From Molecule to Medicine via Machine Learning
PNNL computational biologists, structural biologists, and analytical chemists are using their expertise to safely accelerate the design step of the COVID-19 drug discovery process.
Joining Forces for Trustworthy Artificial Intelligence
PNNL is one of the founding partners of the Trillion Parameter Consortium, which was formed to create reliable generative AI models.
Collaborations Are Key to Shaping the Future of AI
PNNL researchers work with industry partners to transform large language models.
3D-Scaffold, a Deep Learning Approach to Identify Novel Molecules for Therapeutics
A multi-institutional team has developed a deep learning framework to identify novel molecules as drug candidates.
Molecular Traits Explain Organic Matter Differences Across River Corridor Components
Higher temperatures and land-use pressures were associated with weaker chemical separation between river water and sediment dissolved organic matter across 93 sites.
Accelerating Microbial Engineering with Thermodynamic Calculations
New quantum chemistry pipeline uses thermodynamic calculations to help predict changes in cell metabolism for engineered systems.
Unparalleled Resolution of How Microbes and Viruses Impact Biogeochemistry in Rivers
Microbes and viruses play key roles in carbon and nitrogen cycling in riverbed sediments.
Scientists Follow the Trail of Gut Fungi in Search for Sustainable Fuels
Scientists are taking their cues from fungi in the digestive tracts of cows, goats and sheep in the search for new ways to create sustainable fuels and medicines.
Accelerating Materials Discovery with AI
Pacific Northwest National Laboratory scientists discussed their materials research at Accelerate’24.