Emyx: Fast and efficient all-atom protein generation
Computational enzyme design requires generating proteins that scaffold catalytic residues and ligands, a task that demands both geometric accuracy and structural diversity from the underlying generative model. Current all-atom generators inherit expensive architectures from structure prediction, leading to high training costs and limited sample diversity. We argue that much of this complexity is unnecessary for generators, which condition on sparse geometric constraints rather than rich co-evolutionary signals. Emyx is a 140M-parameter conditional flow matching model that concentrates capacity within standard transformer blocks, replacing heavy embedding stacks with lightweight conditiona...
| Authors | Nicholas J. Williams, Ward Haddadin, Matteo P. Ferla et al. |
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| Primary category | cs.LG |
| Published | 12 June 2026 |
| Last updated at source | 26 August 2026 |
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