ipSAE
Calculate interface confidence metrics from a structure and PAE matrix.
Overview
Calculate inter-chain ipSAE, ipTM, pDockQ, pDockQ2, and LIS metrics from a complex structure, per-residue pLDDT scores, and a PAE matrix.
Run ipSAE on Neurosnap
The ipSAE online webserver allows anybody with a Neurosnap account to run and access ipSAE, 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
- Computes ipSAE and inter-chain ipTM metrics for every chain pair in a complex.
- Supports PAE payload alignment modes for auto, Boltz-2, Chai-1, and Protenix outputs.
- Can infer pLDDT from the input structure B-factor field when a separate pLDDT file is not supplied.
- Returns Chai-1/Boltz-2-style scores.csv and rank_1.json outputs for consistent result review.
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.
| Statistic | Value |
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| Credit Usage Rate | loading... |
| Estimated Total Cost | loading... |
| Runtime Mean | loading... |
| Runtime Median | loading... |
| Runtime Standard Deviation | loading... |
| Runtime 90th Percentile | loading... |
| Runtime Longest | loading... |
API Request
Access ipSAE 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 ipSAE in publications or research outputs.
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Bennett, N. R., Coventry, B., Goreshnik, I., Huang, B., Allen, A., Vafeados, D., Peng, Y. P., Dauparas, J., Baek, M., Stewart, L., DiMaio, F., De Munck, S., Savvides, S. N., & Baker, D. Improving de novo protein binder design with deep learning. Nature Communications. 2023. |
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Amani, Keaun, and Danial Gharaie Amirabadi. 2024. Neurosnap SDK Package. Software. https://github.com/NeurosnapInc/neurosnap. |
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Neurosnap Inc. (2022). Neurosnap: An online platform for computational biology and chemistry. Available at: https://neurosnap.ai/ |