Chem
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KAIST Takes the Lead in Developing Core Technologies for Generative AI National R&D Project
<Professor Sanghoo Park from Department of Nuclear and Quantum Engineering>
KAIST announced on the 15th of August that Professor Sanghoo Park of the Department of Nuclear and Quantum Engineering has won two consecutive awards for early-career researchers at two of the world's most prestigious plasma academic conferences.
Professor Park was selected as a recipient of the Early Career Award (ECA) at the Gaseous Electronics Conference (GEC), hosted by the American Physical Society, on August 4. He was also honored with the Young Investigator Award, presented by the International Plasma Chemistry Society (IPCS), on June 19.
The American Physical Society's GEC Early Career Award is given to only one person worldwide every two years, based on a comprehensive evaluation of research excellence, academic influence, and contributions to the field of plasma. The award will be presented at GEC 2025, which will be held at COEX in Seoul from October 13 to 17.
Established in 1948, the GEC is a leading academic conference in the plasma field with a 77-year history of showcasing key research achievements in all areas of plasma, including physics, chemistry, diagnostics, and application technologies. Recently, advanced application research such as eco-friendly chemical processes, next-generation semiconductors, and atomic layer and ultra-low-temperature etching technology for HBM processes have been gaining attention.
To commemorate the award, Professor Park will give an invited lecture at GEC 2025 on the topic of "Deep-Learning-Based Spectroscopic Data Analysis for Advancing Plasma Spectroscopy." In his lecture, he will use case studies to demonstrate a method that allows even non-specialists to easily and quickly perform spectroscopic data analysis—which is essential for spectroscopy, a key analytical method in modern science including plasma diagnostics—by using deep learning technology.
<Award Ceremony at IPCS (Professor Sanghoo Park on the far left)>
Professor Park also won the Young Investigator Award from the IPCS at the 26th International Symposium on Plasma Chemistry (ISPC 26), which was held in Minneapolis, USA, from June 15 to 20.
First held in 1973, the ISPC (International Symposium on Plasma Chemistry) is a representative international conference in the field of plasma chemistry, held biennially. It covers a wide range of topics, from basic plasma chemical reaction principles to applications in semiconductor processes, green energy, environmental science, and biotechnology. Researchers from industry, academia, and research institutions worldwide share their latest findings at each event. The Young Investigator Award is given to a scientist who has obtained their doctorate within the last 10 years and has demonstrated outstanding achievements in the field.
Professor Park was recognized for his leading research achievements in using plasma-liquid interactions and real-time optical diagnostic technology to environmentally fix nitrogen from the air and precisely control the quantity and types of reactive chemical species that are beneficial to the human body and the environment.
< Photo of a certificate>
Professor Sanghoo Park stated, "It is very meaningful to receive the Young Investigator Award representing Korea at the GEC event, which is being held in Korea for the first time in its history." He added, "I am happy that my consistent interest in and achievements in fundamental plasma science have been recognized, and it is even more significant that the efforts of the KAIST research team have been acknowledged by the world's top conferences."
2025.08.16 View 8 -
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 219 -
KAIST Develops Bioelectrosynthesis Platform for Switch-Like Precision Control of Cell Signaling
<(From left)Professor Jimin Park, Ph.D candidate Myeongeun Lee, Ph.D cadidate Jaewoong Lee,Professor Jihan Kim>
Cells use various signaling molecules to regulate the nervous, immune, and vascular systems. Among these, nitric oxide (NO) and ammonia (NH₃) play important roles, but their chemical instability and gaseous nature make them difficult to generate or control externally. A KAIST research team has developed a platform that generates specific signaling molecules in situ from a single precursor under an applied electrical signal, enabling switch-like, precise spatiotemporal control of cellular responses. This approach could provide a foundation for future medical technologies such as electroceuticals, electrogenetics, and personalized cell therapies.
KAIST (President Kwang Hyung Lee) announced on August 11 that a research team led by Professor Jimin Park from the Department of Chemical and Biomolecular Engineering, in collaboration with Professor Jihan Kim's group, has developed a 'Bioelectrosynthesis Platform' capable of producing either nitric oxide or ammonia on demand using only an electrical signal. The platform allows control over the timing, spatial range, and duration of cell responses.
Inspired by enzymes involved in nitrite reduction, the researchers implemented an electrochemical strategy that selectively produces nitric oxide or ammonia from a single precursor, nitrite (NO₂⁻). By changing the catalyst, the team generated ammonia or nitric oxide from nitrite using a copper-molybdenum-sulfur catalyst (Cu2MoS4) and an iron-incorporated catalyst (FeCuMS4), respectively.
Through electrochemical measurements and computer simulations, the team revealed that Fe sites in the FeCuMoS4 catalyst bind nitric oxide intermediates more strongly, shifting product selectivity toward nitric oxide. Under the same electrical conditions, the Fe-containing catalyst preferentially produces nitric oxide, whereas the Cu2MoS4 catalyst favors ammonia production.
<Figure 1. Schematic diagram of a bio-electrosynthesis platform that synthesizes a desired signaling substance with an electrical signal (left) and the results of precise cell control using it (right)>
The research team demonstrated biological functionality by using the platform to activate ion channels in human cells. Specifically, electrochemically produced nitric oxide activated TRPV1 channels (responsive to heat and chemical stimuli), while electrochemically produced ammonia induced intracellular alkalinization and activated OTOP1 proton channels. By tuning the applied voltage and electrolysis duration, the team modulated the onset time, spatial extent, and termination of cellular responses, which effectively turned cellular signaling on and off like a switch.
