Bioinformatics
Download
1 / 36

Macromolecular structure - PowerPoint PPT Presentation


  • 255 Views
  • Uploaded on
  • Presentation posted in: General

Bioinformatics. Macromolecular structure. Contents. Determination of protein structure Structure databases Secondary structure elements (SSE) Tertiary structure Structure analysis Structure alignment Domain recognition Structure prediction Homology modelling

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha

Download Presentation

Macromolecular structure

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript


Bioinformatics

Macromolecular structure


Contents

  • Determination of protein structure

  • Structure databases

  • Secondary structure elements (SSE)

  • Tertiary structure

  • Structure analysis

    • Structure alignment

    • Domain recognition

  • Structure prediction

    • Homology modelling

    • Threading/folder recognition

    • Secondary structure prediction

    • ab initio prediction


Structure

Determination of protein structure

Jacques van Heldenjvanheld@ucmb.ulb.ac.be


Crystallisation

Hanging drop method / vapour diffusion method

Microscope

1-Dilute protein solution

Microscope slide

many different

conditions of 1&2

must be tried

2-Concentrated salt solution

Crystal

Slide courtesy from Shoshana Wodak


Determination of protein structure

Diffraction pattern

Atomic model

Slide courtesy from Shoshana Wodak


The resolution problem

q

q

q

A high resolution protein structure : 1.5 - 2.0 Å resolution

Slide courtesy from Shoshana Wodak


Nuclear Magnetic Resonance (NMR)

Source: Branden & Tooze (1991)


Interatomic forces

  • Covalent interactions

  • Hydrogen bonds

  • Hydrophobic/hydrophilic interactions

  • Ionic interactions

  • van der Waals force

  • Repulsive forces


Structure

Structure databases

Jacques van Heldenjvanheld@ucmb.ulb.ac.be


Structure databases

  • PDB (Protein database)

    • Official structure repository

  • SCOP (Stuctural Classification Of Proteins)

    • Structure classification. Top level reflect structural classes.The second level, called Fold, includes topological and similarity criteria.

  • CATH (Class, Architecture, Topology and Homologous superfamily)


PDB entry header


Class

Architecture

Topology

CATH - A protein domain classification

  • In CATH, protein domains are classified according to a tree with 4 levels of hierarchically

    • Class

    • Architecture

    • Topology

    • Homology

Figure from Shoshana Wodak


Classifications of protein structures (domains)

CATH: structural classification of proteins,

[http://www.biochem.ucl.ac.uk/bsm/cath/]

SCOP: Structural classification of proteins

[http://scop.mrc-lmb.cam.ac.uk/scop/]

FSSP:Fold classification based on structure alignments

[http://www.sander.ebi.ac.uk/fssp/]

HSSP: Homology derived secondary structure assignments

[http://www.sander.ebi.ac.uk/hssp/]

DALI:Classification of protein domains

[http://www.ebi.ac.uk/dali/domain/]

VAST: structural neighbours by direct 3D structure comparison

[http://www.ncbi.nlm.nih.gov:80/Structure/VAST/vast.shtml]

CE: Structure comparisons by Combinatorial Extension

[http://cl.sdsc.edu/ce.html]

Slide courtesy from Shoshana Wodak


Books

  • Branden, C. & Tooze, J. (1991). Introduction to protein structure. 1 edit, Garland Publishing Inc., New York and London.

  • Westhead, D.R., J.H. Parish, and R.M. Twyman. 2002. Bioinformatics. BIOS Scientific Publishers, Oxford.

  • Mount, M. (2001). Bioinformatics: Sequence and Genome Analysis. 1 edit. 1 vols, Cold Spring Harbor Laboratory Press, New York.

  • Gibas, C. & Jambeck, P. (2001). Developing Bioinformatics Computer Skills, O'Reilly.


