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Next-Generation Biological Foundation Model, K-Fold
“Design a drug candidate that binds effectively to this protein.”
In response to such a request, AI predicts the protein’s three-dimensional structure, analyzes which compounds are most likely to bind to it, and designs promising drug candidates. KAIST researchers have developed K-Fold, the world's fastest Bio-AI model for protein structure prediction, which also supports drug candidate design.
KAIST (President Choongsik Bae) announced on August 28 that it had formed “Team KAIST” after being selected as the lead institution for the Ministry of Science and ICT’s “AI Specialized Foundation Model Project” and unveiled K-Fold, a next-generation Bio-AI model developed by Team KAIST.
Team KAIST is led by Professor Woo Youn Kim from the Department of Chemistry. His research group, together with Professors Sung Ju Hwang and Sungsoo Ahn's groups at the Kim Jaechul Graduate School of AI, developed the AI model. Professors Byung-Ha Oh, Ho Min Kim, and Gyuri Lee from the Department of Biological Sciences oversaw protein data construction and validation. HITS, a KAIST faculty startup, integrated K-Fold into HyperLab, its web-based AI research platform, enabling researchers to use the model in real-world research workflows. In addition, the Korea Pharmaceutical and Bio-Pharma Manufacturers Association (KPBMA) and the Korea Biotechnology Industry Organization (KoreaBIO) will lead efforts to raise awareness of K-Fold’s achievements and promote its use across the industry.
K-Fold’s defining capability is its ability to predict the binding between proteins and drug candidates—a critical step in drug discovery.
Drug development begins with determining the structure of a disease-related protein and identifying, among numerous compounds, those most likely to bind to the protein and produce the desired effect. K-Fold not only predicts a protein’s three-dimensional structure, but also calculates where and how a drug candidate is likely to bind, helping researchers identify promising candidates more quickly.
K-Fold goes beyond predicting the structure of a single protein. It can also predict the structures formed when different biomolecules interact, including protein–protein and protein–drug candidate complexes, as well as complexes involving DNA and RNA.
In the project’s stage evaluation conducted in March, its accuracy in predicting molecular complex structures was assessed as approaching that of AlphaFold3, developed by Google DeepMind. In an in-house performance evaluation conducted by the research team in August, K-Fold also outperformed existing global models in selected evaluation categories.
K-Fold demonstrated particularly strong performance in predicting how drug candidates bind to and act on key therapeutic targets, including G protein-coupled receptors (GPCRs) and kinases, which are major drug targets for cancer and other diseases. It also performed strongly in targeted protein degradation (TPD), an emerging drug discovery approach designed to directly eliminate disease-causing proteins.
K-Fold also significantly increased the speed of structure prediction. Conventional protein structure prediction models often require a complex preprocessing step that searches for and compares large amounts of data on similar proteins before calculating a structure. K-Fold applies a new approach that does not depend on this process, eliminating the need for preprocessing calculations and increasing structure prediction speeds by up to 25 times compared with existing models.
This means that researchers can evaluate more drug candidates within the same amount of time. By reducing the time and computing resources required for structure prediction, K-Fold can help rapidly identify the most promising compounds from a vast pool of candidates and narrow the selection for experimental validation.
“National competitiveness in the AI era depends on sovereign AI capabilities, which is the crucial ability to develop and deploy core technologies independently,” said KAIST President Choongsik Bae. “K-Fold is significant because it combines homegrown AI technology with biotechnology to challenge the world’s leading technologies and translates that capability into a service applicable to real-world drug discovery. KAIST will continue to strengthen Korea’s technological sovereignty in AI and its future competitiveness by advancing the convergence of foundational AI technologies with science and technology.”
The research team went beyond developing K-Fold as a standalone model, turning it into an AI research service that researchers can use through a conversational web-based interface.
K-Fold has been integrated into HyperLab, a multi-agent platform developed by HITS, a KAIST faculty startup. This allows researchers to use the model without having to build their own high-performance computing infrastructure or operate complex AI software.
For example, if a researcher asks the AI to “design an antibody that binds strongly to this protein,” it provides step-by-step support for predicting the protein’s structure, designing candidates with a high likelihood of binding, and computationally evaluating the results. Researchers can also ask it to “find a suitable peptide candidate for this cancer target protein.” In practical terms, instead of moving between multiple software tools to calculate structures and analyze results, researchers can simply state their research objective and have the AI carry out the necessary analyses and design tasks in sequence.
To support these capabilities, HyperLab incorporates approximately 120 computational tools and 160 specialized functions for structure prediction, drug design, and the analysis of life science data, including genomic and proteomic data. It also connects more than 100 specialized databases with a large-scale knowledge graph, enabling the platform to retrieve relevant scientific information and apply it to its analyses.
HyperLab aims to serve as an AI Co-Scientist that assists researchers throughout the research process by supporting the full workflow, from understanding a research question and selecting the appropriate tools to predicting structures, analyzing results, and iteratively improving designs.
Bio AI is emerging as a critical technology capable of reducing the time and cost required for drug discovery, driving intense competition among global technology companies and major research institutions in the United States, the United Kingdom, and China. The development of K-Fold is significant because it lays the foundation for sovereign bio AI by securing core bio AI technology domestically, rather than relying solely on overseas models, and making it available for real-world research.
The achievement was first presented at the 2026 Annual Meeting of the Korean Federation of Biomolecular Science, held on June 23, where Professor Woo Youn Kim from the KAIST Department of Chemistry delivered a keynote lecture titled “Generative Drug Design Powered by Agentic AI.”
“K-Fold was developed not to follow existing models, but to overcome the limitations of conventional approaches through a new AI architecture,” explained Professor Kim. “We will develop it into an AI-for-Science platform that makes world-class bio AI technology accessible to researchers everywhere.”
The Team KAIST consortium plans to release K-Fold free of charge. HyperLab will provide beta access to researchers in Korea and abroad, and gradually expand its commercial services by the end of this year.
Meanwhile, industry training on K-Fold is gaining momentum. An online session hosted by KoreaBIO on August 27 attracted 85 participants, while 118 have registered for KPBMA’s hybrid session on September 1. Designed primarily for researchers and practitioners at pharmaceutical and biotech companies, the training covers how to use K-Fold and presents case studies of its application to drug design. The initiative is intended to accelerate the adoption of sovereign bio-AI across the industry.
Related website: [HyperLab Co-Scientist] https://hyperlab.ai/features-co-scientist
K-Fold–HyperLab 3.0 Introduction Video: https://drive.google.com/file/d/1MxhZr-C3pQdIVn1EP44hQICj8G70is3_/view
This research was supported by the Ministry of Science and ICT (MSIT, PJT-25-100009)
2026.08.28 View 1107 -
KAIST Turns Once-Troublesome Protons into an Energy Storage Resource for Batteries
Batteries that use water-based electrolytes have a relatively low risk of fire and are inexpensive, but they have faced limitations in storing large amounts of energy. KAIST researchers have succeeded in using a reaction previously regarded as a “troublemaker” that degrades battery performance to store more energy instead. This achievement opens up the possibility of next-generation water-based batteries capable of storing more energy while charging and discharging rapidly.