<Figure 2. Experimental results showing the change in the production ratio of nitric oxide and ammonia signaling substances according to the type of catalyst (left) and computational simulation results showing the strong bond between iron and nitric oxide (right)>
Professor Jimin Park said, "This work is significant because it enables precise cellular control by selectively producing signaling molecules with electricity. We believe it has strong potential for applications in electroceutical technologies targeting the nervous system or metabolic disorders."
Myeongeun Lee and Jaewoong Lee, Ph.D. students in the Department of Chemical and Biomolecular Engineering at KAIST, served as the co-first authors. Professor Jihan Kim is a co-author. The paper was published online in 'Angewandte Chemie International Edition' on July 8, 2025 (DOI: 10.1002/ange.202508192).
Reference: https://doi.org/10.1002/ange.202508192
Authors: Myeongeun Lee†, Jaewoong Lee†, Yongha Kim, Changho Lee, Sang Yeon Oh, Prof. Jihan Kim, Prof. Jimin Park*
†These authors contributed equally. *Corresponding author.
2025.08.12 View 138 -
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 426 -
KAIST Enables On-Site Disease Diagnosis in Just 3 Minutes... Nanozyme Reaction Selectivity Improved 38-Fold
<(From Left) Professor Jinwoo Lee, Ph.D candidate Seonhye Park and Ph.D candidate Daeeun Choi from Chemical & Biomolecular Engineering>
To enable early diagnosis of acute illnesses and effective management of chronic conditions, point-of-care testing (POCT) technology—diagnostics conducted near the patient—is drawing global attention. The key to POCT lies in enzymes that recognize and react precisely with specific substances. However, traditional natural enzymes are expensive and unstable, and nanozymes (enzyme-mimicking catalysts) have suffered from low reaction selectivity. Now, a Korean research team has developed a high-sensitivity sensor platform that achieves 38 times higher selectivity than existing nanozymes and allows disease diagnostics visible to the naked eye within just 3 minutes.
On the 28th, KAIST (President Kwang Hyung Lee) announced that Professor Jinwoo Lee’s research team from the Department of Chemical & Biomolecular Engineering, in collaboration with teams led by Professor Jeong Woo Han at Seoul National University and Professor Moon Il Kim at Gachon University, has developed a new single-atom catalyst that selectively performs only peroxidase-like reactions while maintaining high reaction efficiency.
Using bodily fluids such as blood, urine, or saliva, this diagnostic platform enables test results to be read within minutes even outside hospital settings—greatly improving medical accessibility and ensuring timely treatment. The key lies in the visual detection of biomarkers (disease indicators) through color changes triggered by enzyme reactions. However, natural enzymes are expensive and easily degraded in diagnostic environments, limiting their storage and distribution.
To address this, inorganic nanozyme materials have been developed as substitutes. Yet, they typically lack selectivity—when hydrogen peroxide is used as a substrate, the same catalyst triggers both peroxidase-like reactions (which cause color change) and catalase-like reactions (which remove the substrate), reducing diagnostic signal accuracy.
To control catalyst selectivity at the atomic level, the researchers used an innovative structural design: attaching chlorine (Cl) ligands in a three-dimensional configuration to the central ruthenium (Ru) atom to fine-tune its chemical properties. This enabled them to isolate only the desired diagnostic signal.
<Figure1. The catalyst in this study (ruthenium single-atom catalyst) exhibits peroxidase-like activity with selectivity akin to natural enzymes through three-dimensional directional ligand coordination. Due to the absence of competing catalase activity, selective peroxidase-like reactions proceed under biomimetic conditions. In contrast, conventional single-atom catalysts with active sites arranged on planar surfaces exhibit dual functionality depending on pH. Under neutral conditions, their catalase activity leads to hydrogen peroxide depletion, hindering accurate detection. The catalyst in this study eliminates such interference, enabling direct detection of biomarkers through coupled reactions with oxidases without the need for cumbersome steps like buffer replacement. The ability to simultaneously detect multiple target substances under biomimetic conditions demonstrates the practicality of ruthenium single-atom catalysts for on-site diagnostics>
Experimental results showed that the new catalyst achieved over 38-fold improvement in selectivity compared to existing nanozymes, with significantly increased sensitivity and speed in detecting hydrogen peroxide. Even in near-physiological conditions (pH 6.0), the catalyst maintained its performance, proving its applicability in real-world diagnostics.
By incorporating the catalyst and oxidase into a paper-based sensor, the team created a system that could simultaneously detect four key biomarkers related to health: glucose, lactate, cholesterol, and choline—all with a simple color change.
This platform is broadly applicable across various disease diagnostics and can deliver results within 3 minutes without complex instruments or pH adjustments. The findings show that diagnostic performance can be dramatically improved without changing the platform itself, but rather by engineering the catalyst structure.
<Figure 2.(a) Schematic diagram of the paper sensor (Zone 1: glucose oxidase immobilized; Zone 2: lactate oxidase immobilized; Zone 3: choline oxidase immobilized; Zone 4: cholesterol oxidase immobilized; Zone 5: no oxidase enzyme). (b) Single biomarker (single disease indicator) detection using the ruthenium single‑atom catalyst–based paper sensor.(c) Multiple biomarker (multiple disease indicator) detection using the ruthenium single‑atom catalyst–based paper sensor>
Professor Jinwoo Lee of KAIST commented, “This study is significant in that it simultaneously achieves enzyme-level selectivity and reactivity by structurally designing single-atom catalysts.” He added that “the structure–function-based catalyst design strategy can be extended to the development of various metal-based catalysts and other reaction domains where selectivity is critical.”
