Yui Tik Pang

Abstract The structural dynamics of proteins play a crucial role in their function, yet most experimental and deep learning methods produce only static models. While molecular dynamics (MD) simulations provide atomistic insight into conformational transitions, they remain computationally prohibitive, particularly for large-scale motions. Here, we introduce DeepPath, a deep-learning-based framework that rapidly generates physically realistic transition pathways between known protein states.

Autotransporters are a large family of virulence factors found in Gram-negative bacteria that play important roles in their pathogenesis. The passenger domain of autotransporters is almost always composed of a large β-helix, with only a small portion of it being relevant to its virulence function. This has led to the hypothesis that the folding of the β-helical structure aids the secretion of the passenger domain across the Gram-negative outer membrane (OM).

Abstract The trimeric spike (S) glycoprotein, which protrudes from the SARS-CoV-2 viral envelope, binds to human ACE2, initiated by at least one protomer’s receptor binding domain (RBD) switching from a "down” (closed) to an "up” (open) state.