Although canonical protein design has benefited from machine learning methods trained on databases of protein sequences and structures, synthetic heteropolymer design still relies heavily on physics-b...

Despite having structures for most proteins, we still do not know their function. Here, authors introduce EvoWeaver, a de novo method to identify genes working together using evolutionary information....

Understanding biomolecular interactions is fundamental to advancing fields like drug discovery and protein design. In this paper, we introduce Boltz-1, an open-source deep learning model incorporating...

Nature, Published online: 10 April 2024; doi:10.1038/s41586-024-07287-2 Citrate synthase from the cyanobacterium Synechococcus elongatus is shown to self-assemble into Sierpiński triangles, a finding that opens up the possibility that other naturally occurring molecular-scale fractals exist.

Enhancers are genomic elements critical for regulating gene expression. In this Review, the authors discuss how sequence-to-function models can be used to unravel the rules underlying enhancer activit...

PLACER is graph neural network for local prediction of protein-ligand conformational ensembles. - baker-laboratory/PLACER