Aggrescan3D
Structure-based aggregation profiling with Aggrescan3D
Overview
Identify and quantify aggregation-prone regions in structured proteins with atomic precision using Aggrescan3D. This structure-based pipeline projects intrinsic aggregation propensities onto user-defined 3D models, leveraging a refined Aggrescan algorithm to pinpoint solvent-exposed hotspots and guide solubility assessment for therapeutic and biotechnological applications.
Run Aggrescan3D on Neurosnap
The Aggrescan3D online webserver allows anybody with a Neurosnap account to run and access Aggrescan3D, 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
- Projects aggregation scores onto protein structures using the Aggrescan scale, analyzing residues in user-provided 3D models.
- Uses spherical modeling around carbon-alpha atoms to assess how nearby residues and solvent exposure affect aggregation tendency.
- Identifies aggregation-prone regions by focusing on surface-exposed areas while excluding buried hydrophobic residues.
- Performs better than sequence-based prediction methods when analyzing naturally folded proteins.
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 Aggrescan3D 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 Aggrescan3D in publications or research outputs.
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Aleksander Kuriata, Valentin Iglesias, Jordi Pujols, Mateusz Kurcinski, Sebastian Kmiecik, Salvador Ventura, Aggrescan3D (A3D) 2.0: prediction and engineering of protein solubility, Nucleic Acids Research, Volume 47, Issue W1, 02 July 2019, Pages W300–W307, https://doi.org/10.1093/nar/gkz321 |
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Neurosnap Inc. (2022). Neurosnap: An online platform for computational biology and chemistry. Available at: https://neurosnap.ai/ |