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Conversion from Dihedral angle representation to Cartesian representation


I'm very new here. In fact, it is my first post. I'm a computer scientist which is studying protein structure prediction in ab initio modeling.

My doubt is concern about conversion of protein from dihedral angles representation to Cartesian representation. Where distances, angles and dihedrals of protein are stored? What algorithm is used for it?

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Fragment file viewers

Currently I was solving a low resolution protein crystal, and I can build a major part of my protein. And then,I was using rosseta to generate a 9ers, and want to choose a proper fragment as a model to build the poorly identified part of my protein manually. So, I have to pick the 200 fragments one by one, by get the pdb code, and download the pdb files and finally find the corresponding sequence to see if the shape of model fits my protein and the poor density. And this process is very time-consuming.

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Rosetta's building is OK, but the program is running failed

I encountered a problem with rosetta that I can not solve it myself. could anyone do me a favor.
I installed rosetta on Cent Os, and everything looks OK. But when I ran the test command "phenix_regression.wizards.test_command_line_rosetta_quick_tests", it failed as following:

Running all command_line tests
Number of tests to run: 38
Running test_autobuild
Running test_autobuild_double

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DockingHighResLegacy repacks all sidechains on first apply(), interface sidechains on subsequent apply()

[Using PyRosetta.ScientificLinux-r47452.64Bit]

docker = DockingHighResLegacy(jump, scoreFxn)

When I use the above in a python script, I get:

protocols.docking.DockingHighRes: in DockingHighRes.apply
protocols.docking.DockingHighRes: ::::::::::::::::::DOCK_MCM:::::::::::::::::::
core.pack.task: Packer task: initialize from command line()
core.pack.interaction_graph.interaction_graph_factory: Instantiating DensePDInteractionGraph
core.pack.pack_rotamers: built 4141 rotamers at 256 positions.

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preparation the fragment files for mutants


I have a protein with a loop and I want to made a single mutation or small insertion in the loop.
Do I need to prepare a new fragment file for protein which has a single mutation in the loop, or can I use the fragment file from parent protein?
Is it possible to avoid regeneration of the fragment file, as it takes a lot of time?

Thank you for you help.


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Does linker modeling exist?

Hi! Is there an existing application that will model a linker (fragment based) between two protein domains, and at the same time ensure that one domain does not clash with the other one? If there is such a thing can someone provide an example/command line etc. ?

Thanks in advance,

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compiling pyrosetta with python from macports

hello, is there any possibility of getting a pyrosetta source distribution that can be compiled with a non system-supplied python (i.e. from macports) on mac osx (10.5+)? i would greatly appreciate this as i am trying to incorporate pyrosetta into a GUI that uses external modules such as OpenGL, PyQt, PyMOL etc. and to me it would seem much easier to compile pyrosetta with a macports version of python than using the system python and having to go through the seemingly painful process of installing all the other dependencies. but i might be wrong.


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Criteria on the calculation of Irmsd of the protein-protein interface

I noticed that in the paper (Chaudhury, S., Berrondo, M., Weitzner, B. D., Muthu, P., Bergman, H., Gray, J. J.; (2011) Benchmarking and analysis of protein docking performance in RosettaDock v3.2. PLoSONE), the one of the evaluation criteria of docking performance, I_rmsd is defined differently from the CAPRI.

It is:
The interface is defined as all residues with an intermolecular distance of at most 4.0 A.

The CAPRI definition is:
the interface residues in the target were redefined as those having at least one atom within 10 A of an atom on the other molecule.

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Cannot get PyMOL_Observer to work on MacOS

The PyMOL_Mover is working but PyMOL_Observer() complains. Hope you can help:

MacOS 10.7.3, 64 bit system

Python 2.7.1 (r271:86832, Jul 31 2011, 19:30:53)
Type "copyright", "credits" or "license" for more information.

IPython 0.12 -- An enhanced Interactive Python.
? -> Introduction and overview of IPython's features.
%quickref -> Quick reference.
help -> Python's own help system.
object? -> Details about 'object', use 'object??' for extra details.

In [1]: from rosetta import *
In [2]: init()

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ab initio protein prediction using homologs

I have a question about the suggestion given in the documentations of ab initio modeling: "to increase your chance of sampling the correct topology, a diverse set of homologous sequences, preferably with sequence changes that may have a greater impact on sampling like deletions and differences in conserved positions, may also be run since a homologue may converge towards the native structure with significantly less sampling." After generating a number of decoys of these homologous sequences, it is recommended to map these decoys to the target sequence.

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