TianZhuAI4S/DiffAffinity
Predicting mutational effects on protein-protein binding via a side-chain diffusion probabilistic model (NeurIPS 2023 Poster)
This tool helps scientists in drug discovery or protein engineering understand how specific changes in a protein's sequence might affect its ability to bind to other proteins. You input the structure of a protein complex and details about potential mutations. It then predicts the change in binding affinity, which is crucial for tasks like designing more effective therapeutic proteins or vaccines, or understanding disease mechanisms. It's intended for researchers working with protein structures and interactions.
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Use this if you need to computationally predict how a single amino acid mutation will alter the binding strength between two proteins.
Not ideal if you are not working with protein structures or do not have experimental protein complex data for your analysis.
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Last pushed
Dec 11, 2023
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