< 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."
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, a world-renowned international academic journal in chemistry, 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. >
Chemical reaction
AI
Artificial intelligence
Isomer
Asymmetric catalytic reaction
Simultaneous analysis
Nuclear magnetic resonance spectrometer