KAIST (President Choongsik Bae) announced on the 19th that a research team led by Sarah S. Park from the Department of Chemistry has developed a new electrode material that sequentially stores zinc ions (Zn²⁺) and protons. The material is based on a two-dimensional conductive metal–organic framework (MOF), a structure in which metals and organic molecules are connected to form microscopic pores.
Aqueous zinc-ion batteries use water-based electrolytes. An electrolyte is a substance that allows ions to move inside a battery. Because aqueous zinc-ion batteries have a relatively low risk of fire, are inexpensive, and impose a low environmental burden, they are attracting attention as a next-generation option for large-scale energy storage systems (ESS).
Because zinc ions carry electrical charge, are divalent ions and slow movement inside electrodes, making it difficult to achieve both high capacity and fast charge–discharge performance at the same time. Protons, by contrast, are extremely small and can move very quickly, making them an ideal charge carrier. However, when too many protons enter an electrode, byproducts form on the electrode surface, interfering with the movement of zinc ions and lowering battery performance. For this reason, protons have traditionally been regarded as “troublemakers” that degrade battery performance, and research has focused on suppressing their reactions.
The research team took a different approach. Instead of suppressing proton reactions, the research team precisely controlled the order in which zinc ions and protons are stored so that both could be used for energy storage.
To accomplish this, they introduced amine functional groups into the micropores of a two-dimensional conductive MOF, designing the material so that it would react with protons only when a certain voltage was reached. By designing the amine functional groups to store protons only at a specific voltage, the researchers enabled zinc ions to be stored first, followed by the additional storage of protons.
The principle is similar to first placing large pebbles in an empty bottle and then filling the gaps between them with fine sand. The electrode is used more efficiently by storing the relatively large zinc ions first and then adding the smaller protons.
In practice, zinc ions were stored first in the higher-voltage range, while protons were additionally stored as the voltage decreased. In the Cu₃(HHTATP)₂ electrode material developed by the research team, zinc ions and protons participated in energy storage sequentially in different voltage ranges.
The sequence is particularly important. If protons react too early, by-products may form and obstruct the movement of zinc ions. By enabling protons to react only after the zinc ions had been stored, the researchers reduced interference between the two storage processes.
The newly developed electrode material achieved a high storage capacity of 368.7 mAh g⁻¹ at 0.5 A g⁻¹. In simple terms, this means that a small amount of electrode material can store a large amount of electricity.
Even when the charging and discharging rate was increased sixteenfold, the electrode retained 46.9% of its initial storage capacity—nearly half. Batteries generally store less energy as their charging and discharging rates increase, but the new electrode maintained substantial storage capacity even under rapid charging and discharging conditions. It also demonstrated stable performance after more than 500 rapid charge–discharge cycles.
Using various X-ray analysis techniques, the research team confirmed that zinc ions were stored first, followed by additional proton storage. The researchers also found that the process of storing and subsequently releasing protons could be repeated.
This study is significant because it overcomes the difficulty of simultaneously achieving high capacity and rapid ion transport in porous electrode materials. In particular, it presents a new direction for developing next-generation aqueous zinc-ion batteries by demonstrating that the storage sequence of different ions can be controlled through molecular-level design.
The findings present a new design approach that could enable safe and economical aqueous zinc-ion batteries to store more energy while charging and discharging rapidly. The approach is expected to help improve the performance of water-based batteries used in applications such as large-scale energy storage systems.
Professor Sarah S. Park from KAIST said, “This study demonstrates that protons, previously regarded as ‘troublemakers’ that could degrade battery performance, can instead be used to store more energy. We expect that applying this principle to various electrode materials will lead to the development of batteries capable of rapidly storing larger amounts of energy.”
POSTECH doctoral student Geunchan Park and master student Gyuwon Lee, participated as co-first authors. The study was published in the international chemistry journal Chem on July 7.
Paper title: Sequential Zn²⁺–H⁺ Storage in a 2D Conductive Metal–Organic Framework for Advanced Aqueous Zinc-Ion Battery
DOI: 10.1016/j.chempr.2026.103129
Author information: Geunchan Park (co-first author), Gyuwon Lee (co-first author), Kangmin Kim (second author), Sarah S. Park (corresponding author)
This research was supported by the Basic Research Program of the National Research Foundation of Korea and the National Supercomputing Center.
2026.08.19 View 734 -
KAIST Controls the Rotation Direction of Light Without Complex New Materials
A new pathway has opened for controlling the rotation direction of light simply by changing how molecules are arranged, without having to synthesize complex new materials. Circularly polarized light is a special form of light that travels while rotating like a pinwheel either to the left or to the right. Because different rotation directions can carry different information, it is drawing attention as a key light source for next-generation displays, optical communications, and security technologies. KAIST researchers have developed a platform technology that arranges symmetric molecules into “microscopic pinwheels,” enabling circularly polarized light with a desired rotation direction.
KAIST (President Choongsik Bae) announced on August 14 that a research team led by Professor Dong Ki Yoon from the Department of Chemistry, in collaboration with researchers from Chungnam National University, Ajou University, Yonsei University, and Japan’s RIKEN, has developed a technology that spatially confines symmetric non-chiral liquid crystal molecules and applies an electric field to form micrometer-scale chiral pinwheel structures, then permanently replicates them onto polymer nanofibers.
Chirality refers to the property of an object whose mirror image cannot be perfectly superimposed on the original, like a person’s left and right hands. Chirality is a key property not only of biological molecules such as proteins and DNA, but also of optical materials used in next-generation displays, optical sensors, and optical communications.
Until now, producing chiral optical materials has generally required the complex synthesis of molecules with asymmetric structures or the addition of large amounts of chiral substances. This has made fabrication complicated, limited the range of usable materials, and made it difficult to realize chiral structures with the same handedness over a large area.
To address this challenge, the research team proposed a new approach based on the idea that “structure creates function.”
The team applied to molecules the same principle by which the same sheet of paper can form either a clockwise or counterclockwise pinwheel depending on how it is folded. They focused on the fact that even symmetric molecules can form structures with different handedness depending on how they assemble.
The researchers first induced rod-shaped molecules to self-assemble into microscopic pinwheel-like structures. They then added an extremely small amount of chiral additive, less than 1% of the total material, to guide all of the pinwheels to face the same direction. The team then successfully replicated this structure onto polymer nanofibers.
