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AF3Complex yields improved structural predictions of protein complexes

Jonathan Feldman, Jeffrey Skolnick

2025Bioinformatics11 citationsDOIOpen Access PDF

Abstract

MOTIVATION: Accurate 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. RESULTS: Benchmarking 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. AVAILABILITY AND IMPLEMENTATION: The AF3Complex code is freely available at https://github.com/Jfeldman34/AF3Complex.git.

Topics & Concepts

BenchmarkingComputer scienceSource codeDownstream (manufacturing)Code (set theory)Protein structureFunction (biology)FidelityComputational biologyChemistryProgramming languageBiologyBiochemistrySet (abstract data type)MarketingOperations managementEconomicsBusinessEvolutionary biologyTelecommunicationsProtein Structure and Dynamicsvaccines and immunoinformatics approachesMachine Learning in Bioinformatics
AF3Complex yields improved structural predictions of protein complexes | Litcius