Protein structure determination & prediction
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Transcript Protein structure determination & prediction
Protein structure
determination &
prediction
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)
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
Steps in obtaining a protein structure
Target selection
Obtain, characterize protein
Determine, refine, model the structure
Deposit in database
X-ray crystallography
http://en.wikipedia.org/wiki/X-ray_diffraction
Sperm Whale Myoglobin
Nuclear magnetic resonance spectroscopy
http://en.wikipedia.org/wiki/Nuclear_magnetic_resonance
Article
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
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
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
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