Assoc. Prof. Mu, Yuguang
Apply AI tools to perform drug discovery researches, using small molecules and peptides/miniproteins, targeting protein as well as RNA molecules. More importantly, find novel drug targets through scRNAseq data.
Research Areas
AI drug discovery, virtual screening, molecular dynamics simulations
Chen Yue
Research Fellow
Research Fellow
Guan Jia Sheng
PhD Student
PhD Student
Le Tran Thao Vy
PhD Student
PhD Student
Liu Yunfeiyang
MSc Student
MSc Student
Rohan Shawn Sunil
PhD Student
PhD Student
Seetoh Wei Song
PhD Student
PhD Student
Sun Ao
PhD Student
PhD Student
Tan Laiheng
PhD Student
PhD Student
Wang Chuyi
MSc Student
MSc Student
Zhou Zhiyuan
PhD Student
PhD Student
- Wang, Z., Wang, S., Li, Y., Guo, J., Wei, Y., Mu, Y., Zheng, L., and Li, W. “A New Paradigm for Applying Deep Learning to Protein-Ligand Interaction Prediction.” Briefings in Bioinformatics 25, no. 3 (2024): 1–10. https://doi.org/10.1093/bib/bbae145
- Tan, L.H., Kwoh, C.K., and Mu, Y. “RmsdXNA: RMSD Prediction of Nucleic Acid-Ligand Docking Poses Using Machine-Learning Method.” Briefings in Bioinformatics 25, no. 3 (2024): 11–20. https://doi.org/10.1093/bib/bbae166
- Lam, H.Y.I., Pincket, R., Han, H., Ong, X.E., Wang, Z., Hinks, J., Wei, Y., Li, W., Zheng, L., and Mu, Y. “Application of Variational Graph Encoders as an Effective Generalist Algorithm in Computer-Aided Drug Design.” Nature Machine Intelligence 5, no. 7 (2023): 754–764. https://doi.org/10.1038/s42256-023-00683-9
- Chen, Z., Mu, Y., and Ren, C. “Concentration-Driven Evolution of Adaptive Artificial Ion Channels or Nanopores with Specific Anticancer Activities.” Angewandte Chemie-International Edition 63, no. 17 (2024): 1–10. https://doi.org/10.1002/anie.202318811
- Hiew, S.H., Lu, Y., Han, H., Gonçalves, R.A., Alfarano, S.R., Mezzenga, R., Parikh, A.N., Mu, Y., and Miserez, A. “Modulation of Mechanical Properties of Short Bioinspired Peptide Materials by Single Amino-Acid Mutations.” Journal of the American Chemical Society 145, no. 6 (2023): 3382–3393. https://doi.org/10.1021/jacs.2c09853