KAIST Proposes a New Dementia Treatment Strategy by Repositioning Molecules without Changing Their Chemical Composition
<(Back row, from left) Professor Mi Hee Lim, Professor Mingeun Kim, Student Jimin Lee, Student Chanju Na, (Upper Right) Dr. Chul-Ho Lee, Dr Kyoung-Shim Kim>
Conventional treatments of Alzheimer’s disease, one of the most common forms of dementia, have been largely focused on targeting individual pathological features. However, Alzheimer’s disease is a multifactorial disorder driven by multiple, tightly interconnected processes, rendering single-target therapeutic approaches inherently limited. Addressing this challenge, KAIST researchers propose a new strategy that enables the simultaneous regulation of multiple disease-inducing factors simply by rearranging the structural positions of drug candidate molecules without altering their chemical substituents.
KAIST (President Kwang Hyung Lee) announced on January 22 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 of the Korea Research Institute of Bioscience and Biotechnology (KRIBB), and Dr. Kyoung-Shim Kim of the Laboratory Animal Resource Center, has elucidated at the molecular level how subtle differences in molecular arrangement, specifically positional isomerism, give rise to distinct modes of action against Alzheimer’s disease.
Using an Alzheimer’s disease mouse model (APP/PS1) harboring human dementia-associated genes, the research team demonstrated that these compounds also exert distinct therapeutic effects in vivo.
Alzheimer’s disease does not arise from a single cause. Rather, multiple pathological factors, including amyloid-b, metal ions, and reactive oxygen species, interact synergistically to exacerbate disease progression. In particular, metal ions bind to amyloid-b, modulating its aggregation and toxicity while promoting the generation of reactive oxygen species, which in turn accelerates neuronal damage. Effective control of Alzheimer’s disease therefore requires therapeutic strategies capable of simultaneously targeting multiple interrelated pathological processes.
< Alzheimer’s Disease – Chemical Approach Illustration (AI-generated image) >
The researchers focused on positional isomers, molecules composed of the same chemical elements but differing only in the positions at which those elements are connected. Remarkably, simple changes in molecular positioning resulted in pronounced differences in reactivity towards reactive oxygen species, as well as in interactions with amyloid-b and metal-bound amyloid-b.
To investigate these effects, the team compared the reactivities of three structurally similar molecules differing only in the positions of their functional groups. Their analyses revealed that even minimal structural rearrangements led to significant differences in antioxidant capacity and produced distinct modes of modulation of amyloid-b and metal-bound amyloid-b through different mechanisms, inducing peptide chemical modifications.
In other words, the study demonstrated that Alzheimer’s disease-related pathological factors can be regulated through mechanistically distinct pathways simply by altering molecular arrangement, without changing molecular composition.
Notably, a specific positional isomer capable of simultaneously modulating reactive oxygen species, amyloid-b, and metal-bound amyloid-b complexes also demonstrated therapeutic efficacy in an Alzheimer’s disease mouse model. In these experiments, the compound reduced oxidative stress in the hippocampus, the brain region critical for memory, and decreased amyloid plaque accumulation, resulting in significant improvements in memory deficits and cognitive impairment.
< In Vivo Efficacy Evaluation and Biological Outcomes According to Positional Isomers of Small-Molecule Compounds >
Professor Mi Hee Lim of KAIST stated, “This study demonstrates that multiple pathological factors associated with Alzheimer’s disease can be targeted simultaneously simply by adjusting molecular positioning, without altering the molecule’s core chemical framework.” She added, “These findings point to a new therapeutic strategy that may enable more precise control of complex, multifactorial diseases such as Alzheimer’s disease.”
This research was conducted with Chanju Na and Jimin Lee, integrated master’s-doctoral students in the Department of Chemistry at KAIST, who served as co-first authors. The results were published in the Journal of the American Chemical Society (Impact Factor: 15.7, top 5.0% in Chemistry) in Issue 1 dated January 14, 2026.