When a conventional luminescent material was coated onto this structure, circularly polarized light rotating in opposite directions was emitted depending not on the luminescent material itself, but on the direction of the pinwheel structure. Circularly polarized light is a special form of light that rotates to the left or right as it travels, and because each rotation direction can carry different information, it can be used in next-generation displays, optical communications, and anti-counterfeiting technologies.
In other words, the study showed that the properties of light can be controlled simply by changing the structure on which a light-emitting material is placed, rather than by changing the light-emitting material itself. Put simply, just as the same LEGO blocks can form completely different shapes depending on how they are assembled, the same molecules can produce different optical properties depending only on how they are arranged.
Professor Dong Ki Yoon said, “The key point of this study is that we controlled the rotation direction of light not through the complex chemical structure of chiral molecules, but only through the way molecules are arranged,” adding, “This work presents a new optical material design principle that can be applied to next-generation displays, AR and VR optical devices, polarization sensors, and optical communications without the need to develop complex new materials.”
Jeong Yeon Han, the first author and a Ph.D. candidate, explained, “In conventional approaches, left-handed and right-handed structures tended to form together, canceling out chiral properties. In this study, however, we succeeded in aligning the structures in a single direction over a large area by designing an extremely small amount of additive to select only one rotation direction.”
This study was led by Ph.D. candidate Jeong Yeon Han as the first author, and the research results were published in the international journal Nature Communications on August 05.
Paper title: Microchiral pinwheel arrays based on achiral molecules,
DOI: 10.1038/s41467-026-76089-z
Authors: Jeong Yeon Han (first author), Won Kyung Park, Byeongil Noh, Fumito Araoka, Sungwook Jung, Byeong Hak Jhun, Youngmin You, Yoonsu Park, Kyung Jin Lee*, Jung-Moo Heo*, and Dong Ki Yoon* (*corresponding authors)
This research was supported by the Technology Innovation Program of the Ministry of Trade, Industry and Energy, the InnoCORE Program of the Ministry of Science and ICT, and the National Research Foundation of Korea.
2026.08.14 View 864 -
KAIST identifies a molecular “switch” that activates cell growth signaling, suggesting a potential basis for next-generation anticancer therapy
Cells carry their own growth switches. When enough nutrients—amino acids in particular—are available, cells flip this switch on and begin to grow. Researchers at KAIST and Yonsei University have now uncovered the molecular mechanism by which amino acid signals activate this cellular growth switch. The findings are expected to open a new avenue for anticancer therapies that target abnormal growth signaling in tumor cells.
KAIST (President Choongsik Bae) announced on July 26 that a research team led by Professors Hee-Sung Park and Jin Young Kang from the Department of Chemistry, working with Professor Sunghoon Kim's team from Yonsei University, has identified a molecular mechanism that links amino acid stimulation to mTORC1-dependent growth signaling.
Cells continually monitor whether enough amino acids—the basic building blocks of proteins—are available in their surroundings, and adjust their growth, protein synthesis, and energy use accordingly. Central to this process is mTORC1 (mammalian Target of Rapamycin Complex 1), a protein complex that functions as the cell's growth switch.
mTORC1 promotes cell growth, protein synthesis, and metabolism when nutrients and energy are abundant. But when mTORC1 becomes excessively active, cells can grow and proliferate beyond what is needed—a pattern of dysregulation observed in numerous cancers. For this reason, mTORC1 has long been considered a prime target for anticancer drug development. Exactly how cells detect external nutrient cues and translate them into mTORC1 activation, however, has remained incompletely understood.
The research team focused on the multi-tRNA synthetase complex (MSC), a large protein assembly composed of multiple aminoacyl-tRNA synthetases and scaffold proteins. While aminoacyl-tRNA synthetases are best known for their essential role in protein synthesis – attaching specific amino acids to their cognate tRNAs – the team showed that, in response to amino acid stimulation the MSC releases LARS1, thereby linking nutrient availability to growth signaling.
The key player within the MSC turned out to be a protein called LARS1 (leucyl-tRNA synthetase 1), an enzyme that attaches leucine to its corresponding tRNA and also functions as an intracellular leucine sensor. When cells receive a signal that nutrients are sufficient, LARS1 undergoes phosphorylation—a modification in which a small chemical tag is attached to a protein, altering its function or binding behavior.
The relationship can be pictured this way: the MSC is a control center where multiple proteins wait on standby, and LARS1 is the field agent dispatched to flip on the growth switch. When nutrients become abundant, LARS1 receives a phosphorylation "deployment signal," dissociates from IARS1, the protein that anchors LARS1 to the MSC, and is thereby released from the complex. The freed LARS1 then goes on to activate mTORC1.
In other words, when nutrients are scarce, LARS1 stays bound within the MSC and the growth signal remains off. Once nutrients become sufficient, LARS1 is released from the MSC and switches on mTORC1.
To investigate the structural basis of this process, the team used cryo-electron microscopy (cryo-EM), a technique that visualizes protein complexes in three dimensions in near-atomic resolution by rapidly freezing samples at extremely low temperatures. This allowed the researchers to determine how LARS1 and IARS1 bind to each other and to structurally explain how phosphorylation could disrupt their interaction.
The results showed that LARS1 and IARS1 are normally bound tightly, but amino acid stimulation induces the phosphorylation of LARS1, weakening its interaction with IARS1. This allows LARS1 to dissociate from the MSC and activate mTORC1.
The researchers also engineered phosphomimetic LARS1 variants—mutant proteins designed to imitate the phosphorylated state—and found that these variants substantially enhanced mTORC1 activity. This confirmed that the phosphorylation of LARS1 functions as the key molecular switch converting a nutrient signal into a cell growth signal.
The significance of this study lies in mapping, in concrete molecular detail, how cells sense amino acids and use that information to activate their growth switch. In particular, the study revealed that, upon receiving nutrient signals, the MSC—a complex involved in protein synthesis—releases its constituent protein LARS1, which then activates cellular growth signaling.
Some existing anticancer drugs work by directly inhibiting mTORC1, the cell's growth switch. However, because mTORC1 is also required for normal cellular growth and metabolism, its direct inhibition may also affect normal cells.
The research team expects that further identifying the kinase responsible for phosphorylating LARS1, along with its regulatory mechanism, could enable a more precise anticancer strategy—one that intercepts the growth signal further upstream, before it reaches mTORC1, rather than blocking mTORC1 itself.
The study was co-first-authored by Youjin Kim and Joo-Chan Kim from KAIST's Department of Chemistry and was published online in Nature Communications on June 11.
Paper title: Cryo-EM structure of the LARS1:IARS1 complex reveals a nutrient-responsive switch controlling mTORC1 signaling
DOI: https://doi.org/10.1038/s41467-026-74085-x
This work was supported by the National Research Foundation of Korea (grant nos. RS-2026-25482352 to H.S.P., RS-2024-00344154 to J.Y.K., and NRF-2021R1A3B1076605 to S.K.) and PNCC (grant no. 160183).
