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Structural Bioinformatics Workshop

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http://bioinfo3d.math.tau.ac.il/FlexProt. Example : Trypsin/Trypsin inhibitor ... strands and sheets. The Holy Grail - Protein Folding. From Sequence to Structure. ... – PowerPoint PPT presentation

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Title: Structural Bioinformatics Workshop


1
Structural Bioinformatics Workshop
  • Max Shatsky
  • Email maxshats_at_post.tau.ac.il
  • Workshop home page http//bioinfo3d.cs.tau.ac.il/
  • (Follow Courses link)

2
Schedule
  • Introduction
  • Introduction to protein structure.
  • Introduction to pattern matching.
  • Protein structure alignment (comparison).
  • Rigid/Flexible case.
  • Protein Docking
  • Rigid/Flexible case.
  • GAMB library.

3
Grade Ingredients
  • GAMB exercise
  • Presentation and Design Review
  • Final Project
  • Software Engineering
  • Efficiency of Solution
  • Working Examples and Test Cases
  • Documentation
  • Knowledge of all project aspects

4
Bioinformatics - Computational Genomics
  • DNA mapping.
  • Protein or DNA sequence comparisons.
  • Exploration of huge textual databases.
  • In essence one- dimensional methods and
    intuition.

5
Structural Bioinformatics - Structural Genomics
  • Elucidation of the 3D structures of biomolecules.
  • Analysis and comparison of biomolecular
    structures.
  • Prediction of biomolecular recognition.
  • Handles three-dimensional (3-D) structures.
  • Geometric Computing. (a methodology shared by
    Computational Geometry, Computer Vision, Computer
    Graphics, Pattern Recognition etc.)

6
Protein Structural Comparison
Pseudoazurin - 1pmy
ApoAmicyanin - 1aaj
7
Algorithmic Solution
About 1 sec. Fischer, Nussinov, Wolfson 1990.
8
Multiple Structural Comparison Globins
9
FlexProt Flexible Protein Alignment
10
FlexProt Flexible Protein Alignment
http//bioinfo3d.math.tau.ac.il/FlexProt
11
Example Trypsin/Trypsin inhibitor
Figure from B. Honigs Labs web-site at Columbia
University.
12
Introduction to Protein Structure
13
The central dogma
  • DNA ---gt mRNA ---gt Protein
  • A,C,G,T A,C,G,U A,D,..Y
  • Guanine-Cytosine T-gtU
  • Thymine-Adenine
  • 4 letter alphabets 20 letter
    alphabet
  • Sequence of nucleic acids seq of
    amino acids

14
When genes are expressed, the genetic information
(base sequence) on DNA is first transcribed
(copied) to a molecule of messenger RNA in a
process similar to DNA replication. The mRNA
molecules then leave the cell nucleus and enter
the cytoplasm, where triplets of bases ((codons)
forming the genetic code specify the particular
amino acids that make up an individual
protein. This process, called translation, is
accomplished by ribosomes (cellular components
composed of proteins and another class of RNA)
that read the genetic code from the mRNA, and
transfer RNAs (tRNAs) that transport amino
acids to the ribosomes for attachment to the
growing protein. (From www.ornl.gov/hgmis/public
at/primer/ )
15
Amino acids and the peptide bond
Cb first side chain carbon (except for glycine).
16
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17
Wire-frame or ribbons display
18
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19
Geometric Representation
3-D Curve vi, i1n
20
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21
Secondary structure
22
? strands and sheets
  • Hydrogen bonds.

23
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25
The Holy Grail - Protein Folding
  • From Sequence to Structure.
  • Relatively primitive computational folding models
    have proved to be NP complete even in the 2-D
    case.

26
Determination of protein structures
  • X-ray Crystallography
  • NMR (Nuclear Magnetic Resonance)
  • EM (Electron microscopy)

27
An NMR result is an ensemble of models
  • Cystatin (1a67)

28
The Protein Data Bank (PDB)
  • International repository of 3D molecular data.
  • Contains x-y-z coordinates of all atoms of the
    molecule and additional data.
  • http//pdb.tau.ac.il
  • http//www.rcsb.org/pdb/

29
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31
Why bother with structureswhen we have sequences
?
  • In evolutionary related proteins structure is
    much better preserved than sequence.
  • Structural motifs may predict similar
  • biological function .
  • Getting insight into protein folding.
  • Recovering the limited (?) number of protein
  • folds.

32
Applications
  • Classification of protein databases by structure.
  • Search of partial and disconnected structural
    patterns in large databases.
  • Extracting Structure information is difficult, we
    want to extract new folds.

33
Applications (continued)
  • Speed up of drug discovery.
  • Detection of structural pharmacophores in an
    ensemble of drugs (similar substructures in
    drugs acting on a given receptor
    pharmacophore).
  • Comparison and detection of drug receptor active
    sites (structurally similar receptor cavities
    could bind similar drugs).

34
Structural Bioinformatics Lab Goals
Development of state of the art algorithmic
methods to tackle major computational tasks
in protein structure analysis, biomolecular
recognition, and Computer Assisted Drug
Design. Establish truly interdisciplinary
collaboration between Life and Computer
Sciences.
35
Object Recognition
36
Geometric Task
Given two configurations of points in the
three dimensional space,
find those rotations and translations of one
of the point sets which produce large
superimpositions of corresponding 3-D
points.
37
Geometric Task (continued)
  • Aspects
  • Object representation (points, vectors, segments)
  • Object resemblance (distance function)
  • Transformation (translations, rotations, scaling)

38
Transformations
  • Translation
  • Translation and Rotation
  • Rigid Motion (Euclidian Trans.)
  • Translation, Rotation Scaling

39
Distance Functions
  • Two point sets Aai i1n
  • Bbj j1m
  • Pairwise Correspondence
  • (ak1,bt1) (ak2,bt2) (akN,btN)

(1) Exact Matching aki bti0
(2) RMSD (Root Mean Square Distance)
Sqrt( Saki bti2/N) lt e
  • Hausdorff distance h(A,B)maxa?A minb?B a
    b
  • H(A,B)max(
    h(A,B), h(B,A))
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