※ Paper title: “Positional Isomerism Tunes Molecular Reactivities and Mechanisms toward Pathological Targets in Dementia”
※ DOI: 10.1021/jacs.5c14323
This study was supported by the National Research Foundation (NRF) of Korea through the Basic Research Program (Creative Research Initiative and Global Science Research Center), the NRF Sejong Science Fellowship, the NRF Ph.D. Followship, and KRIBB Institutional Funding.
KAIST Unveils Cause of Performance Degradation in Electric Vehicle High-Nickel Batteries: "Added with Good Intentions
<(From left in the front row) Professor Nam-Soon Choi, Professor Dong-Hwa Seo, (back row, from left) Ph.D candidate Gihoon Lee, Ph.D candidate Seung Hee Han, Ph.D candidate Jae-Seung Kim, (top) M.S candidate Junyoung Kim>
High-nickel batteries, which are high-energy lithium-ion batteries primarily used in electric vehicles, offer high energy density but suffer from rapid performance degradation. A research team from KAIST has, for the first time globally, identified the fundamental cause of the rapid deterioration (degradation) of high-nickel batteries and proposed a new approach to solve it.
KAIST announced on December 3rd that a research team led by Professor Nam-Soon Choi of the Department of Chemical and Biomolecular Engineering, in collaboration with a research team led by Professor Dong-Hwa Seo of the Department of Materials Science and Engineering, has revealed that the electrolyte additive 'succinonitrile (CN4), which has been used to improve battery stability and lifespan, is actually the key culprit causing performance degradation in high-nickel batteries.
In a battery, electricity is generated as lithium ions travel between the cathode and the anode. A small amount of CN4 is included in the electrolyte to facilitate the movement of lithium. The research team confirmed through computer calculations that CN4, which has two nitrile (-CN) structures, attaches excessively strongly to the nickel ions on the surface of the high-nickel cathode.
The nitrile structure is a 'hook-like' structure, where carbon and nitrogen are bound by a triple bond, making it adhere well to metal ions. This strong bonding destroys the protective electrical double layer (EDL) that should form on the cathode surface. During the charging and discharging process, the cathode structure is distorted (Jahn-Teller distortion), and even electrons from the cathode are drawn out to the CN4, leading to rapid damage of the cathode.
Nickel ions that leak out during this process migrate through the electrolyte to the anode surface, where they accumulate. This nickel acts as a 'bad catalyst' that accelerates electrolyte decomposition and wastes lithium, further speeding up battery degradation.
Various analyses confirmed that CN4 transforms the high-nickel cathode surface into an abnormal layer deficient in nickel, and changes the normally stable structure into an abnormal 'rock-salt structure'.
This proves the dual nature of CN4: while useful in LCO batteries (lithium cobalt oxide), it actually causes the structural collapse in high-nickel batteries with a high nickel ratio.
This research holds significant meaning as a precise analysis that goes beyond simple control of charging/discharging conditions, to even elucidating the actual electron transfer occurring between metal ions and electrolyte molecules. Based on this achievement, the research team plans to develop a new electrolyte additive optimized for high-nickel cathodes.
<Schematic diagram of the ligand coordination between CN₄ molecules and Ni³⁺ on the high-nickel cathode surface and the cathode structural degradation process>
Professor Nam-Soon Choi stated, "A precise, molecular-level understanding is essential to enhance battery lifespan and stability. This research will pave the way for the development of new additives that do not excessively bond with nickel, significantly contributing to the commercialization of next-generation high-capacity batteries."
This research, jointly led by Professor Nam-Soon Choi, Seung Hee Han, Junyoung Kim, and Gihoon Lee of the Department of Chemical and Biomolecular Engineering, and Professor Dong-Hwa Seo and Jae-Seung Kim of the Department of Materials Science and Engineering as co-first authors, was published online on November 14th in the prestigious international journal 'ACS Energy Letters' and was selected as the cover article.
