Orientational degeneracy in the presence of one alignment tensor.

Similar documents
Theory and Applications of Residual Dipolar Couplings in Biomolecular NMR

Dipolar Couplings in Partially Aligned Macromolecules - New Directions in. Structure Determination using Solution State NMR.

Basics of protein structure

Introduction to Comparative Protein Modeling. Chapter 4 Part I

Design of a Novel Globular Protein Fold with Atomic-Level Accuracy

Presentation Outline. Prediction of Protein Secondary Structure using Neural Networks at Better than 70% Accuracy

Examples of Protein Modeling. Protein Modeling. Primary Structure. Protein Structure Description. Protein Sequence Sources. Importing Sequences to MOE

Molecular Modeling lecture 2

Protein Structure. W. M. Grogan, Ph.D. OBJECTIVES

Protein structure prediction. CS/CME/BioE/Biophys/BMI 279 Oct. 10 and 12, 2017 Ron Dror

THE TANGO ALGORITHM: SECONDARY STRUCTURE PROPENSITIES, STATISTICAL MECHANICS APPROXIMATION

Protein Dynamics. The space-filling structures of myoglobin and hemoglobin show that there are no pathways for O 2 to reach the heme iron.

Template Free Protein Structure Modeling Jianlin Cheng, PhD

Presenter: She Zhang

Physiochemical Properties of Residues

Protein Structure Prediction and Display

Useful background reading

CMPS 6630: Introduction to Computational Biology and Bioinformatics. Tertiary Structure Prediction

CMPS 3110: Bioinformatics. Tertiary Structure Prediction

Protein Secondary Structure Prediction

Protein Structure Prediction II Lecturer: Serafim Batzoglou Scribe: Samy Hamdouche

Protein Structure Determination Using NMR Restraints BCMB/CHEM 8190

Protein Structure Prediction, Engineering & Design CHEM 430

Protein Structure Basics

Sequence analysis and comparison

CAP 5510 Lecture 3 Protein Structures

Protein Structure Determination Using NMR Restraints BCMB/CHEM 8190

1) NMR is a method of chemical analysis. (Who uses NMR in this way?) 2) NMR is used as a method for medical imaging. (called MRI )

Objective: Students will be able identify peptide bonds in proteins and describe the overall reaction between amino acids that create peptide bonds.

COMP 598 Advanced Computational Biology Methods & Research. Introduction. Jérôme Waldispühl School of Computer Science McGill University

HOMOLOGY MODELING. The sequence alignment and template structure are then used to produce a structural model of the target.

BIRKBECK COLLEGE (University of London)

NMR, X-ray Diffraction, Protein Structure, and RasMol

Dipolar Couplings in Partially Aligned Macromolecules - New Directions in Structure Determination using Solution State NMR.

Homology Modeling (Comparative Structure Modeling) GBCB 5874: Problem Solving in GBCB

Bio nformatics. Lecture 23. Saad Mneimneh

Interpreting and evaluating biological NMR in the literature. Worksheet 1

Protein folding. α-helix. Lecture 21. An α-helix is a simple helix having on average 10 residues (3 turns of the helix)

Molecular Modeling Lecture 7. Homology modeling insertions/deletions manual realignment

RNA and Protein Structure Prediction

Prediction and refinement of NMR structures from sparse experimental data

Bioinformatics. Macromolecular structure

Supersecondary Structures (structural motifs)

PROTEIN'STRUCTURE'DETERMINATION'

PROTEIN STRUCTURE AMINO ACIDS H R. Zwitterion (dipolar ion) CO 2 H. PEPTIDES Formal reactions showing formation of peptide bond by dehydration:

HSQC spectra for three proteins

Molecular Modeling. Prediction of Protein 3D Structure from Sequence. Vimalkumar Velayudhan. May 21, 2007

Residual Dipolar Couplings BCMB/CHEM 8190

From Amino Acids to Proteins - in 4 Easy Steps

Protein Structure Prediction

Homologous proteins have similar structures and structural superposition means to rotate and translate the structures so that corresponding atoms are

