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Protein structure determination

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Protein structure determination & prediction X-ray crystallography http://en.wikipedia.org/wiki/X-ray_diffraction Nuclear magnetic resonance spectroscopy Ab initio ... – PowerPoint PPT presentation

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Title: Protein structure determination


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Protein structure determination prediction
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Tertiary protein structure protein folding
Three main approaches 1 experimental
determination (X-ray crystallography,
NMR) 2 Comparative modeling (based on
homology) 3 Ab initio (de novo) prediction
(Dr. Ingo Ruczinski at JHSPH)
3
Experimental approaches to protein structure
1 X-ray crystallography -- Used to determine
80 of structures -- Requires high protein
concentration -- Requires crystals -- Able to
trace amino acid side chains -- Earliest
structure solved was myoglobin 2 NMR --
Magnetic field applied to proteins in
solution -- Largest structures 350 amino acids
(40 kD) -- Does not require crystallization
4
Steps in obtaining a protein structure
Target selection
Obtain, characterize protein
Determine, refine, model the structure
Deposit in database
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X-ray crystallography
  • http//en.wikipedia.org/wiki/X-ray_diffraction

Sperm Whale Myoglobin
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Nuclear magnetic resonance spectroscopy
http//en.wikipedia.org/wiki/Nuclear_magnetic_reso
nance
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Article
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Ab initio protein prediction
  • Starts with an attempt to derive secondary
    structure from the amino acid sequence
  • Predicting the likelihood that a subsequence will
    fold into an alpha-helix, beta-sheet, or coil,
    using physicochemical parameters or HMMs and ANNs
  • Able to accurately predict 3/4 of all local
    structures

14
Secondary structure prediction
Chou and Fasman (1974) developed an
algorithm based on the frequencies of amino acids
found in a helices, b-sheets, and
turns. Proline occurs at turns, but not in a
helices. GOR (Garnier, Osguthorpe, Robson)
related algorithm Modern algorithms use
multiple sequence alignments and achieve higher
success rate (about 70-75)
Page 279-280
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Fold recognition (structural profiles)
  • Attempts to find the best fit of a raw
    polypeptide sequence onto a library of known
    protein folds
  • A prediction of the secondary structure of the
    unknown is made and compared with the secondary
    structure of each member of the library of folds

18
Threading
  • Takes the fold recognition process a step
    further
  • Empirical-energy functions for residue pair
    interactions are used to mount the unknown onto
    the putative backbone in the best possible manner
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