KAIST Researchers Develop AI-Engineered Interferon-Lambda Nasal Spray for Broad-Spectrum Respiratory Virus Protection
核心洞察
KAIST (搜索) researchers used artificial intelligence to re-engineer interferon-lambda (搜索) protein, creating a stable nasal spray that withstands 50°C for two weeks and reduces viral load by over 85% in animal models.
The AI-designed protein platform overcomes traditional limitations of interferon-lambda (搜索) therapeutics through structural modifications and advanced delivery technology using nanoliposomes (搜索) and chitosan coating.
The broad-spectrum antiviral platform offers potential for rapid response to seasonal flu and emerging viruses, with particular advantages for developing countries lacking cold chain infrastructure.
A South Korean research team at KAIST (搜索) has achieved a breakthrough in respiratory virus prevention by developing an AI-engineered nasal spray that demonstrates broad-spectrum antiviral activity. The innovative platform addresses critical limitations of existing interferon-lambda (搜索) therapeutics through artificial intelligence-guided protein design and advanced mucosal delivery technology.
AI-Driven Protein Engineering Overcomes Stability Challenges
The joint research team, led by Professors Kim Ho-min and Jeong Hyun-jeong of the Department of Life Sciences and Professor Oh Ji-eun of the Graduate School of Medical Science and Engineering, used AI technology to fundamentally redesign interferon-lambda (搜索) protein structure. Interferon-lambda is an innate immune protein that plays a crucial role in blocking respiratory viruses (搜索) such as the common cold, flu, and COVID-19 (搜索), but its therapeutic application has been limited by instability in heat, degrading enzymes, mucus, and ciliary movement.
The AI protein design technology identified a precise solution by replacing the protein's flexible, loose loop structure with a rigid, spring-like helical structure, significantly enhancing stability. The team further applied surface engineering to make the protein surface more hydrophilic and introduced glycoengineering technology, which adds glycan chains to the protein's surface for additional strengthening and stabilization.
Enhanced Delivery System Improves Mucosal Retention
Beyond protein engineering, the researchers developed an advanced delivery system by encapsulating the redesigned protein in nanoliposomes (搜索) and coating their surface with low-molecular-weight chitosan. This approach significantly improved mucoadhesion, allowing the therapeutic to adhere to the nasal mucosa for extended periods.
The resulting interferon-lambda (搜索) therapeutic demonstrated dramatically improved stability, withstanding temperatures of 50°C for two weeks while maintaining rapid diffusion properties even in viscous nasal mucosa.
Promising Preclinical Results Show Significant Viral Reduction
In influenza (搜索)-infected animal models, the delivery platform demonstrated powerful inhibitory effects, reducing viral load in the nasal cavity by more than 85%. The mucosal immune platform can block viral infections at early stages through simple nasal spray administration, positioning it as a potential therapeutic strategy for both seasonal flu and unexpected emerging viruses.
Clinical and Global Health Implications
Professor Kim Ho-min emphasized the platform's dual achievement: "We have simultaneously overcome the stability and retention time limitations of existing interferon-lambda (搜索) therapeutics through AI-based protein design and mucosal delivery technology." He highlighted the technology's potential utility in developing countries lacking robust cold chain infrastructure, noting its stability at high temperatures and extended mucosal retention.
The research represents significant interdisciplinary collaboration spanning AI protein design, drug delivery optimization, and immune evaluation through infection models. Dr. Yoon Jeong-won of the InnoCORE AI-Drug Discovery Research Center at KAIST (搜索), Dr. Yang Seung-joo of the Department of Life Sciences, and Ph.D. candidate Kwon Jae-hyeok participated as co-first authors.
The research findings were published in Advanced Science on the 20th and Biomaterials Research on the 21st of last month, marking a notable advancement in respiratory virus prevention technology that could address the rapid mutation and diversity challenges posed by respiratory pathogens like influenza (搜索) and COVID-19 (搜索).