※ Paper Title: Unveiling Bidentate Nitrile-Driven Structural Degradation in Ultra-High-Nickel Cathodes,
https://doi.org/10.1021/acsenergylett.5c02845
<Cover Page of International Journal(ACS Energy Letters)>
The research was supported by Samsung SDI.
Reborn as an Artificial Enzyme to Protect the Environment and Health
<(From left) Dr. Neetu Singh, Ph.D candidate Haneul Im, Dr. Seongyeon Kwon (IBS) (Back) Professor YunJung Baek>
Vitamin B2 (riboflavin), which we consume, acts as an important coenzyme that helps food convert into energy within the body. Korean researchers have successfully created a new artificial enzyme for the first time in the world by combining this riboflavin (flavin) with metal, adding the metal's reaction-controlling ability to riboflavin's electron-transfer function. This technology is expected to operate more precisely and stably than natural enzymes, demonstrating potential for use in various fields such as energy production, environmental purification, and new drug development.
The research team led by Professor Yunjung Baek of KAIST Department of Chemistry, in collaboration with Dr. Seongyeon Kwon of the Institute for Basic Science, announced on the 11th of November that they have succeeded in synthesizing a new molecular system that allows flavin to bind with metal ions.
Until now, scientists have long been unable to realize "flavin combined with metal" because flavin has a structural limitation—a complex ring structure entangled with nitrogen and oxygen—which makes it difficult for a metal to selectively bind.
To overcome this limitation, the research team designed a binding site for the metal within the flavin at the molecular level and applied a metallochemical approach that precisely arranges the ligand structure that traps the metal.
Through this, they successfully and stably synthesized the flavin-metal complex by delicately controlling the electronic and spatial interactions around the metal.
This achievement is the first case that integrates flavin's inherent properties and metal's reactivity into a single system, opening up the possibility for the development of 'metal-based artificial enzymes' that finely tune chemical reactions.
Professor Yunjung Baek stated, "We have moved beyond the limitations of naturally occurring flavin and expanded a biomolecule into a new component of metallochemistry. This research suggests a new direction for the design of next-generation catalysts and energy conversion materials based on biomolecules."
This achievement, in which Dr. Neetu Singh and Ph.D candidate Haneul Im of KAIST Department of Chemistry participated as co-first authors, was published in the international journal Inorganic Chemistry, issued by the American Chemical Society (ACS), on November 5th. It was recognized for its creativity and completeness and was selected as the cover article. Furthermore, it was chosen as an ACS Editors’ Choice—a representative paper selected once a day from all 90+ journals published by ACS—acknowledging the importance of the research.
Article Title: Tautomerizable Flavin Ligands for Constructing Primary and Secondary Coordination Spheres, DOI: 10.1021/acs.inorgchem.5c03941
Author Information: Total 5 authors including Neetu Singh (KAIST, Co-first Author), Haneul Im (KAIST, Co-first Author), Seongyeon Kwon (IBS, Co-second Author), Dongwook Kim (IBS, Co-third Author), and Yunjung Baek (KAIST, Corresponding Author).
<Cover Article Selection Photo for Inorganic Chemistry, an International Academic Journal Published by the American Chemical Society>
This research was supported by the 'Excellent New Researcher' project of the Basic Research Program for Individuals funded by the Ministry of Science and ICT, and the 'Materials and Components Development Program' supported by the Ministry of Trade, Industry and Energy.