Seonhye Park and Daeeun Choi, both Ph.D. candidates at KAIST, are co-first authors. The research was published on July 6, 2025, in the prestigious journal Advanced Materials
-Title: Breaking the Selectivity Barrier of Single-Atom Nanozymes Through Out-of-Plane Ligand Coordinatio
- Authors: Seonhye Park (KAIST, co–first author), Daeeun Choi (KAIST, co–first author), Kyu In Shim (SNU, co–first author), Phuong Thy Nguyen (Gachon Univ., co–first author), Seongbeen Kim (KAIST), Seung Yeop Yi (KAIST), Moon Il Kim (Gachon Univ., corresponding author), Jeong Woo Han (SNU, corresponding author), Jinwoo Lee (KAIST, corresponding author
-DOI: https://doi.org/10.1002/adma.202506480
This research was supported by the Ministry of Science and ICT and the National Research Foundation of Korea (NRF).
2025.07.29 View 480 -
KAIST Designs a New Atomic Catalyst for Air Pollution Reduction
<(From Left)Professor Jong Hun Kim from Inha University, Dr. Gyuho Han and Professor Jeong Young Park from KAIST>
Platinum diselenide (PtSe2) is a two-dimensional multilayer material in which each layer is composed of platinum (Pt) and selenium (Se). It is known that its excellent crystallinity and precise control of interlayer interactions allow modulation of various physical and chemical properties. Due to these characteristics, it has been actively researched in multiple fields, including semiconductors, photodetectors, and electrochemical devices. Now, a research team has proposed a new design concept in which atomically dispersed platinum on the surface of platinum diselenide can function as a catalyst for gas reactions. Through this, they have proven its potential as a next-generation gas-phase catalyst technology for high-efficiency carbon dioxide conversion and carbon monoxide reduction.
KAIST (President Kwang Hyung Lee) announced on July 22 that a joint research team led by Endowed Chair Professor Jeong Young Park from the Department of Chemistry, along with Professor Hyun You Kim's team from Chungnam National University and Professor Yeonwoong (Eric) Jung's team from the University of Central Florida (UCF), has achieved excellent carbon monoxide oxidation performance by utilizing platinum atoms exposed on the surface of platinum diselenide, a type of two-dimensional transition metal dichalcogenide (TMD).
To maximize catalytic performance, the research team designed the catalyst by dispersing platinum atoms uniformly across the surface, departing from the conventional use of bulk platinum. This strategy allows more efficient catalytic reactions using a smaller amount of platinum. It also enhances electronic interactions between platinum and selenium by tuning the surface electronic structure. As a result, the platinum diselenide film with a thickness of a few nanometers showed superior carbon monoxide oxidation performance across the entire temperature range compared to a conventional platinum thin film under identical conditions.
In particular, carbon monoxide and oxygen were evenly adsorbed on the surface in similar proportions, increasing the likelihood that they would encounter each other and react, which significantly enhanced the catalytic activity. This improvement is primarily attributed to the increased exposure of surface platinum atoms resulting from selenium vacancies (Se-vacancies), which provide adsorption sites for gas molecules.
The research team confirmed in real-time that these platinum atoms served as active adsorption sites during the actual reaction process, using ambient-pressure X-ray photoelectron spectroscopy (AP-XPS) conducted at the Pohang Accelerator Laboratory. This high-precision analysis was enabled by advanced instrumentation capable of observing surfaces at the nanometer scale under ambient pressure conditions. At the same time, computer simulations based on density functional theory (DFT) demonstrated that platinum diselenide exhibits distinct electronic behavior compared to conventional platinum.
*Density Functional Theory (DFT): A quantum mechanical method for calculating the total energy of a system based on electron density.
Professor Jeong Young Park stated, “This research presents a new design strategy that utilizes platinum diselenide, a two-dimensional layered material distinct from conventional platinum catalysts, to enable catalytic functions optimized for gas-phase reactions.” He added, “The electronic interaction between platinum and selenium created favorable conditions for the balanced adsorption of carbon monoxide and oxygen. By designing the catalyst to exhibit higher reactivity across the entire temperature range than conventional platinum, we improved its practical applicability. This enabled a high-efficiency catalytic reaction mechanism through atomic-level design, a two-dimensional material platform, and precise adsorption control.”
This research was co-authored by Dr. Gyuho Han from the Department of Chemistry at KAIST, Dr. Hyuk Choi from the Department of Materials Science and Engineering at Chungnam National University, and Professor Jong Hun Kim from Inha University. The study was published on July 3 in the world-renowned journal Nature Communications.
Paper Title: Enhanced catalytic activity on atomically dispersed PtSe2 two-dimensional layers
DOI: 10.1038/s41467-025-61320-0
This research was supported by the Mid-Career Researcher Program of the Ministry of Science and ICT, the Core Research Institute Program of the Ministry of Education, the National Strategic Technology Materials Development Project, the U.S. National Science Foundation (NSF) CAREER Program, research funding from Inha University, and the Postdoctoral Researcher Program (P3) at UCF. Accelerator-based analysis was conducted in cooperation with the Pohang Accelerator Laboratory and the Korea Basic Science Institute (KBSI).
