NanoBinder: a machine learning assisted nanobody binding prediction tool using Rosetta energy scores
Abstract Nanobodies offer significant therapeutic potential due to their small size, stability, and versatility. Although advancements in computational protein design have made designing de novo nanobodies increasingly feasible, there are limited tools specifically tailored for this purpose. Rosetta...
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| Main Authors: | Palistha Shrestha, Chandana S. Talwar, Jeevan Kandel, Kwang-Hyun Park, Kil To Chong, Eui-Jeon Woo, Hilal Tayara |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-06-01
|
| Series: | Journal of Cheminformatics |
| Online Access: | https://doi.org/10.1186/s13321-025-01040-1 |
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