2026.07.27 View 1458 -
KAIST Develops a Molecular Platform for the Selective Control of Oxygen Reaction Pathways
Controlling how oxygen reacts is important for improving technologies such as batteries, fuel cells, and environmentally sustainable chemical processes. A KAIST research team has developed a new molecular system that can selectively switch the pathway through which electrons are transferred during oxygen activation. The findings are expected to provide a fundamental design principle for next-generation catalysts and energy-conversion technologies.
KAIST (President Choongsik Bae) announced on the 22nd of July that a research team led by Professor Seung Jun Hwang from the Department of Chemistry has developed a molecular system capable of directing oxygen activation along a selected electron-transfer pathway. By combining germanium with a molecular framework that can store and transfer electrons, the team established a design principle for selectively switching oxygen activation between two- and four-electron pathways.
Catalysts for controlling oxygen reactions have traditionally been developed around transition-metal centers such as iron, cobalt, and nickel. Germanium, by contrast, is a main-group element in the same group of the periodic table as silicon and has generally been considered less suitable for reactions requiring the coordinated transfer of several electrons.
To overcome this limitation, the research team combined germanium with a redox-active ligand, a molecular framework capable of storing, accepting, and transferring electrons. The ligand serves as an electron reservoir and cooperates with the germanium center, allowing the entire molecular structure to participate in multielectron reactions.
When oxygen reacts, the products and reaction outcomes depend on whether two or four electrons are transferred. In general, two-electron oxygen reduction produces hydrogen peroxide, while four-electron reduction produces water. Selectively controlling these pathways is therefore an important challenge in the development of batteries, fuel cells, and greener chemical catalysts.
The study presents a rare example of a main-group molecular system in which two- and four-electron reactivity can be selectively accessed within the same underlying molecular framework. This approach broadens the range of elements that may be considered in catalyst design and provides an alternative strategy to relying exclusively on transition metals.
The team also succeeded in isolating and analyzing a germanium compound representing the two-electron stage of the reaction, which they stabilized by attaching a methyl group to the germanium complex. Remarkably, the germanium atom in this compound could both donate and accept electrons, providing an important clue to how the system controls different reaction pathways.
The team also confirmed the practical potential of the new system. Under mild, light-free conditions, the germanium complex removed halogen atoms such as bromine and chlorine from organic compounds and regenerated alkenes (organic compounds containing a carbon-carbon double bond), which are widely used as raw materials for pharmaceuticals, plastics, and other chemical products. These results suggest that useful chemical feedstocks could be produced through simpler and potentially more energy-efficient processes.
“We expect these findings to inform the development of next-generation catalysts for energy conversion and to contribute to more selective and efficient chemical processes.” said Professor Hwang.
The study was conducted by Sung Gyu Kim and Jinrok Oh, currently postdoctoral researchers in the KAIST Department of Chemistry, and Dae Eui Choi, a student in the combined master’s and doctoral program in the Department of Chemistry at POSTECH. The results were published online in the international journal Chem on July 6.
Paper title: Germanium Ligand Redox Cooperativity: A Key to Ambiphilicity and Switchable Two- and Four-Electron Transfer
DOI: 10.1016/j.chempr.2026.103127
This work was supported by National Research Foundation of Korea grants funded by the Korean government through the Ministry of Science and ICT (NRF-2021R1C1C1010220 and RS-2025-02216980), and by the Samsung Science and Technology Foundation under Project No. SSTF-BA2101-09. Sung Gyu Kim received research fellowship support from the Basic Science Research Program through the National Research Foundation of Korea, funded by the Ministry of Education (RS-2024-00415390).
2026.07.22 View 1291 -
KAIST: Dementia-Causing Substance Turns On a Therapeutic “Switch”
A substance that worsens dementia has become a “switch” that initiates treatment. KAIST researchers have developed a new therapeutic approach that uses hydrogen peroxide (H₂O₂), a reactive oxygen species that damages cells and increases in the brains of patients with Alzheimer’s disease, to activate a drug selectively in diseased brain tissue. The team also confirmed improvements in cognitive function through animal experiments, presenting a new possibility for next-generation dementia treatment.
KAIST announced on the 2nd that a research team led by Professor Mi Hee Lim of the Department of Chemistry, in collaboration with Professor Mingeun Kim of Chonnam National University, Dr. Chul-Ho Lee and Dr. Kyoung-Shim Kim of the Korea Research Institute of Bioscience and Biotechnology, and Dr. Young-Ho Lee of the Korea Basic Science Institute, has developed a prodrug that is activated selectively in the diseased brain in Alzheimer’s disease and confirmed its therapeutic effects through animal experiments.
A prodrug is a drug that initially has minimal therapeutic effect but is converted into an active therapeutic agent only under specific conditions inside the body. In this study, the prodrug was designed to be activated only when it encounters hydrogen peroxide, which increases in the brains of patients with Alzheimer’s disease, allowing it to function as a “smart therapeutic agent” that selectively acts in diseased brain tissue.
In the brains of Alzheimer’s disease patients, hydrogen peroxide, which damages cells, is elevated above normal levels. Until now, it has generally been regarded only as a harmful substance that should be removed. However, the research team devised a method to use it instead as a signal that activates a drug.
The prodrugs developed by the research team, BE-1 and BE-2, are designed to remain minimally reactive in a healthy brain. However, when they encounter hydrogen peroxide in a brain affected by dementia, they are converted into active therapeutic compounds, AP-1 and AP-2. Through this process, they reduce reactive oxygen species, including hydrogen peroxide, while also preventing amyloid beta (Aβ) peptides — peptides known as a major cause of dementia that accumulate in the brain and damage nerve cells — from aggregating into highly toxic clumps.
Using advanced analytical techniques, the research team confirmed that the activated drug alters the morphology of amyloid beta aggregates and suppresses their growth into large aggregates.
These effects were also confirmed in Alzheimer’s disease mouse models. The drug crossed the blood-brain barrier (BBB), a protective barrier that controls whether substances in the blood can enter the brain, and was converted into the therapeutic compound inside the diseased brain. In mice that received long-term drug administration, oxidative stress in the hippocampus, which is responsible for memory, was reduced, and amyloid beta accumulation in the brain also decreased. In behavioral experiments assessing the ability to recognize new objects and navigate mazes, cognitive function was also found to improve.
This study is significant in that the drug was designed to operate only where needed by using the environment of the diseased brain itself. This approach presents a new strategy for dementia treatment that can enhance therapeutic efficacy while reducing side effects, and it is expected to be applicable to the treatment of other neurodegenerative diseases, such as Parkinson’s disease.
