built from scratch can recognize specific compounds"},"content":{"rendered":"

\"Researchers<\/p>\n

Design and characterization of a cortisol-dependent heterodimer. Credit: Gyu Rie Lee et al<\/p>\n

Professor Gyu Rie Lee of the Department of Biological Sciences successfully designed artificial proteins that selectively recognize specific compounds using AI through joint research with Professor David Baker. The research, published<\/a> in the journal Nature Communications, is characterized by using AI to design proteins that recognize specific compounds from scratch (de novo) and implementing them as functional biosensors.<\/p>\n

While the conventional approach mainly involved searching for natural proteins or modifying some of their functions, this research is highly significant in that it “custom-built” proteins with desired functions through AI-based design and even completed experimental verification.<\/p>\n

In particular, the research team successfully designed a protein that selectively recognizes the stress hormone cortisol<\/a> and implemented an AI-designed biosensor based on it. This is evaluated as a case that extends beyond protein design to actual measurable sensor technology, solving the long-standing challenge of small-molecule recognition in the field of protein design.<\/p>\n

\"researchers\"<\/p>\n

Credit: Unsplash\/CC0 Public Domain<\/p>\n

These research results have applications in fields including disease diagnosis, new drug development and environmental monitoring. The technology can precisely detect biomarkers in the blood<\/a> to diagnose diseases early and contribute to the development of targeted therapies through the design of proteins that selectively recognize specific molecules.<\/p>\n

Furthermore, it is expected that the implementation of customized biosensor technology will become possible, such as real-time monitoring<\/a> of air and water quality through the development of sensors that detect environmental pollutants.<\/p>\n

Designing new proteins (de novo proteins) that recognize compounds has been considered a challenge in the field of protein design for a long time because it requires precise calculations at the atomic level. The research team developed an AI model<\/a> that precisely reflects protein-ligand interactions and successfully designed binding proteins using it.<\/p>\n

As a result, artificial binding proteins were designed for six types of compounds, including metabolites and small-molecule drugs, and their functions were verified through experiments. In particular, a cortisol biosensor was developed by designing a chemical-induced dimer based on a new protein that binds with cortisol.<\/p>\n

A provisional patent for the relevant design technology has been filed in the United States.<\/p>\n

Professor Gyu Rie Lee stated, “This research experimentally proves that AI can be used to design proteins that precisely recognize specific compounds,” and added, “We plan to expand this into protein design technology that can be utilized in various fields such as disease diagnosis, new drug development, and environmental monitoring in the future.”<\/p>\n

Professor Gyu Rie Lee of the KAIST Department of Biological Sciences participated in this research as the first author, and Professor David Baker as the corresponding author.<\/p>\n

Director Do-Heon Lee, a mentor professor of the AI-CRED Innovative Drug Research Group, said, “This achievement is a meaningful result derived through cooperation between InnoCORE researchers and a global scholar.<\/p>\n

“We will further strengthen our research capabilities based on active research collaboration with postdoctoral researchers recruited through the InnoCORE project to continue creating innovative results in the AI drug development and bio-fields.”<\/p>\n

The KAIST InnoCORE Research Group aims to accelerate AI-based scientific and technological innovation and promote global joint research by supporting top-tier domestic and international postdoctoral researchers to devote themselves to the development of AI convergence technology in a cutting-edge collective research environment.<\/p>\n

\t\t\t\t\t\t\t\t\t\t\t\t\t\tPublication details\t\t\t\t\t\t\t\t\t\t\t\t\t<\/p>\n

Gyu Rie Lee et al, Small-molecule binding and sensing with a designed protein family, Nature Communications (2026). DOI: 10.1038\/s41467-026-70953-8<\/a><\/p>\n

\t\t\t\t\t\t\t\t\t\t\t\tKey concepts
\n\t\t\t\t\t\t\t\t\t\t\t\tArtificial intelligence<\/a>\t\t\t\t\t\t\t\t\t\t\t<\/p>\n

\n\t\t\t\t\t\t\t\t\t\t\t\t\tProvided by
\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tThe Korea Advanced Institute of Science and Technology (KAIST)<\/a>
\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/p>\n

\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/p>\n

\n\t\t\t\t\t\t\t\t\t\t\t\tCitation:
\n\t\t\t\t\t\t\t\t\t\t\t\tAI-designed proteins built from scratch can recognize specific compounds (2026, April 9)
\n\t\t\t\t\t\t\t\t\t\t\t\tretrieved 9 April 2026
\n\t\t\t\t\t\t\t\t\t\t\t\tfrom https:\/\/phys.org\/news\/2026-04-ai-proteins-built-specific-compounds.html\n\t\t\t\t\t\t\t\t\t\t\t <\/p>\n

\n\t\t\t\t\t\t\t\t\t\t\t This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no
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