2 citations · 2 across the 2 of their papers we have counts for
5 papers
Boltzmann-Expected Molecular Design with Decoupled Annealing Flows
Selma Moqvist, Richard Beckmann, Ross Irwin +2
Most 3D properties relevant to molecular design, including free energies and shape descriptors, are over the Boltzmann distribution over 3D configurations o…
Beyond Manual Curation: Augmenting Targeted Protein Degradation Databases via Agentic Literature Extraction Workflows
Yaochen Rao, Farzaneh Jalalypour, N. M. Anoop Krishnan +1
Predictive models in biomedicine depend on structured assay data locked in the text, tables, and supplements of primary publications. This bottleneck is especially acute in targete…
QT-Net: Rethinking Evaluation of AI Models in Atomic Chemical Space
Pablo Martínez Crespo, Stefano Ribes, Martin Rahm +6
Atomic properties such as partial charges or multipoles encode chemically meaningful information that can inform downstream molecular property prediction, but their evaluation as m…
A Comprehensive Review of Emerging Approaches in Machine Learning for De Novo PROTAC Design
Yossra Gharbi, Rocío Mercado
Targeted protein degradation (TPD) is a rapidly growing field in modern drug discovery that aims to regulate the intracellular levels of proteins by harnessing the cell's innate de…
Modeling PROTAC Degradation Activity with Machine Learning
Stefano Ribes, Eva Nittinger, Christian Tyrchan +1
PROTACs are a promising therapeutic modality that harnesses the cell's built-in degradation machinery to degrade specific proteins. Despite their potential, developing new PROTACs…