Professor Mi Hee Lim of KAIST’s Department of Chemistry said, “This study is meaningful in that hydrogen peroxide, which had previously been regarded only as something to be eliminated, was used as a signal to activate a drug. We expect this strategy, which activates drugs in diseased tissue, to become a new platform for treating complex diseases such as Alzheimer’s disease more safely and effectively.”
This study was co-first-authored by Jimin Lee and Eunseo Hong, Ph.D. candidates in KAIST’s Department of Chemistry, and was published online on May 31, 2026, in the international journal Small (Impact Factor: 12.1, top 10% in the field of chemistry).
※ Paper title: A Prodrug Approach for Activity-Based Chemical Modulation toward Multiple Pathological Targets in Alzheimer’s Disease
DOI: 10.1002/smll.74013
This research was supported by the National Research Foundation of Korea’s Leader Researcher Program, Global Leading Research Center Program, Sejong Science Fellowship, Graduate Student Research Encouragement Program, and institutional programs of KRIBB and KBSI.
2026.07.03 View 2333 -
KAIST Develops Hydrogel Material with Improved Skin Adhesion and Controllable Degradation Rate
<(From Left) Researcher Han-Yeol Yang, Professor Haeshin Lee>
Could wound healing dressings adhere better, and drug delivery patches become more sophisticated? A KAIST research team has developed a technology that leverages natural ingredients derived from plants to increase the strength of seaweed-based hydrogel (a gel material that contains a large amount of water while maintaining its shape) by more than fivefold, while also controlling its adhesiveness and degradation rate.
KAIST announced on June 9th that a research team led by Professor Haeshin Lee from the Department of Chemistry has developed a new material design strategy that utilizes tannic acid—a type of polyphenol, which is a natural antioxidant abundant in tea and fruits—to enhance the mechanical strength and adhesiveness of seaweed-derived hydrogel and to control its degradation rate.
Hydrogel is a high-moisture gel material used in contact lenses, acne patches, mask packs, and wound healing dressings. Because it can adhere closely to the skin while holding drugs or active ingredients, it is being utilized in various bio and healthcare fields, such as drug delivery systems (materials that effectively deliver drugs to desired sites), wound dressings (medical dressings that protect wounds and aid healing), tissue engineering scaffolds (structures that help regenerate artificial tissue), and cosmetic materials.
Among various hydrogel materials, the research team focused on 'κ-Carrageenan'. κ-Carrageenan is a natural polymer extracted from red seaweed (rhodophytes) such as agar-agar, and it is a familiar food ingredient used to increase the viscosity and maintain the shape of jellies and sauces. However, there were limitations to improving the performance of hydrogels made with κ-Carrageenan. The κ-Carrageenan molecule contains many structures called sulfate groups, which create intermolecular repulsion—much like magnets of the same pole pushing each other away—and prevent the formation of a dense structure. For this reason, it was difficult to increase the strength and adhesiveness of the hydrogel or to adjust the degradation rate to a desired level.
To solve this problem, the research team focused on finding a natural substance that could effectively interact with the sulfate groups. As a result, they determined that tannic acid, a natural polyphenol abundant in tea and fruits, could be a promising candidate.
Polyphenols are natural ingredients produced by plants to protect themselves from external environments such as ultraviolet rays or pests, and they have the characteristic of being able to bind with multiple substances simultaneously. In particular, tannic acid has multiple binding sites (galloyl groups), so it was expected to interact strongly with the sulfate groups of κ-Carrageenan and connect the molecules together. The research team believed that this characteristic could be utilized to reinforce the hydrogel structure.
As a result of the study, it was confirmed that the sulfate group, which was previously considered a factor hindering hydrogel formation, actually acts as a core binding site with tannic acid. In other words, the structure that was previously considered a "weakness" played a role in making the hydrogel even firmer upon meeting tannic acid.
< Research Image Related to Polyphenol Interactions >
In fact, the storage modulus (an index representing the firmness and elasticity of a gel) of the κ-Carrageenan hydrogel with added tannic acid was approximately 1,632 Pa, showing an improvement of more than fivefold compared to the pure κ-Carrageenan hydrogel (approximately 294 Pa). This means that the hydrogel can maintain its shape more stably even under external pressure or deformation, demonstrating that it can increase the durability and usability of wound healing dressings or drug delivery patches.
In addition, the research team confirmed that tannic acid stably reinforces the internal network structure (gel network) of the already formed hydrogel, regardless of the point in time when the tannic acid is added. This implies that tannic acid connects molecules at multiple points, allowing the internal structure of the hydrogel to remain consistently firm.
Notably, the research team succeeded in implementing rapid degradability and strong adhesiveness simultaneously. In experiments simulating the human stomach and intestinal environments, the hydrogel containing tannic acid degraded relatively quickly while adhering strongly to the skin and rough surfaces. This means that wound healing dressings will not easily fall off during use but can naturally degrade after completing their role, and drug delivery patches can be utilized to stably deliver drugs for a desired period.
This study is meaningful in that it presented a design principle capable of simultaneously controlling the strength, adhesiveness, and degradation rate of hydrogel using only food-grade natural ingredients without complex chemical synthesis processes. The research team expects this technology to be utilized in various bio and healthcare fields, such as capsules and coating materials for food and functional foods, skin-adhering cosmetics and skincare products, wound dressings, drug delivery patches, and tissue engineering scaffolds.
<Research Image (AI-Generated)>
Professor Haeshin Lee said, "This study is an example showing that the mechanical strength, adhesiveness, and degradation behavior of hydrogel can be designed together using only naturally derived materials," adding, "It can be expanded into a safer and simpler natural polymer gel platform in the fields of food, cosmetics, and biomaterials."
This study, in which PhD student Han-Yeol Yang participated as the first author, was published on April 21st in 'Biomimetics', an international academic journal in the field of biomimetics. ※ Paper Title: Adhesive κ-Carrageenan Hydrogels by Polyphenol Intervention, DOI: 10.3390/biomimetics11040290
Meanwhile, this research was conducted with research funding support from Polyphenol Factory Inc., a faculty-led startup enterprise of KAIST.
2026.06.09 View 2536 -
AI that Understands Chemical Principles... Accelerating the Development of New Drugs and Materials
<(From top left) Professor Woo Youn Kim (KAIST), Dr. Jeheon Woo (KISTI), Dr. Seonghwan Kim (KAIST), and Jun Hyeong Kim (PhD candidate)>
Whether a smartphone battery lasts longer or a new drug can be developed to treat incurable diseases depends on how stably the atoms constituting the material are bonded. The core of 'molecular design' lies in finding how to arrange these countless atoms to form the most stable molecule. Until now, this process has been as difficult as finding the lowest valley in a massive mountain range, requiring immense time and costs. Researchers at KAIST have developed a new technology that uses artificial intelligence to solve this process quickly and accurately.
