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Rosetta

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

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Rosetta

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  1. Rosetta Steven Bitner

  2. Objectives • Introduction • How Rosetta works • How to get it • How to install/use it

  3. 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

  4. TOP-7 protein designed, or synthesized, using Rosetta

  5. 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

  6. How Rosetta Works (Energy functions)

  7. How Rosetta Works (Energy functions) cont.

  8. 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

  9. 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

  10. 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

  11. Why it’s Fast • Changes multiple angles simultaneously by using fragments from the library • Angular changes are discrete, not continuous

  12. 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

  13. 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

  14. 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

  15. 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

  16. 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

  17. 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

  18. Input PDB file 1HOE– displayed using PyMol

  19. Output PDB file 1HOE – displayed using PyMol

  20. 1 u b qBefore → After

  21. 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

  22. 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/

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