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The Rosetta All-Atom Energy Function for Macromolecular Modeling and Design

  • Rebecca F. Alford
  • , Andrew Leaver-Fay
  • , Jeliazko R. Jeliazkov
  • , Matthew J. O'Meara
  • , Frank P. DiMaio
  • , Hahnbeom Park
  • , Maxim V. Shapovalov
  • , P. Douglas Renfrew
  • , Vikram K. Mulligan
  • , Kalli Kappel
  • , Jason W. Labonte
  • , Michael S. Pacella
  • , Richard Bonneau
  • , Philip Bradley
  • , Roland L. Dunbrack
  • , Rhiju Das
  • , David Baker
  • , Brian Kuhlman
  • , Tanja Kortemme
  • , Jeffrey J. Gray
  • Johns Hopkins University
  • University of North Carolina at Chapel Hill
  • University of California at San Francisco
  • University of Washington
  • Fox Chase Cancer Center
  • New York University
  • Simons Foundation
  • Stanford University
  • Fred Hutchinson Cancer Research Center

Research output: Contribution to journal › Article › peer-review

1300 Scopus citations

Abstract

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: A model parametrized 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, called the Rosetta Energy Function 2015 (REF15). 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 its capabilities from soluble proteins to also include membrane proteins, peptides containing noncanonical amino acids, small molecules, carbohydrates, nucleic acids, and other macromolecules.

Original languageEnglish
Pages (from-to)3031-3048
Number of pages18
JournalJournal of Chemical Theory and Computation
Volume13
Issue number6
DOIs
StatePublished - Jun 13 2017

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