KAIST announced on February 10th that Professor Woo Youn Kim's research team in the Department of Chemistry has developed 'Riemannian DenoisingModel (R-DM),' an artificial intelligence model that understands the physical laws governing molecular stability to predict structures.
The most significant feature of this model is that it directly considers the 'energy' of the molecule. While existing AI models simply mimicked the shape of molecules, R-DM refines the structure by considering the forces acting within the molecule. The research team represented the molecular structure as a map where higher energy is depicted as hills and lower energy as valleys, designing the AI to move toward and find the valleys with the lowest energy.
R-DM completes the molecule by navigating this energy landscape, avoiding unstable structures to find the most stable state. This applies the mathematical theory of 'Riemannian geometry,' resulting in the AI learning the fundamental law of chemistry: 'matter prefers the state with the lowest energy.'
Experimental results showed that R-DM achieved up to 20 times higher accuracy than existing AI models, reducing prediction errors to a level nearly indistinguishable from precise quantum mechanical calculations. This represents the world's highest level of performance among AI-based molecular structure prediction technologies.
<Comparison of energy landscapes in Euclidean space and Riemannian space>
This technology can be utilized in various fields, including new drug development, next-generation battery materials, and high-performance catalyst design. It is expected to serve as an 'AI simulator' that will dramatically speed up research and development by significantly shortening the molecular design process, which previously took a long time. Furthermore, it has great potential in environmental and safety fields, as it can quickly predict chemical reaction paths in situations where experiments are difficult, such as chemical accidents or the spread of hazardous substances.
Professor Woo Youn Kim stated, "This is the first case where artificial intelligence has understood the basic principles of chemistry and judged molecular stability on its own. It is a technology that can fundamentally change the way new materials are developed."
<Image of Riemannian Diffusion Model application (AI-generated image)>
This study was led by Dr. Jeheon Woo from the KISTI Supercomputing Center and Dr. Seonghwan Kim from the KAIST Innovative Drug Discovery Research Group as co-first authors. The research results were published on January 2nd in the world-renowned academic journal Nature Computational Science.
※ Paper Title: Riemannian Denoising Model for Molecular Structure Optimization with Chemical Accuracy, DOI: 10.1038/s43588-025-00919-1
Meanwhile, this research was conducted with the support of the Chemical Accident Prediction-Prevention Advanced Technology Development Project of the Korea Environmental Industry & Technology Institute, the Science and Technology Institute InnoCore Project of the Ministry of Science and ICT, and the Data Science Convergence Talent Cultivation Project conducted by the National Research Foundation of Korea with support from the Ministry of Science and ICT.
2026.02.10 View 3940 -
KAIST Suppresses Side Effects of mRNA Therapeutics, Broadly Applicable Platform for Safer, Personalized Treatments
<(From Left) Professor Yong Woong Jun, Ph.D candidate Tae Ung Jeong, Ph.D candidate Jihun Choi>
mRNA, widely known from the COVID-19 vaccine, is not actually a “therapeutic agent,” but a technology that delivers the blueprint for functional proteins into the body so that induces therapeutic effects. Recently, its application has expanded to cancer and genetic disease treatments, but mRNA therapeutics have caused serious side effects such as pulmonary embolism, stroke, thrombosis, and autoimmune diseases because proteins are excessively produced all at once immediately after administration. Although technology to control the endogenous protein factory has been continuously needed, there had been no suitable solution.
KAIST (President Kwang Hyung Lee) announced on the 1st of December that Professor Yong Woong Jun’s research team in the Department of Chemistry has proposed a new strategy that can control the initiation timing and rate at which mRNA produces proteins. By using this method, the rate of protein production can be adjusted/personalized according to a patient’s condition, enabling safer treatment.
This technology is expected to serve as an important turning point in next-generation mRNA therapeutics, not only fundamentally reducing side effects of mRNA treatments but also enabling application to treatment areas requiring precise protein regulation such as stroke, cancer, and immune diseases.
For a protein to be produced, the cell’s “protein production machinery (ribosomes and initiation factors)” must attach to the mRNA blueprint and begin working. The research team focused on the fact that delaying this process even slightly can prevent the sudden surge of protein production.
Therefore, instead of using complex technologies, they developed a simple method in which intentionally slightly damaged DNA fragments are attached to mRNA. These DNA fragments act like a small “shield,” preventing the protein production machinery from immediately attaching to the mRNA and thereby gently slowing the initiation speed of protein production.
The damaged DNA used here is a safe biological material naturally recycled in the body and is very inexpensive. Because it only needs to be mixed with mRNA right before injection, it is suitable for real-world medical use.
As time passes, the body’s natural “repair enzymes” partially degrade the damaged DNA, and during this process, the structure attached to the mRNA is released, smoothly transitioning the protein production speed back to normal mode. As a result, the previous risk of proteins being explosively produced all at once is greatly reduced.
The research team confirmed that by adjusting the length and degree of damage of the DNA, they could precisely design when and how slowly protein production would begin. They also found that even when multiple types of mRNA are administered at once, the proteins can be produced sequentially in the desired order, meaning this method could innovate existing approaches that required multiple separate injections for complex treatments.
This technology was selected by KAIST as one of its “Future Promising Core Technologies” and was also introduced at the “2025 KAIST Techfair Technology Transfer Session.”
<A translation-control strategy based on DNA–mRNA hybrids. The damaged base (in red) is removed by a repair enzyme, after which the DNA and mRNA dissociate, allowing translation factors and ribosomes to bind and initiate protein translation>
Professor Yong Woong Jun said, “Biological phenomena are ultimately chemistry, so we were able to precisely control the protein production process through a chemical approach,” and added that “this technology not only enhances the safety of mRNA therapeutics but also provides a foundation for expanding into precision treatments tailored to various diseases such as cancer and genetic disorders.”
The results of this research, with Jihun Choi (KAIST, 3rd-year PhD student) and Tae Ung Jeong (KAIST, 1st-year PhD student) participating as co–first authors, were published on November 6 in Angewandte Chemie International Edition, one of the most prestigious journals in the field of chemistry.
※ Paper title: “Harnessing Deaminated DNA to Modulate mRNA Translation for Controlled and Sequential Protein Expression,” Authors: Jihun Choi (KAIST, co–first author), Tae Ung Jeong (KAIST, co–first author), and Yong Woong Jun (KAIST, corresponding author), among a total of 10 authors, DOI: 10.1002/anie.202516389
This study was supported by the National Research Foundation of Korea (NRF) through the Excellent Young Researcher Program.
