TY - JOUR T1 - The Rosetta all-atom energy function for macromolecular modeling and design JF - bioRxiv DO - 10.1101/106054 SP - 106054 AU - Rebecca F. Alford AU - Andrew Leaver-Fay AU - Jeliazko R. Jeliazkov AU - Matthew J. O'Meara AU - Frank P. DiMaio AU - Hahnbeom Park AU - Maxim V. Shapovalov AU - P. Douglas Renfrew AU - Vikram K. Mulligan AU - Kalli Kappel AU - Jason W. Labonte AU - Michael S. Pacella AU - Richard Bonneau AU - Philip Bradley AU - Roland L. Dunbrack, Jr. AU - Rhiju Das AU - David Baker AU - Brian Kuhlman AU - Tanja Kortemme AU - Jeffrey J. Gray Y1 - 2017/01/01 UR - http://biorxiv.org/content/early/2017/02/07/106054.abstract N2 - Over the past decade, the Rosetta biomolecular modeling suite has informed diverse biological questions and engineering challenges ranging from interpretation of low-resolution structural data to design of nanomaterials, protein therapeutics, and vaccines. Central to Rosetta’s success is the energy function: amodel parameterized from small molecule and X-ray crystal structure data used to approximate the energy associated with each biomolecule conformation. This paper describes the mathematical models and physical concepts that underlie the latest Rosetta energy function, beta_nov15. Applying these concepts,we explain how to use Rosetta energies to identify and analyze the features of biomolecular models.Finally, we discuss the latest advances in the energy function that extend capabilities from soluble proteins to also include membrane proteins, peptides containing non-canonical amino acids, carbohydrates, nucleic acids, and other macromolecules. ER -