2025.07.22 View 464 -
A KAIST Team Engineers a Microbial Platform for Efficient Lutein Production
<(From Left) Ph.D. Candidate Hyunmin Eun, Distinguished Professor Sang Yup Lee, , Dr. Cindy Pricilia Surya Prabowo>
The application of systems metabolic engineering strategies, along with the construction of an electron channeling system, has enabled the first gram-per-liter scale production of lutein from Corynebacterium glutamicum, providing a viable alternative to plant-derived lutein production.
A research group at KAIST has successfully engineered a microbial strain capable of producing lutein at industrially relevant levels. The team, led by Distinguished Professor Sang Yup Lee from the Department of Chemical and Biomolecular Engineering, developed a novel C. glutamicum strain using systems metabolic engineering strategies to overcome the limitations of previous microbial lutein production efforts. This research is expected to be beneficial for the efficient production of other industrially important natural products used in food, pharmaceuticals, and cosmetics.
Lutein is a xanthophyll carotenoid found in egg yolk, fruits, and vegetables, known for its role in protecting our eyes from oxidative stress and reducing the risk of macular degeneration and cataracts. Currently, commercial lutein is predominantly extracted from marigold flowers; however, this approach has several drawbacks, including long cultivation times, high labor costs, and inefficient extraction yields, making it economically unfeasible for large-scale production. These challenges have driven the demand for alternative production methods.
To address these issues, KAIST researchers, including Ph.D. Candidate Hyunmin Eun, Dr. Cindy Pricilia Surya Prabowo, and Distinguished Professor Sang Yup Lee, applied systems metabolic engineering strategies to engineer C. glutamicum, a GRAS (Generally Recognized As Safe) microorganism widely used in industrial fermentation. Unlike Escherichia coli, which was previously explored for microbial lutein production, C. glutamicum lacks endotoxins, making it a safer and more viable option for food and pharmaceutical applications.
The team’s work, entitled “Gram-per-litre scale production of lutein by engineered Corynebacterium,” was published in Nature Synthesis on 04 July , 2025.
This research details the high-level production of lutein using glucose as a renewable carbon source via systems metabolic engineering. The team focused on eliminating metabolic bottlenecks that previously limited microbial lutein synthesis. By employing enzyme scaffold-based electron channeling strategies, the researchers improved metabolic flux towards lutein biosynthesis while minimizing unwanted byproducts.
<Lutein production metabolic pathway engineering>
To enhance productivity, bottleneck enzymes within the metabolic pathway were identified and optimized. It was determined that electron-requiring cytochrome P450 enzymes played a major role in limiting lutein biosynthesis. To overcome this limitation, an electron channeling strategy was implemented, where engineered cytochrome P450 enzymes and their reductase partners were spatially organized on synthetic scaffolds, allowing more efficient electron transfer and significantly increasing lutein production.
The engineered C. glutamicum strain was further optimized in fed-batch fermentation, achieving a record-breaking 1.78 g/L of lutein production within 54 hours, with a content of 19.51 mg/gDCW and a productivity of 32.88 mg/L/h—the highest lutein production performance in any host reported to date. This milestone demonstrates the feasibility of replacing plant-based lutein extraction with microbial fermentation technology.
“We can anticipate that this microbial cell factory-based mass production of lutein will be able to replace the current plant extraction-based process,” said Ph.D. Candidate Hyunmin Eun. He emphasized that the integrated metabolic engineering strategies developed in this study could be broadly applied for the efficient production of other valuable natural products used in pharmaceuticals and nutraceuticals.
<Schematic diagram of microbial-based lutein production platform>
“As maintaining good health in an aging society becomes increasingly important, we expect that the technology and strategies developed here will play pivotal roles in producing other medically and nutritionally significant natural products,” added Distinguished Professor Sang Yup Lee.
This work is supported by the Development of Next-generation Biorefinery Platform Technologies for Leading Bio-based Chemicals Industry project 2022M3J5A1056072 and the Development of Platform Technologies of Microbial Cell Factories for the Next-Generation Biorefineries project 2022M3J5A1056117 from the National Research Foundation supported by the Korean Ministry of Science and ICT.
Source:
Hyunmin Eun (1st), Cindy Pricilia Surya Prabowo (co-1st), and Sang Yup Lee (Corresponding). “Gram-per-litre scale production of lutein by engineered Corynebacterium”. Nature Synthesis (Online published)
For further information:
Sang Yup Lee, Distinguished Professor of Chemical and Biomolecular Engineering, KAIST (leesy@kaist.ac.kr, Tel: +82-42-350-3930)
2025.07.14 View 1190 -
New and Highly Efficient Recycling Technology to Turn Used Tires into Raw Materials for Rubber and Nylon
< (From left) Kyungmin Choi (MS-Ph.D. integrated course, Department of Chemistry), Dr. Beomsoon Park, Professor Soon Hyeok Hong, Dr. Kyoungil Cho >
Approximately 1.5 billions of tires are discarded globally every year, and this is identified as one of the major causes of serious environmental pollution. The research team at the Department of Chemistry at KAIST has achieved a breakthrough by selectively converting waste tires into high-purity cyclic alkenes, valuable chemical building blocks used in the production of rubber and nylon fibers. This advance marks a new milestone in chemical recycling technology for waste tires.
The team, led by Professor Soon Hyeok Hong, has developed a dual-catalyst-based reaction system that overcomes the long-standing challenges associated with recycling vulcanized rubber materials.
