Practically Useful: What the Rosetta Protein Modeling Suite Can Do for You

By Kristian Kaufmann, Gordon Lemmon, Samuel L. DeLuca, J. Sheehan, Jens Meiler. 2010

404 citations recorded by the source corpus.

The objective of this review is to enable researchers to use the software package Rosetta for biochemical and biomedicinal studies. We provide a brief review of the six most frequent research problems tackled with Rosetta. For each of these six tasks, we provide a tutorial that illustrates a basic Rosetta protocol. The Rosetta method was originally developed for de novo protein structure prediction and is regularly one of the best performers in the community-wide biennial Critical Assessment of Structure Prediction. Predictions for protein domains with fewer than 125 amino acids regularly have a backbone root-mean-square deviation of better than 5.0 Å. More impressively, there are several cases in which Rosetta has been used to predict structures with atomic level accuracy better than 2.5 Å. In addition to de novo structure prediction, Rosetta also has methods for molecular docking, homology modeling, determining protein structures from sparse experimental NMR or EPR data, and protein design. Rosetta has been used to accurately design a novel protein structure, predict the structure of protein−protein complexes, design altered specificity protein−protein and protein−DNA interactions, and stabilize proteins and protein complexes. Most recently, Rosetta has been used to solve the X-ray crystallographic phase problem.

Subfields: Genetics, Molecular Biology, Surgery

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Citations in the corpus

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).”
Computational Methods in Drug Discovery (2014, methodology): “ROSETTALIGAND was used by Kaufmann et al. (2009) to predict the binding mode of serotonin with serotonin transporters.”
Strategies and molecular tools to fight antimicrobial resistance: resistome, transcriptome, and antimicrobial peptides (2013, methodology): “Driven by high profitability, the pharmaceutical industry has focused its production on blockbuster drugs (or global FMCG)– such as those used in the treatment of chronic diseases such as cancer or sexual dysfunction, for example—rather than the development of antimicrobial drugs used for short…”
Introduction to the BioChemical Library (BCL): An Application-Based Open-Source Toolkit for Integrated Cheminformatics and Machine Learning in Computer-Aided Drug Discovery (2022, background): “Its command-line usage will be familiar to users of the popular macromolecular modeling software ROSETTA (Kaufmann et al., 2010).”
Real-Time PyMOL Visualization for Rosetta and PyRosetta (2011, methodology): “The Rosetta software suite, an object-oriented protein structure prediction tool [1], can effectively perform protein structure prediction and design [2] [3].”
Web‐accessible molecular modeling with Rosetta: The Rosetta Online Server that Includes Everyone (ROSIE) (2018, background): “…efforts have expanded the usability of Rosetta with interfaces to Python (PyRosetta 25 ), and XML (RosettaScripts 26 ), and the publication of introductory tutorials, 27–29 most of Rosetta’s functionality still requires familiarity with the Unix command line environment, limiting use by nonexperts.”