2025.12.02 View 3648 -
KAIST-KBSI, ‘Communication’ Between Proteins Found to Mitigate Alzheimer’s Toxicity… Opening the Path to Treatment
50 million people worldwide are estimated to have dementia, with Alzheimer’s disease—accounting for over 70%—being the representative neurodegenerative brain disorder. A Korean research team has, for the first time in the world, identified at the molecular level that tau and amyloid-β, the two key pathological proteins of Alzheimer’s disease, directly communicate to regulate toxicity. This achievement is expected to provide new insights into the pathophysiology of Alzheimer’s disease, as well as important clues for discovering biomarkers for early diagnosis and developing therapeutics for neurodegenerative brain disorders.
KAIST (President Kwang Hyung Lee) announced on the 24th of August that Professor Mi Hee Lim’s research team in the Department of Chemistry (Director of the Research Center for Metal–Neuroprotein Interactions), in collaboration with Dr. Young-Ho Lee’s team from the Division of Advanced Biomedical Research at the Korea Basic Science Institute (KBSI, President Sung-kwang Yang) under the National Research Council of Science & Technology (NST, Chairperson Yeung-Shik Kim), together with Dr. Yun Kyung Kim and Dr. Sung Su Lim from the Brain Science Institute at the Korea Institute of Science and Technology (KIST, President Sang-Rok Oh), has elucidated at the molecular level that the microtubule-binding domain of tau—one of the major pathological proteins of Alzheimer’s disease—directly interacts with amyloid-β (tau–amyloid-β communication), alters its aggregation pathway, and alleviates cellular toxicity.
Pathologically, Alzheimer’s disease is characterized by the accumulation of“neurofibrillary tangles” formed by aggregates of tau, a protein responsible for transporting nutrients and signaling molecules within neurons, and “amyloid plaques (senile plaques)” formed by clusters of amyloid-β fragments—abnormally cleaved from amyloid precursor protein, which is involved in brain development, intercellular signaling, and neuronal recovery—that aggregate in and around neuronal membranes in the brain.
Although tau and amyloid-β form pathological structures in spatially separated locations, it has been suggested that they may coexist inside and outside of cells and potentially interact. However, the molecular-level understanding of how their direct interaction affects the onset and progression of the disease has not been clearly revealed until now.
The joint research team found that among the structural repeats of tau protein that bind to microtubules (the intracellular transport system) inside neurons—K18, R1–R4, PHF6*, and PHF6—specifically K18, R2, and R3 bind with amyloid-β to form ‘tau–amyloid-β heterocomplexes.’ This process is significant because amyloid-β normally assembles into highly toxic, rigid fibers (amyloid fibrils), but when certain tau regions bind, amyloid-β shifts to an aggregation pathway that produces less toxic, less rigid aggregates.
Notably, these repeat regions of tau delay the nucleation stage (the initial step of amyloid aggregation linked to disease onset) and simultaneously alter the aggregation speed and structural form of amyloid-β associated with disease progression. As a result, the toxicity caused by amyloid-β was markedly reduced in both the intracellular and extracellular environments of the brain.
In this study, the team combined precise analytical techniques—including spectroscopy, mass spectrometry, isothermal titration calorimetry, and nuclear magnetic resonance—with cell-based toxicity assays to comprehensively analyze the structural, thermodynamic, and functional properties of tau–amyloid interactions.
The findings revealed that specific regions of tau’s microtubule-binding repeats possess both hydrophilic (water-attracting) and hydrophobic (water-repelling) characteristics, and when the balance of these two properties is optimized, tau binds more effectively to amyloid-β. In other words, the intrinsic properties of tau determine its binding affinity with amyloid-β, its modulation of aggregation pathways, and its ability to regulate toxicity.
Dr. Young-Ho Lee of KBSI stated, “This research has uncovered a new molecular mechanism for the onset and progression of dementia, an intractable neurodegenerative disease. In particular, multidisciplinary convergent research focused on molecular interactions and protein aggregation is expected to play a pivotal role in clarifying not only the cross-talk between Alzheimer’s and Parkinson’s diseases but also the interconnections among various diseases such as dementia, diabetes, and cancer.”
Professor Mi Hee Lim of KAIST added, “Tau protein does not merely contribute to pathological formation, but rather, through specific microtubule-binding repeat structures, it exerts a molecular function that actively mitigates amyloid-β aggregation and toxicity. This provides a new turning point in the pathological understanding of Alzheimer’s disease. The significance of this study lies in identifying new molecular motifs that could serve as therapeutic targets not only for Alzheimer’s but also for a variety of protein aggregation-based neurodegenerative brain disorders.”
This research, with Dr. Min Geun Kim of KAIST’s Department of Chemistry as first author, was published on August 22 in the internationally renowned journal Nature Chemical Biology (Impact factor: 13.7, top 3.8% in the field of chemistry).
※ Paper Title: “Interactions with tau’s microtubule-binding repeats modulate amyloid-β aggregation and toxicity”
※ DOI: 10.1038/s41589-025-01987-0
This research was supported by the National Research Foundation of Korea’s Basic Research Program (Leader Research and Mid-career Researcher Program), the Sejong Science Fellowship, as well as KBSI and KIST.
2025.08.25 View 7239 -
KAIST Develops AI That Automatically Designs Optimal Drug Candidates for Cancer-Targeting Mutations
< (From left) Ph.D candidate Wonho Zhung, Ph.D cadidate Joongwon Lee , Prof. Woo Young Kim , Ph.D candidate Jisu Seo >
Traditional drug development methods involve identifying a target protin (e.g., a cancer cell receptor) that causes disease, and then searching through countless molecular candidates (potential drugs) that could bind to that protein and block its function. This process is costly, time-consuming, and has a low success rate. KAIST researchers have developed an AI model that, using only information about the target protein, can design optimal drug candidates without any prior molecular data—opening up new possibilities for drug discovery.
KAIST (President Kwang Hyung Lee) announced on the 10th that a research team led by Professor Woo Youn Kim in the Department of Chemistry has developed an AI model named BInD (Bond and Interaction-generating Diffusion model), which can design and optimize drug candidate molecules tailored to a protein’s structure alone—without needing prior information about binding molecules. The model also predicts the binding mechanism (non-covalent interactions) between the drug and the target protein.
The core innovation of this technology lies in its “simultaneous design” approach. Previous AI models either focused on generating molecules or separately evaluating whether the generated molecule could bind to the target protein. In contrast, this new model considers the binding mechanism between the molecule and the protein during the generation process, enabling comprehensive design in one step. Since it pre-accounts for critical factors in protein-ligand binding, it has a much higher likelihood of generating effective and stable molecules. The generation process visually demonstrates how types and positions of atoms, covalent bonds, and interactions are created simultaneously to fit the protein’s binding site.
