Rosetta Steven Bitner. Objectives Introduction How Rosetta works How to get it How to install/use it.

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Presentation transcript:

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

TOP-7 protein designed, or synthesized, using Rosetta

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 (Energy functions)

How Rosetta Works (Energy functions) cont.

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 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 User guide

Using Rosetta Rosetta on-line Server – 200 residues at a time Robetta site – down until mid October ’06 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

Input PDB file 1HOE– displayed using PyMol

Output PDB file 1HOE – displayed using PyMol

1 u b q Before → After

Software used for this presentation Rosetta – release Rosetta Design Server PyMol for visualization RCSB PDB

References Rosetta Design Web Server Protein Structure Prediction Using Rosetta, Numerical Computer Methods, C.A. Rohl, C.E. Strauss, K.M. Misura, D. Baker, pp , 2004 README documentation included with rosetta2.0.1 Rosetta Website David Baker Lab Homepage