{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Daily Paper Cast","title":"IntFold: A Controllable Foundation Model for General and Specialized Biomolecular Structure Prediction","html":"<iframe width=\"100%\" height=\"180\" frameborder=\"no\" scrolling=\"no\" seamless src=\"https://share.transistor.fm/e/b93026f0\"></iframe>","width":"100%","height":180,"duration":1314,"description":"\n            🤗 Upvotes: 32 | q-bio.BM\n\n            Authors:\n            The IntFold Team, Leon Qiao, Wayne Bai, He Yan, Gary Liu, Nova Xi, Xiang Zhang\n\n            Title:\n            IntFold: A Controllable Foundation Model for General and Specialized Biomolecular Structure Prediction\n\n            Arxiv:\n            http://arxiv.org/abs/2507.02025v1\n\n            Abstract:\n            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.\n            ","thumbnail_url":"https://img.transistorcdn.com/8lOVNnuwhrA3rxrDMv7Osu4j_t1-jORooO6NfGcQhcw/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS81Zjg1/YzRhODczMDU4MmE4/OGMwN2FiNDlmYzI2/MDliMi5qcGVn.webp","thumbnail_width":300,"thumbnail_height":300}