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

ABSTRACT: 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 functions can be considerably improved in their ability to describe large-scale

SUBMITTER: Park H 

PROVIDER: S-EPMC5515585 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature