Molecular machine learning (ML) underpins critical workflows in drug discovery, material science, and catalyst optimization by rapidly predicting molecular interactions and properties. For instance, ...

Learn how large language models like ChatGPT make knowledge graph creation accessible, revealing hidden connections in your ...

This useful manuscript describes cryo-EM structures of archaeal proteasomes that reveal insights into how occupancy of binding pockets on the 20S protease regulates proteasome gating. The evidence ...

Researchers from Ruhr University Bochum, Germany, have developed a new method that allows them to visualize the contribution ...

The continuous, solid-phase system achieved a refolding yield of approximately 100% by gradually pumping lysozyme through the ...

Learn how GraphRAG transforms unstructured text into structured data, revolutionizing AI retrieval with deeper insights and ...

Research team used ProteinMPNN to expand the sequence space of synthetic binding proteins (SBPs), improving their solubility ...

Endogenous intracellular allosteric modulators of GPCRs remain largely unexplored, with limited binding and phenotype data available. This gap arises from the lack of robust computational methods for ...

Researchers have captured a time-resolved video of a protein interaction essential to healthy brain development.

AfCycDesign: Cyclic offset to the relative positional encoding in AlphaFold2 enables accurate structure prediction ... transition metal binding sites in proteins. It integrates geometric and ...

One of the most advanced solutions is dynamic graph representation learning, which embeds structural and temporal correlations into a representative vector for each node or subgraph. Existing models ...