We've been working with our colleagues at IceKredit on an exciting project for the First Global AI Drug Design Competition sponsored by Baidu and Tsinghua University to help identify potential COVID-19 treatments. Using advanced machine learning, we developed a model that can predict whether new compounds might be effective against SARS-CoV-2.
What makes our approach special is that it looks at molecules from multiple angles - both the fine details of their structure and their broader chemical fingerprints. This multi-scale view helps us make more accurate predictions about which compounds are worth testing in the lab. This work builds on our recent publication in the Journal of Computer-Aided Molecular Design and shows how our computational methods can be applied to tackle urgent health challenges like the pandemic.
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I'm excited to share that our collaborative work with Professor Hui Wei's team at NJU-BME has been recognized with the RSC Horizons Dalton Prize. This interdisciplinary project focused on advancing our understanding of nanozymes and their potential applications.
Nanozymes are artificial nanomaterials that can act like natural enzymes - they catalyze reactions just like the biological enzymes in our bodies, but they're engineered rather than evolved. The potential applications are pretty exciting: these synthetic catalysts could be used to treat cancer and inflammation, and they're even being explored for wearable medical devices. Our research demonstrated that these designed nanozymes actually outperform natural enzymes in several key areas. The work also provided new insights into what factors control how effectively these artificial catalysts work - knowledge that will be crucial for designing even better nanozymes in the future. This recognition highlights both the innovative science and the successful international collaboration that made this research possible. It's a great example of how interdisciplinary partnerships can lead to breakthroughs with real-world biomedical applications. |
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June 2025
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