RT Journal Article
SR Electronic
T1 The Rosetta all-atom energy function for macromolecular modeling and design
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 106054
DO 10.1101/106054
A1 Rebecca F. Alford
A1 Andrew Leaver-Fay
A1 Jeliazko R. Jeliazkov
A1 Matthew J. O'Meara
A1 Frank P. DiMaio
A1 Hahnbeom Park
A1 Maxim V. Shapovalov
A1 P. Douglas Renfrew
A1 Vikram K. Mulligan
A1 Kalli Kappel
A1 Jason W. Labonte
A1 Michael S. Pacella
A1 Richard Bonneau
A1 Philip Bradley
A1 Roland L. Dunbrack, Jr.
A1 Rhiju Das
A1 David Baker
A1 Brian Kuhlman
A1 Tanja Kortemme
A1 Jeffrey J. Gray
YR 2017
UL http://biorxiv.org/content/early/2017/02/07/106054.abstract
AB 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.