<Figure 1. Schematic of the diffusion model developed by the research team, which generates molecular structures and non-covalent interactions based on protein structures. Starting from a noise distribution, the model gradually removes noise (via reverse diffusion) to restore the atom positions, types, covalent bond types, and interaction types, thereby generating molecules. Interacting patterns are extracted from prior knowledge of known binding molecules or proteins, and through an inpainting technique, these patterns are kept fixed during the reverse diffusion process to guide the molecular generation.>
Moreover, this model is designed to meet multiple essential drug design criteria simultaneously—such as target binding affinity, drug-like properties, and structural stability. Traditional models often optimized for only one or two goals at the expense of others, but this new model balances various objectives, significantly enhancing its practical applicability.
The research team explained that the AI operates based on a “diffusion model”—a generative approach where a structure becomes increasingly refined from a random state. This is the same type of model used in AlphaFold 3, the 2024 Nobel Chemistry Prize-winning tool for protein-ligand structure generation, which has already demonstrated high efficiency.
Unlike AlphaFold 3, which provides spatial coordinates for atom positions, this study introduced a knowledge-based guide grounded in actual chemical laws—such as bond lengths and protein-ligand distances—enabling more chemically realistic structure generation.
<Figure 2. (Left) Target protein and the original bound molecule; (Right) Examples of molecules designed using the model developed in this study. The values for protein binding affinity (Vina), drug-likeness (QED), and synthetic accessibility (SA) are shown at the bottom.>
Additionally, the team applied an optimization strategy where outstanding binding patterns from prior results are reused. This allowed the model to generate even better drug candidates without additional training. Notably, the AI successfully produced molecules that selectively bind to the mutated residues of EGFR, a cancer-related target protein.
This study is also meaningful because it advances beyond the team’s previous research, which required prior input about the molecular conditions for the interaction pattern of protein binding.
Professor Woo Youn Kim commented that “the newly developed AI can learn and understand the key features required for strong binding to a target protein, and design optimal drug candidate molecules—even without any prior input. This could significantly shift the paradigm of drug development.” He added, “Since this technology generates molecular structures based on principles of chemical interactions, it is expected to enable faster and more reliable drug development.”
Joongwon Lee and Wonho Zhung, PhD students in the Department of Chemistry, participated as co-first authors of this study. The research results were published in the international journal Advanced Science (IF = 14.1) on July 11.
● Paper Title: BInD: Bond and Interaction-Generating Diffusion Model for Multi-Objective Structure-Based Drug Design
● DOI: 10.1002/advs.202502702
This research was supported by the National Research Foundation of Korea and the Ministry of Health and Welfare.
2025.08.12 View 8098 -
Anti-Neuroinflammatory Natural Products from Isopod-Related Fungus Now Accessible via Chemical Synthesis
<(From left) Professor Sunkyu Han, Ph.D candidate Yoojin Lee, Ph.D candidate Taewan Kim>
"Herpotrichone" is a natural substance that has been evaluated highly for its excellent ability to suppress inflammation in the brain and protect nerve cells, displaying significant potential to be developed as a therapeutic agent for neurodegenerative brain diseases such as Alzheimer's disease and Parkinson's disease. This substance could only be obtained in minute quantities from fungi that are symbiotic with isopods. However, KAIST researchers have succeeded in chemically synthesizing this rare natural product, thereby presenting the possibility for the development of next-generation drugs for neurodegenerative diseases.
*Chemical Synthesis: A process of creating desired substances using chemical reactions.
KAIST (President Kwang Hyung Lee) announced on the 31st of July that a research team led by Professor Sunkyu Han of the Department of Chemistry successfully synthesized the natural anti-neuroinflammatory substances 'herpotrichones A, B, and C' for the first time.
Herpotrichone natural products are substances obtainable only in minute quantities from 'Herpotrichia sp. SF09', a symbiotic pill bug fungus, and possess a unique 6/6/6/6/3 pentacyclic framework consisting of five fused rings (four six-membered and one three-membered ring).
Interestingly, this substance exhibits excellent anti-neuroinflammatory effects that suppress brain inflammatory reactions. Recently, its mechanism of action to protect nerve cells by inhibiting ferroptosis (iron-mediated cell death) was also reported, raising expectations for its potential as a therapeutic drug for brain diseases.
Professor Han's research team devised a biosynthetically inspired strategy to chemically synthesize herpotrichoneS. The key to success was a named chemical reaction "Diels-Alder (DA) reaction". This reaction forms a six-membered ring by creating new bonds between carbon-based partners, much like two puzzle pieces interlocking to form a single ring.
<Figure 2. Key Synthetic Strategy for Hypotricon A, B, and C Based on Hydrogen Bonding>
Furthermore, the research team focused on a weak attractive phenomenon between molecules called "hydrogen bonding". By delicately designing and controlling this hydrogen bond, they were able to precisely induce the reaction to occur chemo-, regio- and stereoselectively, thereby synthesizing herpotrichone. Notably, without the pivotal hydrogen bond, only a small amount of the target natural product was formed or only undesirable byproducts were generated.
The configuration of the C2’ hydroxyl moiety was essential in directing the desired transition states leading to the target natural products.
Thanks to this induced hydrogen bonding, the reacting molecules approached the correct positions and went through an ideal transition state, allowing for the synthesis of herpotrichone C. This reaction principle was also successfully applied to herpotrichone A and B, enabling the successful synthesis of these natural products.
During the key Diels-Alder reaction conducted in the laboratory, new molecular structures not yet discovered in nature were also formed. Some of these have a high probability of being novel natural products with excellent pharmacological activity, thus doubling the significance of this research for anticipating natural products through synthesis.
Indeed, while Professor Han's research team conducted synthetic studies on herpotrichone A and B based on a 2019 paper by Chinese researchers who discovered and elucidated their structures, the research team observed the formation of undesired byproducts.
Interestingly, in 2024, the same Chinese research team that discovered herpotrichones A and bn reported the discovery of a new natural product called herpotrichone C, which turned out to be the same substance as the major byproduct previously obtained by Professor Han's team en route to herpotrichones A and B.
Professor Han stated, "This is the first total synthesis of a rare natural product with pharmacological activity related to neurodegenerative diseases and systematically presents the principle of biomimetic synthesis of complex natural products." He added, "It is expected to contribute to the development of novel natural product-based anti-neuroinflammatory therapeutics and biosynthesis research of this group of natural products."
This research outcome, with Yoojin Lee, a master's and Ph.D. integrated course student in the Department of Chemistry, as the first author, was published on July 16th in the Journal of the American Chemical Society (JACS), one of the most prestigious academic journals in the field of chemistry.
This research was supported by the National Research Foundation of Korea (NRF) Mid-career Researcher Support Program, the KAIST UP Project, the KAIST Grand Challenge 30 Project, and the KAIST Trans-Generational Collaborative Research Laboratory Project.
2025.08.04 View 4630