Dihedral Angles. Homayoun Valafar. Department of Computer Science and Engineering, USC 02/03/10 CSCE 769

Peptides And Proteins

Getting To Know Your Protein

Outline. Levels of Protein Structure. Primary (1 ) Structure. Lecture 6:Protein Architecture II: Secondary Structure or From peptides to proteins

Pymol Practial Guide

A.D.J. van Dijk "Modelling of biomolecular complexes by data-driven docking"

Steps in protein modelling. Structure prediction, fold recognition and homology modelling. Basic principles of protein structure

Residual Dipolar Couplings Measured in Multiple Alignment Media.

ALL LECTURES IN SB Introduction

Template Free Protein Structure Modeling Jianlin Cheng, PhD

Secondary Structure. Bioch/BIMS 503 Lecture 2. Structure and Function of Proteins. Further Reading. Φ, Ψ angles alone determine protein structure

Protein Structure: Data Bases and Classification Ingo Ruczinski

Get familiar with PDBsum and the PDB Extract atomic coordinates from protein data files Compute bond angles and dihedral angles

Protein Structure. Hierarchy of Protein Structure. Tertiary structure. independently stable structural unit. includes disulfide bonds

Secondary and sidechain structures

Molecular Modelling. part of Bioinformatik von RNA- und Proteinstrukturen. Sonja Prohaska. Leipzig, SS Computational EvoDevo University Leipzig

CMPS 6630: Introduction to Computational Biology and Bioinformatics. Structure Comparison

Assignment 2 Atomic-Level Molecular Modeling

I690/B680 Structural Bioinformatics Spring Protein Structure Determination by NMR Spectroscopy

Announcements. Primary (1 ) Structure. Lecture 7 & 8: PROTEIN ARCHITECTURE IV: Tertiary and Quaternary Structure

114 Grundlagen der Bioinformatik, SS 09, D. Huson, July 6, 2009

Protein Structures. Sequences of amino acid residues 20 different amino acids. Quaternary. Primary. Tertiary. Secondary. 10/8/2002 Lecture 12 1

THE UNIVERSITY OF MANITOBA. PAPER NO: 409 LOCATION: Fr. Kennedy Gold Gym PAGE NO: 1 of 6 DEPARTMENT & COURSE NO: CHEM 4630 TIME: 3 HOURS

BCH 4053 Spring 2003 Chapter 6 Lecture Notes

Protein Bioinformatics Computer lab #1 Friday, April 11, 2008 Sean Prigge and Ingo Ruczinski

Protein Structure Determination using NMR Spectroscopy. Cesar Trinidad

Outline. Levels of Protein Structure. Primary (1 ) Structure. Lecture 6:Protein Architecture II: Secondary Structure or From peptides to proteins

Molecular Modeling lecture 4. Rotation Least-squares Superposition Structure-based alignment algorithms

SUPPLEMENTARY INFORMATION. doi: /nature07461

CS273: Algorithms for Structure Handout # 2 and Motion in Biology Stanford University Thursday, 1 April 2004

BCMP 201 Protein biochemistry

HIV protease inhibitor. Certain level of function can be found without structure. But a structure is a key to understand the detailed mechanism.

Sequential Assignment Strategies in Proteins

Lecture 26: Polymers: DNA Packing and Protein folding 26.1 Problem Set 4 due today. Reading for Lectures 22 24: PKT Chapter 8 [ ].