Tires are composed of complex blends of synthetic and natural rubber, and their physical strength and durability are reinforced with additives such as silica, carbon black, and antioxidants. In particular, cross-linking between rubber chains is formed through the vulcanization process, giving them a structure resistant to heat and pressure, which is one of the main reasons why chemical recycling of waste tires is difficult.
Until now, waste tire recycling has mainly relied on pyrolysis or mechanical recycling methods. The pyrolysis method is a technology that decomposes polymer chains at high temperatures of 350-800°C to convert them into fuel oil, but it clearly has limitations such as high energy consumption, low selectivity, and the production of low-quality hydrocarbon mixtures.
To solve these problems, the research team developed a method to convert waste rubber into useful chemicals using dual catalysis. The first catalyst helps to break down rubber molecules by changing their bonding structure, and the second catalyst creates cyclic compounds through a ring-closing reaction.
This process shows high selectivity of up to 92% and a yield of 82%. The produced cyclopentene can be recycled into rubber, and cyclohexene can be used as a raw material for nylon fibers, making them industrially very valuable.
The research team successfully applied the developed system to discarded waste tires, achieving selective conversion into high-purity cyclic alkenes. Unlike the existing pyrolysis method, this is evaluated as a new turning point in the field of waste tire recycling as it can produce high-value chemicals through low-temperature precision catalytic reactions.
In addition, this catalytic platform is compatible with a wide range of synthetic and waste rubbers, positioning it as a promising foundation for scalable, circular solutions in the polymer and materials industries.
< Figure 1. Development of a Catalytic Method for Chemical Recycling of Waste Rubber >
Professor Hong stated, "This research offers an innovative solution for the chemical recycling of waste tires. We aim to develop next-generation high-efficiency catalysts and lay the groundwork for commercialization to enhance economic feasibility. Ultimately, our goal is to contribute to solving the broader waste plastic problem through fundamental chemistry."
This research, in which Beomsoon Park, Kyoungil Cho, and Kyungmin Choi participated, was supported by the National Research Foundation of Korea and was published online in the internationally renowned academic journal ‘Chem’ on June 18th.
※Paper Title: Catalytic and Selective Chemical Recycling of Post-Consumer Rubbers into Cycloalkenes
※DOI: 10.1016/j.chempr.2025.102625
2025.06.26 View 2524 -
Distinguished Professor Sang Yup Lee Wins 2025 Global Metabolic Engineering Award
< Distinguished Professor Sang Yup Lee (Senior Vice President for Research) from the Department of Chemical & Biomolecular Engineering >
KAIST announced on the 20th that Professor Sang Yup Lee, who serves as the Vice President for Research and a Distinguished Professor at our university, has been awarded the '2025 Gregory N. Stephanopoulos Award for Metabolic Engineering' by the International Metabolic Engineering Society (IMES). Professor Lee delivered his award lecture at the 16th Metabolic Engineering Conference (ME16), held in Copenhagen, Denmark, from June 15th to 19th.
This award was established through contributions from the American Institute of Chemical Engineers (AIChE) Foundation, as well as fellow colleagues and acquaintances, to honor the achievements of Dr. Gregory Stephanopoulos, widely recognized as one of the pioneers of metabolic engineering. Presented biennially, the award recognizes scientists who have successfully commercialized fundamental research in metabolic engineering or have made outstanding contributions to the quantitative analysis, design, and modeling of metabolic pathways.
Professor Sang Yup Lee boasts an impressive record of over 770 journal papers and more than 860 patents. His groundbreaking research in metabolic engineering and biochemical engineering is highly acclaimed globally.
Throughout his 31 years as a professor at KAIST, Professor Lee has developed various metabolic engineering-based technologies and strategies. These advancements have been transferred to industries, facilitating the production of bulk chemicals, polymers, natural products, pharmaceuticals, and health functional foods. He has also founded companies and actively engages in advisory roles with various enterprises.
The International Metabolic Engineering Society (IMES) defines metabolic engineering as the manipulation of metabolic pathways in microorganisms or cells to produce useful substances (such as pharmaceuticals, biofuels, and chemical products). It utilizes tools like systems biology, synthetic biology, and computational modeling with the aim of enhancing the economic viability and sustainability of bio-based processes.
Furthermore, Professor Lee previously received the Merck Metabolic Engineering Award, a prominent international award in the field, in 2008. In 2018, he was honored with the Eni Award, often referred to as the Nobel Prize in energy, presented by the President of Italy.
Professor Sang Yup Lee remarked, "Metabolic engineering is a discipline that leads the current and future of biotechnology. It is a tremendous honor to receive this meaningful award at a time when the transition to a bio-based economy is accelerating. Together with my students and fellow researchers, we have generated numerous patents and transferred technologies to industry, and also established startups in the fields of biofuels, wound healing, and cosmetics. I will continue to pursue research that encompasses both fundamental research and technological commercialization."
The 'International Metabolic Engineering Society (IMES)' is a specialized society under the American Institute of Chemical Engineers. Its mission is to enable the production of various bio-based products, including pharmaceuticals, food additives, chemicals, and fuels, through metabolic engineering. The society hosts the Metabolic Engineering Conference biennially, offering researchers opportunities for knowledge exchange and collaboration.
