SpatialPPIv2 Protein Interaction Prediction
Predict protein-protein interaction probability from paired structures or sequences.
Overview
SpatialPPIv2 predicts whether a pair of proteins is likely to interact using protein language model embeddings and graph attention networks. The tool supports structure-based inference from PDB or mmCIF files, and sequence-only inference from amino-acid FASTA-style inputs when structures are unavailable.
Run SpatialPPIv2 Protein Interaction Prediction on Neurosnap
The SpatialPPIv2 Protein Interaction Prediction online webserver allows anybody with a Neurosnap account to run and access SpatialPPIv2 Protein Interaction Prediction, 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
- Predicts pairwise protein-protein interaction probability for two submitted proteins.
- Uses structure-aware ProtT5 inference when PDB or mmCIF structures are available.
- Supports sequence-only inference with ESM-2 attention-contact graphs when structures are unavailable.
- Returns a compact CSV summary with interaction probability, thresholded label, chain selections, and input lengths.
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 SpatialPPIv2 Protein Interaction Prediction 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 SpatialPPIv2 Protein Interaction Prediction in publications or research outputs.
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Hu W, Ohue M. SpatialPPIv2: Enhancing protein-protein interaction prediction through graph neural networks with protein language models. Computational and Structural Biotechnology Journal. 2025;27:508-518. https://doi.org/10.1016/j.csbj.2025.01.022 |
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Neurosnap Inc. (2022). Neurosnap: An online platform for computational biology and chemistry. Available at: https://neurosnap.ai/ |