Macromolecular modeling with rosetta.

By Rhiju Das, David Baker. 2008

987 citations recorded by the source corpus.

Subfields: Materials Chemistry, Molecular Biology, Computational Biology & Bioinformatics

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Citations in the corpus

Generalized Biomolecular Modeling and Design with RoseTTAFold All-Atom (2023, positive): “Sequences were obtained using LigandMPNN and Rosetta FastRelax ( 55 ), and 4416 designs were selected based on consistency with AF2 ultraviolet-visible (UV-Vis) spectra consistent with Cys-bound heme (as judged by the Soret maximum wavelength after in vitro heme loading) ( 59 ).”
Critical assessment of methods of protein structure prediction (CASP) — round x (2013, methodology): “Also important has been the emergence of robust on-line6 and off-line7–9 user-friendly modeling software packages, and the provision of databases of models.10 –12 The accuracy of homology models, as monitored by CASP, has improved dramatically, through a combination of improved methods, larger…”
Learning from Protein Structure with Geometric Vector Perceptrons (2020, methodology): “The smaller size of this benchmark also allows a comparison to the computationally expensive physics-based calculations of the fixbb protocol in Rosetta, a software suite well-established in the structural biology community (Das & Baker, 2008).”
Rosetta3: An Object-Oriented Software Suite for the Simulation and Design of Macromolecules (2011, positive): “The ROSETTA molecular modeling suite has proved useful in solving a wide variety of problems in structural biology (Das and Baker, 2008; Kaufmann et al. , 2010; Table 19.1).”
High resolution comparative modeling with RosettaCM (2013, methodology): “Structures are built up using a Rosetta “fold tree”(Das and Baker, 2008): the global position of each segment is represented in Cartesian space, while the backbone and sidechain conformation of residues in each segment are represented in torsion space.”
Outcome of a Workshop on Applications of Protein Models in Biomedical Research (2009, background): “…(Bryson et al., 2005; Rost, 2003); an atomic model of a domain can be obtained from the sequence alone by ab initio or de novo prediction methods (Das and Baker, 2008); fold assignment and sequence-structure alignment can be achieved by threading against a library of known folds (Godzik, 2003);…”
Large-scale determination of previously unsolved protein structures using evolutionary information (2015, background): “…carried out, optimizing first a low-resolution energy function favoring hydrophobic burial and backbone hydrogen bonding, and second a detailed all atom energy function describing hydrogen bonding and electrostatic interactions, van der Waals interactions, and solvation ( Das and Baker, 2008 ).”
Generative modeling for protein structures (2018, methodology): “Guided by a heuristic energy function, Rosetta samples native protein fragments to fold backbones and can optimize over amino acid types and orientations to determine the most likely amino acid sequence corresponding to the designed backbone [14].”
Protein structure modeling with MODELLER. (2014, background): “Free modeling does not require a related protein, but instead uses a variety of methods to combine physics with the known behaviors of protein structures (for example by combining multiple short structural fragments extracted from known proteins)(9-11); it is, however, extremely computationally expe”
Alteration of enzyme specificity by computational loop remodeling and design (2009, methodology): “Our general method was implemented as an extension to the Rosetta suite of molecular modeling programs (11, 31).”
Rosetta FlexPepDock ab-initio: Simultaneous Folding, Docking and Refinement of Peptides onto Their Receptors (2011, methodology): “Rosetta infrastructure As for the original FlexPepDock refinement protocol, the FlexPepDock ab-initio protocol is fully implemented within the Rosetta modeling framework [44].”
A Comprehensive, High-Resolution Map of a Gene’s Fitness Landscape (2014, methodology): “We predicted G ( Gwild-type – Gmutant) using Rosetta (Das and Baker 2008; Chaudhury et al. 2010) for 4,783 missense mutations of TEM-1, allowing limited backbone flexibility (fig.”
Simulation of the clinical and pathological manifestations of Coronavirus Disease 2019 (COVID-19) in golden Syrian hamster model: implications for disease pathogenesis and transmissibility (2020, methodology): “7 Relax application.(14) ACE2-spike interface binding energy was calculated by InterfaceAnalyzer within Rosetta.”
Relaxation of backbone bond geometry improves protein energy landscape modeling (2014, background): “6 However, it is formally possible that new minima exist when the additional DOFs are added, but local optimization fails to identify them.”
Enhancing structure prediction and design of soluble and membrane proteins with explicit solvent-protein interactions (2017, methodology): “Specifically, these techniques are: Rosetta (protein modeling and design software with implicit solvation (Das and Baker, 2008)), Fold-X (protein modeling and design software with knowledge-based explicit solvent model (Schymkowitz et al., 2005)), HADDOCK (protein modeling refinement step using…”