Chemobiological Platform Enables Renewable Conversion of Sugars into Core Aromatic Hydrocarbons of Petroleum
<(From Left) Professor Sun Kyu Han, Ph.D candidate Tae Wan Kim, Professor Kyeong Rok Choi, Professor Sang Yup Lee>
With growing concerns over fossil fuel depletion and the environmental impacts of petrochemical production, scientists are actively exploring renewable strategies to produce essential industrial chemicals. A collaborative research team—led by Distinguished Professor Sang Yup Lee, Senior Vice President for Research, from the Department of Chemical and Biomolecular Engineering, together with Professor Sunkyu Han from the Department of Chemistry at the Korea Advanced Institute of Science and Technology (KAIST)—has developed an integrated chemobiological platform that converts renewable carbon sources such as glucose and glycerol into oxygenated precursors, which are subsequently deoxygenated in the same solvent system to yield benzene, toluene, ethylbenzene, and p-xylene (BTEX), which are fundamental aromatic hydrocarbons used in fuels, polymers, and consumer products.
<Figure 1. Schematic representation of the chemobiological synthesis of BTEX from glucose or glycerol in Escherichia coli>
From Sugars to Aromatic Hydrocarbons of Petroleum
The researchers designed four metabolically engineered strains of Escherichia coli, each programmed to produce a specific oxygenated precursor—phenol, benzyl alcohol, 2-phenylethanol, or 2,5-xylenol. These intermediates are generated through tailored genetic modifications, such as deletion of feedback-regulated enzymes, overexpression of pathway-specific genes, and introduction of heterologous enzymes to expand metabolic capabilities.
During fermentation, the products were continuously extracted into the organic solvent isopropyl myristate (IPM). Acting as a dual-function solvent, IPM not only mitigated the toxic effects of aromatic compounds on cell growth but also served directly as the reaction medium for downstream chemical upgrading. By eliminating the need for intermediate purification, solvent exchange, or distillation, this solvent-integrated system streamlined the conversion of renewable feedstocks into valuable aromatics.
Overcoming Chemical Barriers in An Unconventional Solvent
A central innovation of this work lies in adapting chemical deoxygenation reactions to function efficiently within IPM—a solvent rarely used in organic synthesis. Traditional catalysts and reagents often proved ineffective under these conditions due to solubility limitations or incompatibility with biologically derived impurities.
Through systematic optimization, the team established mild and selective catalytic strategies compatible with IPM. For example, phenol was successfully deoxygenated to benzene in up to 85% yield using a palladium-based catalytic system, while benzyl alcohol was efficiently converted to toluene after activated charcoal pretreatment of the IPM extract. More challenging transformations, such as converting 2-phenylethanol to ethylbenzene, were achieved through a mesylation–reduction sequence adapted to the IPM phase. Likewise, 2,5-xylenol derived from glycerol was converted to p-xylene in 62% yield via a two-step reaction, completing the renewable synthesis of the full BTEX spectrum.
A Sustainable, Modular Framework
Beyond producing BTEX, the study establishes a generalizable framework for integrating microbial biosynthesis with chemical transformations in a continuous solvent environment. This modular approach reduces energy demand, minimizes solvent waste, and enables process intensification—key factors for scaling up renewable chemical production.
The high boiling point of IPM (>300 °C) simplifies product recovery, as BTEX compounds can be isolated by fractional distillation while the solvent is readily recycled. Such a design is consistent with the principles of green chemistry and the circular economy, providing a practical alternative to fossil-based petrochemical processes.
Toward A Carbon-Neutral Future
Dr. Xuan Zou, the first author of this paper, explaind, “By coupling the selectivity of microbial metabolism with the efficiency of chemical catalysis, this platform establishes a renewable pathway to some of the most widely used building blocks in the chemical industry. Future efforts will focus on optimizing metabolic fluxes, extending the platform to additional aromatic targets, and adopting greener catalytic systems.”
In addition, Distinguished Professor Sang Yup Lee noted “As the global demand for BTEX and related chemicals continues to grow, this innovation provides both a scientific and industrial foundation for reducing reliance on petroleum-based processes. It marks an important step toward lowering the carbon footprint of the fuel and chemical sectors while ensuring a sustainable supply of essential aromatic hydrocarbons.”
