DyneTrion: A Spatio-temporally Coherent Generative Emulator for Protein Dynamics Across Timescales

• URL: http://arxiv.org/abs/2607.15309v1
• Date: Wed, 15 Jul 2026 12:36:46 GMT
• Title: DyneTrion: A Spatio-temporally Coherent Generative Emulator for Protein Dynamics Across Timescales
• Abstract summary: We present DyneTrion, a generative protein dynamics emulator.<n>It enforces geometric symmetry, structural consistency and temporal coherence within a single framework.<n>Across 100-ns MD trajectory simulation benchmarks, DyneTrion reproduces MD trajectory distributions while maintaining stereochemical validity during extrapolations.
• Score: 7.294976373980908
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Proteins function through coordinated motion across multiple spatial and temporal scales, underpinning processes such as ligand binding, allostery, and catalysis. However, accessing long-timescale conformational change through molecular dynamics (MD) simulations remains prohibitively expensive for systematic exploration across diverse systems. Here, we present DyneTrion, a generative protein dynamics emulator that jointly enforces geometric symmetry, structural consistency and temporal coherence within a single framework. DyneTrion uses a tri-attention architecture that integrates invariant point attention (IPA) for SE(3)-robust geometric updates, spatial attention anchored to a reference conformation to preserve structural integrity, and temporal attention to model correlated evolution across time frames. Across 100-ns MD trajectory simulation benchmarks, DyneTrion reproduces MD-derived flexibility, ensemble distributions and interaction observables while maintaining stereochemical validity during extrapolation. To evaluate long time-scale generalization, we introduce dynamicPDB, a dataset of over 10,000 proteins with up to 1-$μ$s all-atom trajectories at 10-ps resolution and accompanying physical annotations. On microsecond trajectories, DyneTrion preserves free-energy landscapes and metastable-state populations, and it supports large conformational propagation in apo-to-holo transitions and fast folders. Together, DyneTrion provides a scalable path from static structure prediction toward time-resolved, ensemble-faithful protein modeling. The code is publicly available at https://github.com/fudan-generative-vision/DyneTrion

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