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bioRxiv · 10.1101/2025.02.27.640585

AF3Complex Yields Improved Structural Predictions of Protein Complexes

Feldman, J.·Skolnick, J.
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Abstract

MotivationAccurate structures of protein complexes are essential for understanding biological pathway function. A previous study showed how downstream modifications to AlphaFold 2 could yield AF2Complex, a model better suited for protein complexes. Here, we introduce AF3Complex, a model equipped with both similar and novel improvements, built on AlphaFold 3. ResultsBenchmarking AF3Complex and AlphaFold 3 on a large dataset of protein complexes, it was shown that AF3Complex outperforms AlphaFold 3. Moreover, by evaluating the structures generated by AF3Complex on datasets of protein-peptide complexes and antibody-antigen complexes, it was established that AF3Complex could create high-fidelity structures for these challenging complex types. Additionally, when deployed to generate structural predictions for protein complexes used in the recent CASP16 competition, AF3Complex yielded structures that would have placed it among the top models in the competition. AvailabilityThe AF3Complex code is freely available at https://github.com/Jfeldman34/AF3Complex.git. ContactPlease contact jonathanfeldman@gatech.edu.

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Feldman, J., Skolnick, J.. 2025-03-03. AF3Complex Yields Improved Structural Predictions of Protein Complexes. https://doi.org/10.1101/2025.02.27.640585

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