2025.06.20 View 2216 -
KAIST Develops Glare-Free, Heat-Blocking 'Smart Window'... Applicable to Buildings and Vehicles
• Professor Hong Chul Moon of the Department of Chemical and Biomolecular Engineering develops RECM, a next-generation smart window technology, expecting cooling energy savings and effective indoor thermal management.
• When using the developed RECM, a significantly superior temperature reduction effect is observed compared to conventional windows.
• With a 'pedestrian-friendly smart window' design that eliminates glare by suppressing external reflections, it is expected to be adapted in architectural structures, transportation, and more.
< (From left) First author Hoy Jung Jo, Professor Hong Chul Moon >
In the building sector, which accounts for approximately 40% of global energy consumption, heat ingress through windows has been identified as a primary cause of wasted heating and cooling energy. Our research team has successfully developed a 'pedestrian-friendly smart window' technology capable of not only reducing heating and cooling energy in urban buildings but also resolving the persistent issue of 'light pollution' in urban living.
On the 17th of June, Professor Hong Chul Moon's research team at KAIST's Department of Chemical and Biomolecular Engineering announced the development of a 'smart window technology' that allows users to control the light and heat entering through windows according to their intent, and effectively neutralize glare from external sources.
Recently, 'active smart window' technology, which enables free adjustment of light and heat based on user operation, has garnered significant attention. Unlike conventional windows that passively react to changes in temperature or light, this is a next-generation window system that can be controlled in real-time via electrical signals.
The next-generation smart window technology developed by the research team, RECM (Reversible Electrodeposition and Electrochromic Mirror), is a smart window system based on a single-structured *electrochromic device that can actively control the transmittance of visible light and near-infrared (heat).
*Electrochromic device: A device whose optical properties change in response to an electrical signal.
In particular, by effectively suppressing the glare phenomenon caused by external reflected light—a problem previously identified in traditional metal *deposition smart windows—through the combined application of electrochromic materials, a 'pedestrian-friendly smart window' suitable for building facades has been realized.
*Deposition: A process involving the electrochemical reaction to coat metal ions, such as Ag+, onto an electrode surface in solid form.
The RECM system developed in this study operates in three modes depending on voltage control.
Mode I (Transparent Mode) is advantageous for allowing sunlight to enter the indoor space during winter, as it transmits both light and heat like ordinary glass.
In Mode II (Colored Mode), *Prussian Blue (PB) and **DHV+• chemical species are formed through a redox (oxidation-reduction) reaction, causing the window to turn a deep blue color. In this state, light is absorbed, and only a portion of the heat is transmitted, allowing for privacy while enabling appropriate indoor temperature control.
*Prussian Blue: An electrochromic material that transitions between colorless and blue upon electrical stimulation.
**DHV+•: A radical state colored molecule generated upon electrical stimulation.
Mode III (Colored and Deposition Mode) involves the reduction and deposition of silver (Ag+) ions on the electrode surface, reflecting both light and heat. Concurrently, the colored material absorbs the reflected light, effectively blocking glare for external pedestrians.
The research team validated the practical indoor temperature reduction effect of the RECM technology through experiments utilizing a miniature model house. When a conventional glass window was installed, the indoor temperature rose to 58.7°C within 45 minutes. Conversely, when RECM was operated in Mode III, the temperature reached 31.5°C, demonstrating a temperature reduction effect of approximately 27.2°C.
Furthermore, since each state transition is achievable solely by electrical signals, it is regarded as an active smart technology capable of instantaneous response according to season, time, and intended use.
< Figure 1. Operation mechanism of the RECM smart window. The RECM system can switch among three states—transparent, colored, and colored & deposition—via electrical stimulation. At -1.6 V, DHV•+ and Prussian Blue (PB) are formed, blocking visible light to provide privacy protection and heat blocking. At -2.0 V, silver (Ag) is deposited on the electrode surface, reflecting light and heat, while DHV•+ and Prussian Blue absorb reflected light, effectively suppressing external glare. Through this mechanism, it functions as an active smart window that simultaneously controls light, heat, and glare. >
Professor Hong Chul Moon of KAIST, the corresponding author of this study, stated, "This research goes beyond existing smart window technologies limited to visible light control, presenting a truly smart window platform that comprehensively considers not only active indoor thermal control but also the visual safety of pedestrians." He added, "Various applications are anticipated, from urban buildings to vehicles and trains."
< Figure 2. Analysis of glare suppression effect of conventional reflective smart windows and RECM. This figure presents the results comparing the glare phenomenon occurring during silver (Ag) deposition between conventional reflective smart windows and RECM Mode III. Conventional reflective devices resulted in strong reflected light on the desk surface due to their high reflectivity. In contrast, RECM Mode III, where the colored material absorbed reflected light, showed a 33% reduction in reflected light intensity, and no reflected light was observed from outside. This highlights the RECM system's distinctiveness and practicality as a 'pedestrian-friendly smart window' optimized for dense urban environments, extending beyond just heat blocking. >
The findings of this research were published on June 13, 2025, in Volume 10, Issue 6 of 'ACS Energy Letters'. The listed authors for this publication are Hoy Jung Jo, Yeon Jae Jang, Hyeon-Don Kim, Kwang-Seop Kim, and Hong Chul Moon.
