This is a list of some of the more frequently asked questions about Rosetta.
See Also:
Rosetta is available to academic and commercial researchers through a license. Academic licenses are free. Please see https://www.rosettacommons.org/software/license-and-download for licensing and download Rosetta.
We distribute source code in C++ and users need to compile it themselves.
Rosetta requires a Unix-like operating system like Linux or MacOS - it will not easily run on a Windows machine.
To get the sampling needed for most Rosetta protocols, it's best to run Rosetta on a multiprocessor computing cluster. Most Rosetta protocols are trivially parallelizable, though, and can be run on a single processor, at the cost of much longer runtimes.
Most modern processors should be suitable. The one limitation you may run into is memory. We recommend at least 1G memory per CPU running Rosetta for best performance.
Please see the page Build Documentation or the Installation tutorial for instructions on how to compile and install Rosetta.
A good starting point will be the series of introductory tutorials.
RosettaCommons is a collection of 40+ groups and institutions from around the world which work together to develop and support Rosetta. See https://www.rosettacommons.org/about for more information.
There are a number of publicly accessible servers on the web that allow researchers to run certain Rosetta protocols without installing Rosetta locally.
Robetta is the original Rosetta web server.
ROSIE (the Rosetta Online Server that Includes Everyone) is a new, centralized site for Rosetta web servers, and includes a number of protocols.
Other web servers also exist.
PyRosetta is a wrapper around the C++ Rosetta libraries, allowing them to be used from user-written Python scripts. See http://pyrosetta.org for more details.
CSRosetta is a set of scripts and adjustments to the standard Rosetta platform which makes working with all NMR data (not just chemical shifts) easier. See http://www.csrosetta.org for more information.
Ab initio protein folding performs task of predicting 3-D structural models for a protein molecule from its sequence information. visit our full-chain protein structure prediction server: Robetta: http://robetta.org/
Ab initio structure prediction classically refers to structure prediction using nothing more than first-principles (i.e. physics). De Novo is a more general term that refers to the greater category of methods that do not use templates from homologous PDB structures. Since Rosetta uses fragments from existing PDB structures in order to guide the search in conjunction with energy functions, there is a semantic argument as to whether it is truly "ab initio" (although the same could be said for any statistically derived energy function). Long story short: call it what you want, but be prepared for a debate!
Fragment libraries are the pieces of experimentally determined structures that Rosetta uses to guide the search of conformational space when predicting structures using the ab initio protocol, as well as longer loop conformations in homology models.
See the scoring explained and analyzing results for more information.
There have been a large number of Rosetta papers, so finding the appropriate one to cite can be a challenge.
Generally, you want to cite the paper which presented the protocol which you are using in your paper. Often the relevant publications are listed on the documentation page for the application you used.
You can also take a look at the Rosetta canon for major papers, and https://www.rosettacommons.org/about/pubs for a somewhat comprehensive list of Rosetta related publications.
The main Rosetta documentation page is at http://www.rosettacommons.org/docs/latest/. The contents of this website are also available in the documentation/ directory in the downloaded version of Rosetta.
We also have runnable demos of Rosetta protocols in the demos/ directory of the Rosetta demos. The text contents of these demos are available online at http://www.rosettacommons.org/demos/latest/.
If you're interested in modifying Rosetta to implement new protocols, you can find resources at https://www.rosettacommons.org/dev.
Rosetta will delete residues which are missing too many backbone atoms. "Missing" includes those atoms which are marked with zero occupancy in the PDB. Add the flag "-ignore_zero_occupancy false" to change this behavior.
If the backbone atoms are completely missing, use the loopmodel protocol to build in the residues.
The documentation for each application should list most of the relevant options for that application.
The options overview should list options which affect most protocols in Rosetta.
A list of almost all of the options Rosetta recognizes is at the full options list. (Not every protocol understands every option, though.)
This is highly protocol dependent. There are a few protocols which take full advantage of MPI communication, and require MPI to run. Most Rosetta protocols, though, are intrinsically serial for each output structure, but can support running under MPI by having each processor work on a single output structure. See MPI for more details.
We highly recommend to use the Robetta server to create fragment file. http://robetta.bakerlab.org/fragmentsubmit.jsp It is possible to run fragment picking locally, but requires the installation of a number of dependencies and is non-trivial.
Rosetta requires a chemical specification of each residue and how they behave. By default it can recognize a fair number of the important residues, but does not understand things like ligands. See preparing ligands for details on how to get Rosetta to recognize your residue.
Packing is the process of putting sidechains onto a backbone, or optimizing the conformation of sidechains. Rosetta uses a set of "rotamers" (discrete sidechain conformation samples derived from experimentally determined structures) and a Metropolis Monte Carlo simulated annealing process to determine which combination of rotamers produces the lowest energy for a given backbone.
Design in Rosetta uses the same packing machinery as sidechain optimization, but instead of optimizing within the rotamers for a single amino acid, it considers rotamers for a number of different amino acid identities.
See fixing errors for more information.
Most protocols can use the input structure as a "mock native" structure.