Protein Structure Prediction Using Rosetta

By Carol A. Rohl, Charles E.M. Strauss, Kira M. S. Misura, David Baker. 2004

1,719 citations recorded by the source corpus.

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

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Citations in the corpus

Protein Structure and Sequence Generation with Equivariant Denoising Diffusion Probabilistic Models (2022, background): “However, for the task of structure generation, stochastic search algorithms based on handcrafted energy functions and heuristic sampling approaches are still in wide use [25, 34, 2, 26].”
Improving homology modeling from low-sequence identity templates in Rosetta: A case study in GPCRs (2020, methodology): “Peptide fragments are mined from the PDB based on the target sequence and can improve local geometries that may be inaccessible from template structures [24].”
De novo protein design by deep network hallucination (2020, methodology): “We used Rosetta in silico protein folding simulations 20 to assess the extent to which the hallucinated sequences encode the hallucinated structures according to the Rosetta forcefield 21 .”
Improved protein structure prediction using predicted interresidue orientations (2019, positive): “These distance- and orientationdependent potentials were used as restraints, together with the Rosetta centroid level (coarse-grained) energy function (16), and folded structures satisfying the restraints were generated starting from conformations with randomly selected backbone dihedral angles by 3”
I-TASSER server: new development for protein structure and function predictions (2015, background): “The community-wide blind CASP experiments have shown that many automated servers, such as I-TASSER (1,2), Rosetta (3) and HHpred (4), can now generate structural models with accuracy comparable to the best human-expert guided modeling (5–7).”
Toward optimal fragment generations for ab initio protein structure assembly (2012, methodology): “12,24 The second method is sequence-independent, which gathers fragments of various lengths and conformations by clustering the structures from the PDB library.”
Evolutionary context-integrated deep sequence modeling for protein engineering (2020, background): “Rational design is oftentimes assisted by quantitative approaches to evaluate sequences that fold into a specific structure, including biophysical modeling [3,4] , force field approximations [5–7] , structure prediction [8–10] , and molecular dynamics simulations [11] .”
Scientific Benchmarks for Guiding Macromolecular Energy Function Improvement (2013, background): “More specifically, Score12, (Rohl et al. 2004), the default fullatom energy function in Rosetta is composed of a Lennard-Jones term, an implicit solvation term (Lazaridis & Karplus, 1999), an orientation-dependent hydrogen bond term (Kortemme et al.”
High resolution comparative modeling with RosettaCM (2013, methodology): “As in the Rosetta de novo structure prediction protocol(Rohl et al., 2004), these terms are gradually phased in.”
Protein sequence design by conformational landscape optimization (2021, methodology): “Energy landscapes of designs were mapped out using Rosetta de novo structure prediction (ab initio folding) (27).”
Large-scale determination of previously unsolved protein structures using evolutionary information (2015, methodology): “…structures of proteins from large families with no representatives of known structure by integrating co-evolution derived contact information from GREMLIN ( Kamisetty et al., 2013 ) into the Rosetta structure prediction methodology ( Simons et al., 1999 ; Rohl et al., 2004 ; Raman et al., 2009 ).”
Alternate states of proteins revealed by detailed energy landscape mapping (2010, positive): “For each protein we ran three sampling runs with the normal Rosetta fragment insertion approach.(26) In the first set, we excluded fragments from homologous structures in the PDB, in the second set we used all the fragments available (a library of 400 fragments for each residue position) but not inc”
Ab Initio Protein Structure Assembly Using Continuous Structure Fragments and Optimized Knowledge-based Force Field (2012, methodology): “Rosetta14,43 is one of the best-established ab initio protein folding methods as demonstrated in the CASP experiments.”
GPCRM: a homology modeling web service with triple membrane-fitted quality assessment of GPCR models (2018, methodology): “Loops can be transferred from a template structure without any changes (the ‘High similarity’ option) or refined in either Modeller or Rosetta (the cyclic coordinate descent (CCD) algorithm).”