Structure

Secondary structure elements

Jacques van Heldenjvanheld@ucmb.ulb.ac.be


Secondary structure - -helix

Carbon

Nitrogen

Oxygen

3.6 residues

hydrogen bond

Source: Branden & Tooze (1991)


Hydrophobicity of side-chain residues in helices

Blue: polar

Red: basic or acidic

Source: Branden & Tooze (1999)


Secondary structure -  sheets

Antiparallel

Parallel

Source: Branden & Tooze (1991)


Secondary structure - twist of  sheets

Mixed  sheet

Source: Branden & Tooze (1991)


Angles of rotation

  • Each dipeptide unit is characterized by two angles of rotation

    • Phiaround the N-Calpha bond

    • Psiaround the Calpha-C bond

Image from Branden & Tooze (1999)


The Ramachandran map

Dipeptide unit

Dipeptide unit

Slide courtesy from Shoshana Wodak


Structure

Tertiary structure

Jacques van Heldenjvanheld@ucmb.ulb.ac.be


Retinol binding protein (PDB:1rpb)

-sheet

loop

-helix

Combinations of secondary structures


Bioinformatics

Analysis of structure

Jacques van Heldenjvanheld@ucmb.ulb.ac.be


Structure-structure alignment and comparison

Structure B

Structure A

Question: Is structure A similar to structure B ?

Approach: structure alignments

Slide courtesy from Shoshana Wodak


Analyzing conformational changes

Open form

Closed form

Citrate synthase, ligand induced conformational changes

Domain motion and small structural distortions

Slide courtesy from Shoshana Wodak


Defining Domains: What for?

  • Link between domain structure and function

Different structural domains

can be associated with

different functions

Enzyme active sites are

often at domain interfaces;

domain movements play

a functional role

DNA Methyltransferase

Cathepsin D

Slide courtesy from Shoshana Wodak


Methods for Identifying Domains

  • Underlying principle

    • Domain limits are defined by identifying groups of residues such that the number of contacts between groups is minimized.

N

N

C

C

4-cuts

1-cut

N

C

2-cuts

Slide courtesy from Shoshana Wodak


Lactate dehydrogenase

Domains From Contact Map

Slide courtesy from Shoshana Wodak


Structure

Structure prediction

Jacques van Heldenjvanheld@ucmb.ulb.ac.be


Methods for structure prediction

  • Homology modelling

    • Building a 3D model on the basis of similar sequences

  • Threading

    • Threading the sequence on all known protein structures, and testing the consistency

  • Secondary structure prediction

  • ab initio prediction of tertiary structure

    • For proteins of normal size, it is almost impossible to predict structures ab initio.

    • Some results have been obtained in the prediction of oligopeptide structures.


Homology modelling - steps

  • Similarity search

  • Modelling of backbone

    • Secondary structure elements

    • Loops

  • Modelling of side chains

  • Refinement of the model

  • Verification

    • Steric compatibility of the residues


Homology modelling - similarity search

  • Starting from a query sequence, search for similar sequences with known structure.

    • Search for similar sequences in a database of protein structures.

    • Multiple alignment.

    • A weight can be assigned to each matching protein (higher score to more similar proteins)

  • The higher is the sequence similarity, the more accurate will be the predicted structure.

    • When one disposes of structure for proteins with >70% similarity with the query, a good model can be expected.

    • When the similarity is <40%, homology modeling gives poor results.

    • The lack of available structures constitutes one of the main limitations to homology modeling

      • In 2004, PDB contains


Homology modelling - Backbone modelling

  • Modelling of secondary structure elements

    • a-helices

    • b-sheets

    • For each secondary structure element of the template, align the backbone of query and template.

  • Loop modelling

    • Databases of loop regions

    • Loop main chain depends on number of aa and neighbour elements (a-a, a-b, b-a, b-b)


Homology modelling - Side chain modelling

  • Side-chain conformation (model building and energy refinement)

    • Conserved side chains take same coordinates as in the template.

    • For non-conserved side chains, use rotamer libraries to determine the most favourable conformation.


Homology modelling - refinement

  • After the steps above have been completed, the model can be refined by modifying the positions of some atoms in order to reduce the energy.


ad
  • Login