Molecular Modeling lecture 17, Tue, Mar. 19. Rotation Least-squares Superposition Structure-based alignment algorithms

Conformational Geometry of Peptides and Proteins:

StructuralBiology. October 18, 2018

Introduction to" Protein Structure

NMR Spectroscopy of Polymers

Biomolecules: lecture 10

Motif Prediction in Amino Acid Interaction Networks

Solving the three-dimensional solution structures of larger

Review. Membrane proteins. Membrane transport

ion mobility spectrometry IR spectroscopy

NMR BMB 173 Lecture 16, February

1. Amino Acids and Peptides Structures and Properties

Molecular modeling with InsightII

Protein structure prediction. CS/CME/BioE/Biophys/BMI 279 Oct. 10 and 12, 2017 Ron Dror

Protein Structures: Experiments and Modeling. Patrice Koehl

Transcription:

Orientational degeneracy in the presence of one alignment tensor. Rotation about the x, y and z axes can be performed in the aligned mode of the program to examine the four degenerate orientations of two modules as shown below - The180 rotations about the axes of the alignment tensor generate multiple solutions for the relative orientations of the two modules. The four different orientations of module 1 relative to module 2 are shown above. The dotted line indicates the covalent junction between the modules. This covalent information may in certain cases be sufficient to select the most probable conformation. The residual dipolar couplings considered here (between spins from covalently bound nuclei) contain purely orientational information; this means that there is complete translational freedom in all Cartesian (x,y,z) directions. Where possible either covalent, experimental or non-bonded interactions can of course be used to place different modules with respect to each other. The program Module will calculate, and localise the steric contacts due to atom-overlap between modules (left).

RDC for refining homology-based models. A number of groups have recognised the obvious power of RDC's to either verify or refine structural models. It is something of a revolution for the solution state structural biologist to have access to coherent structural information from throughout the molecule, as soon as backbone assignment has been completed. The increasing number of experimentally determined structures available in databases have increased the possibility of structure modelling from primary sequence alone, on the basis of sequence similarity. RDC's measured in secondary structural elements (so that the local geometry can be assumed to be relatively good, and tensors can be determined from sufficient couplings) can be used to either verify, or refine, the predicted folds. This idea is illustrated here using the program Module, although the approach has been suggested by numerous authors (Meiler et al 2000, Chou et al 2000, Annila et al 1999) in recent years. In this example the global fold is assumed to be known, but the relative orientation of secondary structural elements is not precisely determined (this may be the case for example when a homology-based model is available). In the first case we have selected all of the secondary structural elements to be part of the same module. If we determine a single tensor for this selection, assuming therefore that the relative orientation is correct, the fit is already quite good, as shown from the correlation plots for the different coupling types. Nevertheless there are significant differences between calculated and experimental values.

We now divide the secondary structural elements into four separate modules - the three helices and the central beta-sheet; If we fit these modules separately to independent tensors we get better correlations between experimental and calculated values. If we look at the orientation of the tensors relative to the separate structural elements in the pdb frame we can see why this might be - The alignment tensors of the different motifs are differently oriented with respect to the pdb frame. The axial and rhombic components have similar values, suggesting that the orientation of the secondary structural elements was not quite right in the initial model. In particular the C-terminal helix, (blue) seems to be tilted significantly relative to the others.

The program can now be used to orient the motifs into a common frame so that each of the alignment tensors is coaxial. All four modules are then aligned with the same tensor axes. In this case a large number of possible solutions exist for the different orientations of the modules, due to the 4-fold degeneracy for each motif. The program can test these different possibilities to find the geometry, which is in best agreement. The structure will then need to be refined in a molecular dynamics type calculation to ensure that non-bond and covalent considerations are respected. Structural Homology from Database Comparisons with RDC. An obvious development of this kind of analysis is the direct comparison of measured sets of RDC with expected couplings from structural motifs present in databases. It has indeed recently have shown that RDC can also be used to rapidly identify complete or partial homologous fold by comparison with structures of different characteristic length, present in the available databases (Annila et al 1999, Meiler et al 2000, Andrec et al 2001). Delaglio et al 2000, have also shown that in the case where extensive data are available from two alignment media, it is possible to identify 7-amino acid segments from the structural database which are in best agreement with a sliding window of experimental RDC's along the primary chain of the protein of interest, and superimpose the common regions to define the fold of the molecule (Molecular Fragment Replacement). The improved structural definition available from two different alignment media will be discussed below.