IntFold: A Controllable Foundation Model for General and Specialized Biomolecular Structure Prediction - podcast episode cover

IntFold: A Controllable Foundation Model for General and Specialized Biomolecular Structure Prediction

Jul 05, 2025•22 min•Ep. 935
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Episode description

🤗 Upvotes: 32 | q-bio.BM

Authors:
The IntFold Team, Leon Qiao, Wayne Bai, He Yan, Gary Liu, Nova Xi, Xiang Zhang

Title:
IntFold: A Controllable Foundation Model for General and Specialized Biomolecular Structure Prediction

Arxiv:
http://arxiv.org/abs/2507.02025v1

Abstract:
We introduce IntFold, a controllable foundation model for both general and specialized biomolecular structure prediction. IntFold demonstrates predictive accuracy comparable to the state-of-the-art AlphaFold3, while utilizing a superior customized attention kernel. Beyond standard structure prediction, IntFold can be adapted to predict allosteric states, constrained structures, and binding affinity through the use of individual adapters. Furthermore, we introduce a novel confidence head to estimate docking quality, offering a more nuanced assessment for challenging targets such as antibody-antigen complexes. Finally, we share insights gained during the training process of this computationally intensive model.

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