• Period: July 2026 ~ Present

• Education

Mar 2022 ~ Present B.S., Convergent Bioscience and Informatics, Chungnam National University

• Project

(1) Deep Learning-based α2-Na/K-ATPase (α2NKA) Binder Design

• Summary

My research focuses on the structure-based computational design of inhibitors that selectively target a specific isoform of a therapeutically important membrane transport protein one enriched in astrocytes and implicated in neurodegenerative conditions such as Alzheimer’s disease with the aim of overcoming the isoform non-specificity that limits conventional therapeutics acting on this protein family and opening new avenues for precision pharmacological intervention in the central nervous system. Through an integrated structural bioinformatics pipeline comprising homology modeling, binding free-energy prediction, structural analysis, AI-based complex structure prediction, and binding-pocket identification, I have identified key residues governing isoform selectivity. Building on this foundation, I plan to design the binder as a cyclic peptide leveraging its enhanced structural rigidity and binding stability compared to linear peptides using generative protein design tools, followed by complex validation via AI-based structure prediction and binding-stability assessment through molecular dynamics simulations. This work aims to advance astrocyte-targeted therapeutic strategies for neurodegenerative disease at the intersection of structure-based drug design and AI-driven protein engineering.

• Contact: dbtjrwo1124@gmail.com