title: Macromolecular modeling with rosetta.
abstract: Advances over the past few years have begun to enable prediction and design of macromolecular structures at near-atomic accuracy. Progress has stemmed from the development of reasonably accurate and efficiently computed all-atom potential functions as well as effective conformational sampling strategies appropriate for searching a highly rugged energy landscape, both driven by feedback from structure prediction and design tests. A unified energetic and kinematic framework in the Rosetta program allows a wide range of molecular modeling problems, from fibril structure prediction to RNA folding to the design of new protein interfaces, to be readily investigated and highlights areas for improvement. The methodology enables the creation of novel molecules with useful functions and holds promise for accelerating experimental structural inference. Emerging connections to crystallographic phasing, NMR modeling, and lower-resolution approaches are described and critically assessed.
authors.affiliation: Department of Biochemistry, University of Washington, Seattle, WA 98195, USA. rhiju@u.washington.edu
authors.forename: Rhiju
authors.initials: R
authors.lastname: Das
authors.forename: David
authors.initials: D
authors.lastname: Baker
mesh_terms: D000465:Algorithms; D000818:Animals; D018360:Crystallography, X-Ray / Q000379:methods; D006801:Humans; D046911:Macromolecular Substances; D009682:Magnetic Resonance Spectroscopy; D008958:Models, Molecular; D008968:Molecular Conformation; D009690:Nucleic Acid Conformation; D011108:Polymers / Q000737:chemistry; D011487:Protein Conformation; D015202:Protein Engineering / Q000379:methods*; D012313:RNA / Q000737:chemistry; D012984:Software; D013816:Thermodynamics
chemical_list: D046911:Macromolecular Substances; D011108:Polymers; D012313:RNA