Use FKSFold-Chai
Official Neurosnap webserver for accessing FKSFold-Chai online.
Overview
FKSFold-Chai extends Chai-1 with Feynman-Kac steering during diffusion to improve molecular-glue ternary complex prediction and other challenging co-folding cases. It keeps the Chai-1 biomolecular input model while adding particle-based resampling controls for steering generated structures toward stronger interface confidence.
Neurosnap Overview
The FKSFold-Chai online webserver allows anybody with a Neurosnap account to run and access FKSFold-Chai, 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
- Adds Feynman-Kac particle steering to the Chai-1 diffusion process.
- Targets molecular-glue ternary complex co-folding while preserving Chai-style biomolecular inputs.
- Supports interface-confidence, pLDDT, and mean-interface-pTM steering score choices.
- Exposes particle count, resampling interval, potential type, lambda weight, and sigma threshold controls.
- Keeps Chai-1 confidence outputs for ranked structure review.
- Useful for difficult induced-proximity systems where unconstrained co-folding may be ambiguous.
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 FKSFold-Chai 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 FKSFold-Chai in publications or research outputs.
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Shen, J., Zhou, S., & Che, X. (2025). FKSFold: Improving AlphaFold3-Type Predictions of Molecular Glue-Induced Ternary Complexes with Feynman-Kac-Steered Diffusion. bioRxiv. https://doi.org/10.1101/2025.05.03.651455 |
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Chai Discovery, Jacques Boitreaud, Jack Dent, Matthew McPartlon, Joshua Meier, Vinicius Reis, Alex Rogozhnikov, Kevin Wu bioRxiv 2024.10.10.615955; doi: https://doi.org/10.1101/2024.10.10.615955 |
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Abramson, J., Adler, J., Dunger, J. et al. Accurate structure prediction of biomolecular interactions with AlphaFold 3. Nature 630, 493–500 (2024). https://doi.org/10.1038/s41586-024-07487-w |
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Neurosnap Inc. (2022). Neurosnap: An online platform for computational biology and chemistry. Available at: https://neurosnap.ai/ |
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