Simultaneous Optimization of Biomolecular Energy Functions on Features from Small Molecules and Macromolecules

Most biomolecular modeling energy functions for structure prediction, sequence design, and molecular docking have been parametrized using existing macromolecular structural data; this contrasts molecular mechanics force fields which are largely optimized using small-molecule data. In this study, we describe an integrated method that enables optimization of a biomolecular modeling energy function simultaneously against small-molecule thermodynamic data and high-resolution macromolecular structural data. We use this approach to develop a next-generation Rosetta energy function that utilizes a new anisotropic implicit solvation model, and an improved electrostatics and Lennard-Jones model, illustrating how energy…

• FF
  Foundation for the National Institutes of Health

  Award: R01GM092802
• OO
  Office of Science

  Award: DE-AC02-06CH11357