※ Paper Title: Glare-Free, Energy-Efficient Smart Windows: A Pedestrian-Friendly System with Dynamically Tunable Light and Heat Regulation
※ DOI: 10.1021/acsenergylett.5c00637
< Figure 3. Temperature reduction performance verification in a miniature model house. The actual heat blocking effect was evaluated by applying RECM devices to a model building. Under identical conditions, the indoor temperature with ordinary glass rose to 58.7°C, whereas with RECM in Mode III, it reached 31.5°C, demonstrating a maximum temperature reduction effect of 27.2°C. The indoor temperature difference was also visually confirmed through thermal images, which proves the potential for indoor temperature control in urban buildings. >
This research was supported by the Nano & Material Technology Development Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT and the internal research program of the Korea Institute of Machinery and Materials.
2025.06.20 View 4231 -
Simultaneous Analysis of 21 Chemical Reactions... AI to Transform New Drug Development
< Photo 1. (From left) Professor Hyunwoo Kim and students Donghun Kim and Gyeongseon Choi in the Integrated M.S./Ph.D. program of the Department of Chemistry >
Thalidomide, a drug once used to alleviate morning sickness in pregnant women, exhibits distinct properties due to its optical isomers* in the body: one isomer has a sedative effect, while the other causes severe side effects like birth defects. As this example illustrates, precise organic synthesis techniques, which selectively synthesize only the desired optical isomer, are crucial in new drug development. Overcoming the traditional methods that struggled with simultaneously analyzing multiple reactants, our research team has developed the world's first technology to precisely analyze 21 types of reactants simultaneously. This breakthrough is expected to make a significant contribution to new drug development utilizing AI and robots.
*Optical Isomers: A pair of molecules with the same chemical formula that are mirror images of each other and cannot be superimposed due to their asymmetric structure. This is analogous to a left and right hand, which are similar in form but cannot be perfectly overlaid.
KAIST's Professor Hyunwoo Kim's research team in the Department of Chemistry announced on the 16th that they have developed an innovative optical isomer analysis technology suitable for the era of AI-driven autonomous synthesis*. This research is the world's first technology to precisely analyze asymmetric catalytic reactions involving multiple reactants simultaneously using high-resolution fluorine nuclear magnetic resonance spectroscopy (19F NMR). It is expected to make groundbreaking contributions to various fields, including new drug development and catalyst optimization.
*AI-driven Autonomous Synthesis: An advanced technology that automates and optimizes chemical substance synthesis processes using artificial intelligence (AI). It is gaining attention as a core element for realizing automated and intelligent research environments in future laboratories. AI predicts and adjusts experimental conditions, interprets results, and designs subsequent experiments independently, minimizing human intervention in repetitive experiments and significantly increasing research efficiency and innovativeness.
Currently, while autonomous synthesis systems can automate everything from reaction design to execution, reaction analysis still relies on individual processing using traditional equipment. This leads to slower speeds and bottlenecks, making it unsuitable for high-speed repetitive experiments.
Furthermore, multi-substrate simultaneous screening techniques proposed in the 1990s garnered attention as a strategy to maximize reaction analysis efficiency. However, limitations of existing chromatography-based analysis methods restricted the number of applicable substrates. In asymmetric synthesis reactions, which selectively synthesize only the desired optical isomer, simultaneously analyzing more than 10 types of substrates was nearly impossible.
< Figure 1. Conventional organic reaction evaluation methods follow a process of deriving optimal reaction conditions using a single substrate, then expanding the substrate scope one by one under those conditions, leaving potential reaction areas unexplored. To overcome this, high-throughput screening is introduced to broadly explore catalyst reactivity for various substrates. When combined with multi-substrate screening, this approach allows for a much broader and more systematic understanding of reaction scope and trends. >
To overcome these limitations, the research team developed a 19F NMR-based multi-substrate simultaneous screening technology. This method involves performing asymmetric catalytic reactions with multiple reactants in a single reaction vessel, introducing a fluorine functional group into the products, and then applying their self-developed chiral cobalt reagent to clearly quantify all optical isomers using 19F NMR.
Utilizing the excellent resolution and sensitivity of 19F NMR, the research team successfully performed asymmetric synthesis reactions of 21 substrates simultaneously in a single reaction vessel and quantitatively measured the product yield and optical isomer ratio without any separate purification steps.
Professor Hyunwoo Kim stated, "While anyone can perform asymmetric synthesis reactions with multiple substrates in one reactor, accurately analyzing all the products has been a challenging problem to solve until now. We expect that achieving world-class multi-substrate screening analysis technology will greatly contribute to enhancing the analytical capabilities of AI-driven autonomous synthesis platforms."
< Figure 2. A method for analyzing multi-substrate asymmetric catalytic reactions, where different substrates react simultaneously in a single reactor, using fluorine nuclear magnetic resonance has been implemented. By utilizing the characteristics of fluorine nuclear magnetic resonance, which has a clean background signal and a wide chemical shift range, the reactivity of each substrate can be quantitatively analyzed. It is also shown that the optical activity of all reactants can be simultaneously measured using a cobalt metal complex. >
He further added, "This research provides a technology that can rapidly verify the efficiency and selectivity of asymmetric catalytic reactions essential for new drug development, and it is expected to be utilized as a core analytical tool for AI-driven autonomous research."
