3 papers
q-bio.BM2025
Learning conformational ensembles of proteins based on backbone geometry
Nicolas Wolf, Leif Seute, Vsevolod Viliuga +3
Deep generative models have recently been proposed for sampling protein conformations from the Boltzmann distribution, as an alternative to often prohibitively expensive Molecular…
cs.LG2025
Energy-Based Flow Matching for Generating 3D Molecular Structure
Wenyin Zhou, Christopher Iliffe Sprague, Vsevolod Viliuga +3
Molecular structure generation is a fundamental problem that involves determining the 3D positions of molecules' constituents. It has crucial biological applications, such as molec…
q-bio.BM2025
Flexibility-Conditioned Protein Structure Design with Flow Matching
Vsevolod Viliuga, Leif Seute, Nicolas Wolf +4
Recent advances in geometric deep learning and generative modeling have enabled the design of novel proteins with a wide range of desired properties. However, current state-of-the-…