This research was supported by the Development of Platform Technologies of Microbial Cell Factories for the Next-Generation Biorefineries Project (2022M3J5A1056117) and the Development of Advanced Synthetic Biology Source Technologies for Leading the Biomanufacturing Industry Project (RS-2024-00399424), funded by the National Research Foundation supported by the Korean Ministry of Science and ICT. This study was published in the latest issue of the Proceedings of the National Academy of Sciences of the United States of America (PNAS).
World's First Quantum Computing for Lego-like Design of Porous Materials
<(From Left to Right)Professor Jihan Kim, Ph.D. candidate Sinyoung Kang, Ph.D. candidate Younghoon Kim from the Department of Chemical and Biomolecular Engineering>
Multivariate Porous Materials (MTV) are like a 'collection of Lego blocks,' allowing for customized design at a molecular level to freely create desired structures. Using these materials enables a wide range of applications, including energy storage and conversion, which can significantly contribute to solving environmental problems and advancing next-generation energy technologies. Our research team has, for the first time in the world, introduced quantum computing to solve the difficult problem of designing complex MTVs, opening an innovative path for the development of next-generation catalysts, separation membranes, and energy storage materials.
On September 9, Professor Jihan Kim's research team at our university's Department of Chemical and Biomolecular Engineering announced the development of a new framework that uses a quantum computer to efficiently explore the design space of millions of multivariate porous materials (hereafter, MTV).
MTV porous materials are structures formed by the combination of two or more organic ligands (linkers) and building block materials like metal clusters. They have great potential for use in the energy and environmental fields. Their diverse compositional combinations llow for the design and synthesis of new structures. Examples include gas adsorption, mixed gas separation, sensors, and catalysts.
However, as the number of components increases, the number of possible combinations grows exponentially. It has been impossible to design and predict the properties of complex MTV structures using the conventional method of checking every single structure with a classical computer.
The research team represented the complex porous structure as a 'network (graph) drawn on a map' and then converted each connection point and block type into qubits that a quantum computer can handle. They then asked the quantum computer to solve the problem: "Which blocks should be arranged at what ratio to create the most stable structure?"
<Figure1. Overall schematics of the quantum computing algorithm to generate feasible MTV porous materials. The algorithm consists of two mapping schemes (qubit mapping and topology mapping) to allocate building blocks in a given connectivity. Different configurations go through a predetermined Hamiltonian, which is comprised of a ratio term, occupancy term, and balance term, to capture the most feasible MTV porous material>
Because quantum computers can calculate multiple possibilities simultaneously, it's like spreading out millions of Lego houses at once and quickly picking out the sturdiest one. This allows them to explore a vast number of possibilities—which a classical computer would have to calculate one by one—with far fewer resources.
The research team also conducted experiments on four different MTV structures that have been previously reported. The results from the simulation and the IBM quantum computer were identical, demonstrating that the method "actually works well."
<Figure2. VQE sampling results for experimental structures and the structures that reproduce them, using IBM Qiskit's classical simulator. The experimental structure is predicted to be the most probable outcome of the VQE algorithm's calculation, meaning it will be generated as the most stable form of the structure.>
In the future, the team plans to combine this method with machine learning to expand it into a platform that considers not only simple structural design but also synthesis feasibility, gas adsorption performance, and electrochemical properties simultaneously.
Professor Jihan Kim said, "This research is the first case to solve the bottleneck of complex multivariate porous material design using quantum computing." He added, "This achievement is expected to be widely applied as a customized material design technology in fields where precise composition is key, such as carbon capture and separation, selective catalytic reactions, and ion-conducting electrolytes, and it can be flexibly expanded to even more complex systems in the future."
Ph.D. candidates Sinyoung Kang and Younghoon Kim of the Department of Chemical and Biomolecular Engineering participated as co-first authors in this study. The research results were published in the online edition of the international journal ACS Central Science on August 22.
