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Navigating protein landscapes with a machine-learned transferable coarse-grained model

Designing simplified models for protein simulation has been a significant challenge for several decades. Using a diverse set of test proteins, and a deep-learning architecture, we have now developed a simple and chemically transferable force field for efficient simulation of protein sequences.

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