< Figure 3. It can be seen that in a multi-substrate reductive amination reaction using a total of 21 substrates, the yield and optical activity of the reactants according to the catalyst system were simultaneously measured using a fluorine nuclear magnetic resonance-based analysis platform. The yield of each reactant is indicated by color saturation, and the optical activity by numbers. >
Donghun Kim (first author, Integrated M.S./Ph.D. program) and Gyeongseon Choi (second author, Integrated M.S./Ph.D. program) from the KAIST Department of Chemistry participated in this research. The study was published online in the Journal of the American Chemical Society on May 27, 2025.※ Paper Title: One-pot Multisubstrate Screening for Asymmetric Catalysis Enabled by 19F NMR-based Simultaneous Chiral Analysis※ DOI: 10.1021/jacs.5c03446
This research was supported by the National Research Foundation of Korea's Mid-Career Researcher Program, the Asymmetric Catalytic Reaction Design Center, and the KAIST KC30 Project.
< Figure 4. Conceptual diagram of performing multi-substrate screening reactions and utilizing fluorine nuclear magnetic resonance spectroscopy. >
2025.06.16 View 2996 -
KAIST develops technology for selective RNA modification in living cells and animals
· A team led by Professor Won Do Heo from the Department of Biological Sciences, KAIST, has developed a pioneering technology that selectively acetylates specific RNA molecules in living cells and tissues.
· The platform uses RNA-targeting CRISPR tools in combination with RNA-modifying enzymes to chemically modify only the intended RNA.
· The method opens new possibilities for gene therapy by enabling precise control of disease-related RNA without affecting the rest of the transcriptome.
< Photo 1. (From left) Professor Won Do Heo and Jihwan Yu, a Ph.D. Candidate of the Department of Biological Sciences >
CRISPR-Cas13, a powerful RNA-targeting technology is gaining increasing attention as a next-generation gene therapy platform due to its precision and reduced side effects. Utilizing this system, researchers at KAIST have now developed the world’s first technology capable of selectively acetylating (chemically modifying) specific RNA molecules among countless transcripts within living cells. This breakthrough enables precise, programmable control of RNA function and is expected to open new avenues in RNA-based therapeutic development.
KAIST (President Kwang Hyung Lee) announced that a research team led by Professor Won Do Heo in the Department of Biological Sciences has recently developed a groundbreaking technology capable of selectively acetylating specific RNA molecules within the human body using the CRISPR-Cas13 system—an RNA-targeting platform gaining increasing attention in the fields of gene regulation and RNA-based therapeutics.
RNA molecules can undergo chemical modifications—the addition of specific chemical groups—which alter their function and behavior without changing the underlying nucleotide sequence. However, some of these modifications, a critical layer of post-transcriptional gene regulation, remain poorly understood. Among them, N4-acetylcytidine (ac4C) has been particularly enigmatic, with ongoing debate about its existence and function in human messenger RNA (mRNA), the RNA that encodes proteins.
To address this gap, the KAIST research team developed a targeted RNA acetylation system, named dCas13-eNAT10. This platform combines a catalytically inactive Cas13 enzyme (dCas13) that guides the system to specific RNA targets, with a hyperactive variant of the NAT10 enzyme (eNAT10), which performs RNA acetylation. This approach enables precise acetylation of only the desired RNA molecules among the vast pool of transcripts within the cell.
< Figure 1. Development of hyperactive variant eNAT10 through NAT10 protein engineering. By engineering the NAT10 protein, which performs RNA acetylation in human cells, based on its domain and structure, eNAT10 was developed, showing approximately a 3-fold increase in RNA acetylation activity compared to the wild-type enzyme. >
Using this system, the researchers demonstrated that guide RNAs could direct the dCas13-eNAT10 complex to acetylate specific RNA targets, and acetylation significantly increased protein expression from the modified mRNA. Moreover, the study revealed, for the first time, that RNA acetylation plays a role in intracellular RNA localization, facilitating the export of RNA from the nucleus to the cytoplasm—a critical step in gene expression regulation.
To validate its therapeutic potential, the team successfully delivered the targeted RNA acetylation system into the livers of live mice using adeno-associated virus (AAV), a commonly used gene therapy vector. This marks the first demonstration of in vivo RNA modification, extending the applicability of RNA chemical modification tools from cell culture models to living organisms.
< Figure 2. Acetylation of various RNA in cells using dCas13-eNAT10 fusion protein. Utilizing the CRISPR-Cas13 system, which can precisely target specific RNA through guide RNA, a dCas13-eNAT10 fusion protein was created, demonstrating its ability to specifically acetylate various endogenous RNA at different locations within cells. >
Professor Won Do Heo, who previously developed COVID-19 treatment technology using RNA gene scissors and technology to activate RNA gene scissors with light, stated, "Existing RNA chemical modification research faced difficulties in controlling specificity, temporality, and spatiality. However, this new technology allows selective acetylation of desired RNA, opening the door for accurate and detailed research into the functions of RNA acetylation." He added, "The RNA chemical modification technology developed in this study can be widely used as an RNA-based therapeutic agent and a tool for regulating RNA functions in living organisms in the future."
< Figure 3. In vivo delivery of targeted RNA acetylation system. The targeted RNA acetylation system was encoded in an AAV vector, commonly used in gene therapy, and delivered intravenously to adult mice, showing that target RNA in liver tissue was specifically acetylated according to the guide RNA. >
This research, with Ph.D. candidate Jihwan Yu from the Department of Biological Sciences at KAIST as the first author, was published in the journal Nature Chemical Biology on June 2, 2025. (Title: Programmable RNA acetylation with CRISPR-Cas13, Impact factor: 12.9, DOI: https://doi.org/10.1038/s41589-025-01922-3)
This research was supported by the Samsung Future Technology Foundation and the Bio & Medical Technology Development Program of the National Research Foundation of Korea.
2025.06.10 View 2489