Adil Kabylda
@kabylda.bsky.social
PhD Researcher in Tkatchenko Group @uni_lu / #LINO22 / BSc and MSc in Chemistry @MSU_1755 @QPD_Lab / Pavlodar KZ 🇰🇿
kabylda.github.io
kabylda.github.io
To assess its capabilities and limitations, we benchmarked SO3LR on systems ranging from small molecules to large solvated biomolecules: protein, glycoprotein, and lipid bilayer. The model proved stable, reproduced local and global structural properties, and scaled to ~200k atoms on a single GPU.
September 7, 2025 at 4:24 PM
To assess its capabilities and limitations, we benchmarked SO3LR on systems ranging from small molecules to large solvated biomolecules: protein, glycoprotein, and lipid bilayer. The model proved stable, reproduced local and global structural properties, and scaled to ~200k atoms on a single GPU.
Our recent work on SO3LR, a general-purpose machine learned force field for molecular simulations, has been published in @jacs.acspublications.org! 🌞 doi.org/10.1021/jacs...
September 7, 2025 at 4:24 PM
Our recent work on SO3LR, a general-purpose machine learned force field for molecular simulations, has been published in @jacs.acspublications.org! 🌞 doi.org/10.1021/jacs...