DynamicBind
Predict protein-ligand complexes using protein structure files and ligands in SMILES format.
Overview
DynamicBind uses a deep equivariant generative model to predict ligand-specific protein-ligand complex structures. It works with unbound protein structures, including AlphaFold models, and requires only ligand SMILES and protein structure to predict complex structures.
Run DynamicBind on Neurosnap
The DynamicBind online webserver allows anybody with a Neurosnap account to run and access DynamicBind, 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
- Employs a deep equivariant generative model to predict ligand-specific protein-ligand complex structures.
- Works with unbound protein structures, including AlphaFold models.
- Requires only ligand SMILES and protein structure to predict complex structures.
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 DynamicBind 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 DynamicBind in publications or research outputs.
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Wei, L. et al. "DynamicBind: predicting ligand-specific protein-ligand complex structure with a deep equivariant generative model", https://nature.com, 05 February 2024, https://www.nature.com/articles/s41467-024-45461-2. |
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Neurosnap Inc. (2022). Neurosnap: An online platform for computational biology and chemistry. Available at: https://neurosnap.ai/ |