IntFold：一種可控的基礎模型，適用於通用與專項生物分子結構預測

摘要

我們介紹了IntFold，這是一個可控的基礎模型，適用於一般及專業生物分子結構的預測。IntFold展現出與當前最先進的AlphaFold3相媲美的預測準確性，同時採用了更優化的自定義注意力核心。除了標準的結構預測外，IntFold還能夠通過使用個別適配器來預測變構態、受限結構以及結合親和力。此外，我們引入了一種新穎的置信度頭部來評估對接質量，為諸如抗體-抗原複合體等挑戰性目標提供了更細緻的評估。最後，我們分享了在這一計算密集型模型訓練過程中所獲得的洞見。

English

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.

IntFold：一種可控的基礎模型，適用於通用與專項生物分子結構預測

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

摘要

Support