Paper Title: Quantum Computing Based Design of Multivariate Porous Materials
DOI: https://doi.org/10.1021/acscentsci.5c00918
Meanwhile, this research was supported by the Ministry of Science and ICT's Mid-Career Researcher Support Program and the Heterogeneous Material Support Program.
Batteries Make 12Minute Charge for 800km Drive a Reality
<Photo 1. (From left in the front row) Dr. Hyeokjin Kwon from Chemical and Biomolecular Engineering, Professor Hee Tak Kim, and Professor Seong Su Kim from Mechanical Engineering>
Korean researchers have ushered in a new era for electric vehicle (EV) battery technology by solving the long-standing dendrite problem in lithium-metal batteries. While conventional lithium-ion batteries are limited to a maximum range of 600 km, the new battery can achieve a range of 800 km on a single charge, a lifespan of over 300,000 km, and a super-fast charging time of just 12 minutes.
KAIST (President Kwang Hyung Lee) announced on the 4th of September that a research team from the Frontier Research Laboratory (FRL), a joint project between Professor Hee Tak Kim from the Department of Chemical and Biomolecular Engineering, and LG Energy Solution, has developed a "cohesion-inhibiting new liquid electrolyte" original technology that can dramatically increase the performance of lithium-metal batteries.
Lithium-metal batteries replace the graphite anode, a key component of lithium-ion batteries, with lithium metal. However, lithium metal has a technical challenge known as dendrite, which makes it difficult to secure the battery's lifespan and stability. Dendrites are tree-like lithium crystals that form on the anode surface during battery charging, negatively affecting battery performance and stability.
This dendrite phenomenon becomes more severe during rapid charging and can cause an internal short-circuit, making it very difficult to implement a lithium-metal battery that can be recharged under fast-charging conditions.
The FRL joint research team has identified that the fundamental cause of dendrite formation during rapid charging of lithium metal is due to non-uniform interfacial cohesion on the surface of the lithium metal. To solve this problem, they developed a "cohesion-inhibiting new liquid electrolyte."
The new liquid electrolyte utilizes an anion structure with a weak binding affinity to lithium ions (Li⁺), minimizing the non-uniformity of the lithium interface. This effectively suppresses dendrite growth even during rapid charging.
This technology overcomes the slow charging speed, which was a major limitation of existing lithium-metal batteries, while maintaining high energy density. It enables a long driving range and stable operation even with fast charging.
Je-Young Kim, CTO of LG Energy Solution, said, "The four years of collaboration between LG Energy Solution and KAIST through FRL are producing meaningful results. We will continue to strengthen our industry-academia collaboration to solve technical challenges and create the best results in the field of next-generation batteries."
<Figure 1. Infographic on the KAIST-LGES FRL Lithium-Metal Battery Technology>
Hee Tak Kim, Professor from Chemical and Biomolecular Engineering at KAIST, commented, "This research has become a key foundation for overcoming the technical challenges of lithium-metal batteries by understanding the interfacial structure. It has overcome the biggest barrier to the introduction of lithium-metal batteries for electric vehicles."
The study, with Dr. Hyeokjin Kwon from the KAIST Department of Chemical and Biomolecular Engineering as the first author, was published in the prestigious journal Nature Energy on September 3.
Nature Energy: According to the Journal Impact Factor announced by Clarivate Analytics in 2024, it ranks first among 182 energy journals and 23rd among more than 21,000 journals overall.
Article Title: Covariance of interphasic properties and fast chargeability of energy-dense lithium metal batteries
DOI: 10.1038/s41560-025-01838-1
The research was conducted through the Frontier Research Laboratory (FRL, Director Professor Hee Tak Kim), which was established in 2021 by KAIST and LG Energy Solution to develop next-generation lithium-metal battery technology.
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.
KAIST Takes the Lead in Developing Core Technologies for Generative AI National R&D Project
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.
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.
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."
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.
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.
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.
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).