48 citations · 107 across the 3 of their papers we have counts for
3 papers
On the design space between molecular mechanics and machine learning force fields
Yuanqing Wang, Kenichiro Takaba, Michael S. Chen +14
A force field as accurate as quantum mechanics (QM) and as fast as molecular mechanics (MM), with which one can simulate a biomolecular system efficiently enough and meaningfully e…
Machine-learned molecular mechanics force field for the simulation of protein-ligand systems and beyond
Kenichiro Takaba, Iván Pulido, Pavan Kumar Behara +11
The development of reliable and extensible molecular mechanics (MM) force fields -- fast, empirical models characterizing the potential energy surface of molecular systems -- is in…
EspalomaCharge: Machine learning-enabled ultra-fast partial charge assignment
Yuanqing Wang, Iván Pulido, Kenichiro Takaba +4
Atomic partial charges are crucial parameters in molecular dynamics (MD) simulation, dictating the electrostatic contributions to intermolecular energies, and thereby the potential…