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bioRxiv · 10.64898/2026.04.03.716280

Dissecting the Black Box of AlphaFold in Protein-Protein Complex Assembly

Li, S.·Mu, Z.·Yan, C.
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Abstract

AlphaFold has revolutionized protein complex structure prediction, yet how it assembles intermolecular interfaces remains poorly understood. Contrary to the prevailing view that inter-protein coevolution drives complex prediction, we uncover a geometry-over-coevolution principle governing assembly in AlphaFold-Multimer and AlphaFold3. Through systematic perturbation of evolutionary and structural inputs and development of residue-level constraint propagation mapping to trace the emergence and propagation of geometric information within the network, we show that prediction accuracy is governed primarily by monomer-derived structural geometry and interface-specific sequence-geometry compatibility, rather than direct inter-protein coevolutionary signals. Our mapping reveals a hierarchical assembly mechanism in which monomer-level geometric representations are established first and progressively propagated to constrain cross-chain interfaces. This mechanism further explains why antigen-antibody complexes are predicted less accurately, as their intrinsic interface plasticity and non-canonical architectures limit the propagation of geometric constraints across interfaces. Together, these findings establish a mechanistic framework for understanding how artificial intelligence models assemble protein complexes and provide principles for improving next-generation structure prediction.

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Li, S., Mu, Z., Yan, C.. 2026-04-06. Dissecting the Black Box of AlphaFold in Protein-Protein Complex Assembly. https://doi.org/10.64898/2026.04.03.716280

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