Automated Molecular Replacement

Slides:



Advertisements
Similar presentations
Curved Trajectories towards Local Minimum of a Function Al Jimenez Mathematics Department California Polytechnic State University San Luis Obispo, CA
Advertisements

Molecular Replacement in CCP4
Molecular Replacement
Search in electron density using Molrep
Medical Image Registration Kumar Rajamani. Registration Spatial transform that maps points from one image to corresponding points in another image.
Automated phase improvement and model building with Parrot and Buccaneer Kevin Cowtan
Learning Objectives: To understand what is meant by the term, ‘relative molecular mass’
A 3-D reference frame can be uniquely defined by the ordered vertices of a non- degenerate triangle p1p1 p2p2 p3p3.
Prediction to Protein Structure Fall 2005 CSC 487/687 Computing for Bioinformatics.
CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Homology Modeling Anne Mølgaard, CBS, BioCentrum, DTU.
The TEXTAL System for Automated Model Building Thomas R. Ioerger Texas A&M University.
A Molecular Replacement Pipeline Garib Murshudov Chemistry Department, University of York 
3. Crystals What defines a crystal? Atoms, lattice points, symmetry, space groups Diffraction B-factors R-factors Resolution Refinement Modeling!
. Protein Structure Prediction [Based on Structural Bioinformatics, section VII]
Protein structure prediction May 30, 2002 Quiz#4 on June 4 Learning objectives-Understand difference between primary secondary and tertiary structure.
Introduction to Bioinformatics - Tutorial no. 8 Predicting protein structure PSI-BLAST.
Automated protein structure solution for weak SAD data Pavol Skubak and Navraj Pannu Automated protein structure solution for weak SAD data Pavol Skubak.
Estimating Sums and Differences
Lesson 5 -1:. A benchmark is a number that is easy to use when you estimate. When estimating the sums and differences of fractions, we use the benchmarks.
Inverse Kinematics for Molecular World Sadia Malik April 18, 2002 CS 395T U.T. Austin.
Computational Structure Prediction Kevin Drew BCH364C/391L Systems Biology/Bioinformatics 2/12/15.
Chapter 9 Superposition and Dynamic Programming 1 Chapter 9 Superposition and dynamic programming Most methods for comparing structures use some sorts.
28 th March 2007 MrBUMP – Automated Molecular Replacement Ronan Keegan, Martyn Winn CCP4, Daresbury Laboratory.
28 Mar 06Automation1 Overview of developments within CCP4 Generation 1 ccp4i tasks Generation 2 isolated scripts / web service Generation 3 integrated.
Molecular Replacement
The process of replacing a number by another number that is close to the same value. What’s Our Rule for the Boss?
Modelling binding site with 3DLigandSite Mark Wass
Molecular Replacement Martyn Winn CCP4 group, Daresbury Laboratory, UK.
CSE554AlignmentSlide 1 CSE 554 Lecture 5: Alignment Fall 2011.
Authors Project Database Handler The project database handler dbCCP4i is a small server program that handles interactions between the job database and.
A Molecular Replacement Pipeline Garib Murshudov Chemistry Department, University of York 
A Molecular Replacement Pipeline Garib Murshudov Chemistry Department, University of York 
BALBES (Current working name) A. Vagin, F. Long, J. Foadi, A. Lebedev G. Murshudov Chemistry Department, University of York.
Data quality and model parameterisation Martyn Winn CCP4, Daresbury Laboratory, U.K. Prague, April 2009.
1 P9 Extra Discussion Slides. Sequence-Structure-Function Relationships Proteins of similar sequences fold into similar structures and perform similar.
Using CCP4 for PX Martin Noble, Oxford University and CCP4.
Computing Missing Loops in Automatically Resolved X-Ray Structures Itay Lotan Henry van den Bedem (SSRL)
Overview of MR in CCP4 II. Roadmap
Bulk Model Construction and Molecular Replacement in CCP4 Automation Ronan Keegan, Norman Stein, Martyn Winn.
MrBUMP – Molecular Replacement with Bulk Model Preparation Automated search model discovery and preparation for structure solution by molecular replacement.
Module 3 Protein Structure Database/Structure Analysis Learning objectives Understand how information is stored in PDB Learn how to read a PDB flat file.
CSE554AlignmentSlide 1 CSE 554 Lecture 8: Alignment Fall 2013.
1 MrBUMP – Molecular Replacement with Bulk Model Preparation Ronan Keegan, Martyn Winn CCP4 group, Daresbury Laboratory Como May 23rd 2006.
. Protein Structure Prediction. Protein Structure u Amino-acid chains can fold to form 3-dimensional structures u Proteins are sequences that have (more.
Protein Folding & Biospectroscopy Lecture 6 F14PFB David Robinson.
Direct Use of Phase Information in Refmac Abingdon, University of Leiden P. Skubák.
Protein Homologue Clustering and Molecular Modeling L. Wang.
17 th March 2008 MrBUMP progress report Ronan Keegan & Martyn Winn Daresbury Laboratory.
Fitting EM maps into X-ray Data Alexei Vagin York Structural Biology Laboratory University of York.
Topic 1 Roland Dunbrack. Modeling of Biological Units Model data files of single proteins may require –sequence alignment(s) to templates (entry and chain)
CCP4 Molecular Replacement Model Generation Create a CCP4i task for generating Molecular Replacement models. - Selecting suitable PDB entries, based on.
10/24/2014PHY 711 Fall Lecture 251 PHY 711 Classical Mechanics and Mathematical Methods 10-10:50 AM MWF Olin 103 Plan for Lecture 25: Rotational.
CSE 554 Lecture 8: Alignment
Stony Brook Integrative Structural Biology Organization
Computational Structure Prediction
Estimating Sums and Differences
2 Understanding Variables and Solving Equations.
CCP4 from a user perspective
2 Understanding Variables and Solving Equations.
Estimating Sums and Differences of Fractions and Mixed Numbers
Before: December 4, 2017 Solve each system by substitution. Steps:
Estimating Sums and Differences
Estimating Sums and Differences
MrBUMP: progress and plans
Low-Resolution Structures of Proteins in Solution Retrieved from X-Ray Scattering with a Genetic Algorithm  P. Chacón, F. Morán, J.F. Díaz, E. Pantos,
Ligand Binding to the Voltage-Gated Kv1
Binchen Mao, Rongjin Guan, Gaetano T. Montelione  Structure 
Database for MR.
Screw Rotation and Other Rotational Forms
Presentation transcript:

Automated Molecular Replacement Part 1: Automating Amore Make Amore as easy to use as Molrep, Phaser. Part 2: Construction of “best” model for Phaser Enable maximum number of structures to be solved using MR.

Amore Solution Process 1. Estimate number of molecules in Asymmetric unit (MATTHEWS). 2. Solve for first molecule (AUTO-AMORE) a) Rotation function. Euler angles { (α,β,γ) } b) Translation function. Euler angles + fractional translations { (x,y,z)} c) Fitting = Rigid Body Refinement 3. Solve for additional molecules. Extra translations. (iterative) 4. Final round of fitting 5. Apply rotations and translations to atom coordinates. (PDBSET ) 6. Merge into one pdb file. 7. Check for clashing (DISTANG)

Solution for n molecules Take top 5 (distinct) translation solutions from n – 1 molecule solution Take top 5 (distinct) rotation solutions Consider all possible combinations Search for translation solutions for 1 more molecule Score by summing correlation coefficients over all n molecules Sort solutions in order of decreasing score

Test Results Target Model % seq no. mols Solved 1n5b 1k6z 97 4 Yes 1nio 1ggp_A 1 1cv7 1gfl 96 1k6d 1o91 2 1mzr 1a80 51 1h5q 1v18a 34 12 No

Future developments Incorporation in Ronan’s pipeline Model Building using Arp/Warp

PART 2 Construction of “best model” for phaser Apply sequence alignment algorithm PSIBLAST : sequence – profile alignment FFAS : profile – profile alignment Modify template (Chainsaw) If Target R = Template R retain If not … R. Schwarzenbacher et al, Acta Cryst D60 1229, (2004)

Chainsaw Template Target Action >= Serine Prune to CG Alanine Prune to CB Glycine Prune to CA >= Alanine Add CB

Future work Use more sophisticated sequence alignment algorithms Apply to ensembles