220 likes | 302 Views
Rosetta. Steven Bitner. Objectives. Introduction How Rosetta works How to get it How to install/use it. Introduction. Developed in the David Baker lab at University of Washington Winner of CASP (Critical Assessment of Structure Prediction) competition at Lawrence Livermore Labs, CA
E N D
Rosetta Steven Bitner
Objectives • Introduction • How Rosetta works • How to get it • How to install/use it
Introduction • Developed in the David Baker lab at University of Washington • Winner of CASP (Critical Assessment of Structure Prediction) competition at Lawrence Livermore Labs, CA • Implies that Rosetta is the best de novo predictor • Rosetta is a protein prediction and docking software package • Also used to design proteins from (nearly) arbitrary 3-D shapes • November, 2003, ‘Top-7’ first synthetic protein • Rosetta home • Human Proteome Folding Project • Also called the World Community Grid
How Rosetta Works • Minimize energy in the folded state • Uses a combination of energy formulas based on the likelihood of particular structures, and the fitness of the sequence • Side-chains simplified to a centroid located at center of mass of the side-chain • Average of observed side-chain centroids in known structures • Local sequence does not decide the local structure, it only biases the decision • Non-local favorable conditions • Buried hydrophobic fragments • Paired β strands • Specific side-chain interactions
How Rosetta Works cont. • Side-chains are added using Monte Carlo methods • Overlaps of side-chain centroids and backbone atoms are penalized • Uses probabilistic β-strand pairing and β-sheet patterns • Fragment Insertion - more later • Fragment Assembly - more later
Fragment Insertion • Finds three and nine residue fragments from known library and replaces unknown torsion angles with the ‘known’ ones • Scores all windows of three and nine residues • Create fragment list with the 200 best three residue and 200 best nine residue fragments
Fragment Assembly • Randomly choose a nine residue fragment from the top 25 fragments in the ranked list • Score this replacement, negatives are kept • Each simulation chooses a different random start and attempts 28,000 nine residue insertions • Next 8,000 attempted three residue insertions are scored with the overall structure
Why it’s Fast • Changes multiple angles simultaneously by using fragments from the library • Angular changes are discrete, not continuous
Getting the Software • Go to the website (bakerlab.org) • Register by clicking on Rosetta Licensing Information • Go to link in email that is sent to you • Download
Installing software • Upload onto a Linux machine, or other supported platform (see README_platform) • UTD’s Apache server does not work • Unpack using tar –zxvf ‘filename’ • Go into rosetta++ directory • Make gcc • Takes about 20 minutes • This is the standard version
Different install versions • Other ways to install than make gcc • See the README in rosetta++ directory • GCCDEBUG – for use if you plan on making updates to the software
Using the downloaded software • PDB file must be in the same directory as the program or the paths.txt file must be updated • paths.txt must be updated for the data source the default is a non-existant directory • User guide – assumes a good knowledge of the system
Using Rosetta • Rosetta on-line Server – 200 residues at a time http://rosettadesign.med.unc.edu/index.html • Robetta site – down until mid October ’06 http://robetta.bakerlab.org/ • Downloaded software • Can use res files to specify portions of the backbone, or you can select the residues that you wish to pack on the web server
Interpreting results • Output file fields • Rosetta Commons site also has similar document except the energy labels use E for energy in stead of LJ and LK for Lennard-Jones and Lazaridis-Karplus respectively as the prefix • E.g. Lennard-Jones attractive score is Eatr in the Rosetta commons output file and LJatr in the Rosetta Design output file
Software used for this presentation • Rosetta – release 2.1.0 • Rosetta Design Server http://rosettadesign.med.unc.edu/index.html • PyMol for visualization • RCSB PDB http://www.rcsb.org/pdb/Welcome.do
References • Rosetta Design Web Server http://rosettadesign.med.unc.edu/documentation.html • Protein Structure Prediction Using Rosetta, Numerical Computer Methods, C.A. Rohl, C.E. Strauss, K.M. Misura, D. Baker, pp. 66-93, 2004 • README documentation included with rosetta2.0.1 • Rosetta Website https://www.rosettacommons.org/ • David Baker Lab Homepage http://www.bakerlab.org/