Protein 3D Structure 단백질 3차 구조
In the 1950s, Max Perutz and John Kendrew at Cambridge University achieved the seemingly impossible by employing X-ray crystallography to decode the molecular structures of proteins. These breakthroughs sparked a revolution in structural biology and biochemistry. In the 2010s, technical advancements in Cryo-EM, including innovations in electron microscopy, image recording devices, and image processing algorithms, once again transformed structural biology. Cryo-EM now allows us to gain unprecedented insights into the complex details of proteins and their roles in biological processes at an atomic resolution. We are experiencing a new paradigm shift in structural biology as we enter the 2020s, thanks to artificial intelligence and deep-learning algorithms like AlphaFold and RoseTTAFold. These advanced technologies have enabled us to predict structures of the entire protein universe and have even allowed us to forecast the protein interactome, marking the beginning of a new age in structural biology.
What will come next, and what does the future hold?
Making Discoveries and Developments for Humanity & Society
in Collaboration with Artificial Intelligence
Protein Design 단백질디자인
The conventional approach to understanding proteins has been the "Sequence - > Structure - > Function" paradigm. However, scientists are now exploring the opposite direction. Rather than starting with a known sequence and uncovering its structure and function, we are addressing the question:
Given a specific function or trait that we aim to optimize, what protein structure and sequence are required?
This scientific inquiry coined Protein Design 단백질디자인
Recent advancements in the field of Protein Design have been made possible through the integration of Artificial Intelligence 인공지능. For example, the ProteinMPNN is a machine learning-based approach that generates protein sequences from an existing protein backbone scaffold. Another innovative technique is RF diffusion, which utilizes a generative AI model to craft de novo protein backbone scaffolds.
Research Interests 관심 연구
Our research group focuses on characterizing the structure of protein complexes involved in intercellular communication, such as cell-cell junctions and receptor-ligand interactions. Understanding the structural information of protein complexes can unveil their underlying molecular mechanisms, such as how proteins interact with each other, how they undergo conformational changes upon their interactions, and how they perform subsequent signaling. To achieve this, we utilize traditional molecular biology/biochemistry techniques along with two cutting-edge biophysical methods - X-ray crystallography and Single Particle Cryo-EM. Our lab facilitates protein expression and purification in various systems, including bacteria, insects, and mammalian cells.
Our laboratory has recently adopted the powerful Rosetta software and various AI-based approaches for protein modeling, docking, and design. We have also started working collaboratively with the "Data Science Group" at IBS and the "SketchLab" at the Department of Industrial Design, KAIST, to develop a cutting-edge tool for AI-based protein design. This collaboration leverages our expertise in structural biology and protein engineering with the proficiency of the Data Science Group and SketchLab in advanced digital technologies.
This expertise and experience position us to contribute significantly to Creating of novel Biomaterials for Medicine, Technology and Sustainability. Our focus extends to the Modulation of Inter-cellular Communication and Cellular Responses, including but not limited to angiogenesis, lymphangiogenesis, synaptogenesis, neurogenesis, and immune response. By accelerating the discovery of potent new therapeutics through our innovative approaches, we anticipate making meaningful strides in the near future. Also, we hope our commitment to integrating diverse disciplines and pushing the boundaries of protein design underscores our dedication to advancing scientific knowledge.
Immune Response & Infectious Disease
Pathogen-associated Molecular Pattern & TLR
- KIm HM and Kim YM, Immunity, 2018
- Kim SY et al., Nature Communications, 2017
- Kim SJ and Kim HM., BMB Reports, 2017
- Ryu JK et al., Immunity, 2017
- Park BS et al., Nature, 2009
- Jung K et al., PLos One, 2009
- Kim HM et al., Cell, 2007
- Jin MS et al., Cell, 2007
Interferon & IFN Receptor
Chung JH et al., Cytokine, 2020
Sung PS et al., Scientific Reports, 2017
BAFF & BAFFR, CD40L & CD40
An HJ et al., J Biol Chem, 2011
Lee KE et al., Colloids Surf B Biointerfaces. 2008
Kim HM et al., Nature Structural Biology, 2003
Angiogenesis & Lymphangiogenesis
Angiopoietin & Tie Receptor
- Jo G et al., Nature Communications, 2021
- Yin GN et al., Diabetes, 2018
- Oh N et al., Scientific Reports, 2015
- Koh YJ et al., Cancer Cell, 2010
- Kim HZ et al., BBA, 2009
VEGF & VEGFR
- Kim DK et al., Nature Communications. 2022
- Lee DH et al., Biomaterials, 2018
- Hong HK et al., IOVS, 2020
- Joo K et al., IOVS, 2017
- Lee J et al., Mol Cancer Ther, 2015
LRG1 & TGFR, LPHN
- Yang et al., Experimental & Molecular Medicine. 2023
- Yin et al., Experimental & Molecular Medicine, 2022
Synaptogenesis & Nerve Regeneration
LAR-RPTP & Slitrk, IL1RAPL1, IL-1RAcP
- Won SY and Kim HM, Mol Cells, 2018
- Won SY et al., Frontiers in Molecular Neuroscience. 2017
- Lie E et al., Nature Communications, 2016
- Um JW et al., Nature Communications, 2014
Neurexin, Neuroligin & MDGA
- Kim JA et al., Neuron, 2017
LRG1 & TGFR, LPHN
- Yang et al., Experimental & Molecular Medicine. 2023
- Yin et al., Experimental & Molecular Medicine, 2022
Metabolism & Growth
IGF/IFGBP/ALS & IGFR
- Kim H et al., Nature Communications, 2022
GDF15 & GFRAL, RET
- GFRAL을 표적으로 하는 단일클론 항체 및 이의 용도 (대한민국, 특허 출원)
- hGFRAL 표적 단일클론항체-ASO 복합체 (대한민국, 특허출원)
LRG1 & TGFR, LPHN
- Yang JM et al., Experimental & Molecular Medicine, 2023
- Yin GN et al., Experimental & Molecular Medicine, 2023
Drug Development
Cancer
- Kim DK et al., Nature Communications. 2022
- Jang S et al., Biomaterials, 2021
- Lee DH et al., Biomaterials, 2018
- Kim YR et al., Theranostics, 2015
- Lee J et al. Molecular Cancer Therapeutics, 2015
Macular & Eye Disease
- Jo G et al., Nature Communications, 2021
- Hong HK et al., IOVS, 2020
- Joo K et al., IOVS, 2017
- Park SJ et al., Eye, 2015