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Rigidity-Aware Geometric Pretraining for Protein Design and Conformational Ensembles
Generative models have recently advanced $\textit{de novo}$ protein design by learning the statistical regularities of natural structures. However, current approaches face three key limitations: (1) Existing methods cannot jointly learn protein geometry and design tasks, where pretraining can be a s
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