PocketXMol | Protein Design
Pocket-conditioned peptide generation and redesign.
Overview
PocketXMol Peptide Design is the peptide-focused PocketXMol workflow for receptor-conditioned peptide generation and redesign inside a protein binding pocket. It supports de novo peptide generation, cyclic peptide generation, inverse folding, and side-chain packing within one pocket-aware 3D modeling framework.
Run PocketXMol | Protein Design on Neurosnap
The PocketXMol | Protein Design online webserver allows anybody with a Neurosnap account to run and access PocketXMol | Protein Design, no downloads required. Information submitted through this webserver is kept confidential and never sold to third parties as detailed by our strong Terms of Use and Privacy Policy.
Features
- Supports de novo linear peptide generation against a receptor pocket.
- Supports de novo cyclic peptide generation.
- Supports peptide inverse folding and side-chain packing from a template structure.
- Uses the same pocket-conditioned 3D framework across peptide workflows.
Statistics
Neurosnap periodically calculates runtime statistics based on job execution data. These estimates provide a general guideline for how long your job may take, but actual runtimes can vary significantly depending on factors like input size or settings used.
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API Request
Access PocketXMol | Protein Design using the Neurosnap API by sending a request using any programming language with HTTP support. To safely generate an API key, visit the API tab of your overview page.
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Citations
Please cite the original work when using PocketXMol | Protein Design in publications or research outputs.
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Peng, X., Guo, R., Guo, F., Wang, Z., Sun, J., Guan, J., Jia, Y., Xu, Y., Huang, Y., Zhang, M., Peng, J., Wang, X., Han, C., Wang, Z., and Ma, J. Unified modeling of 3D molecular generation via atomic interactions with PocketXMol. Cell (2026). https://doi.org/10.1016/j.cell.2026.01.003 |
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Neurosnap Inc. (2022). Neurosnap: An online platform for computational biology and chemistry. Available at: https://neurosnap.ai/ |