Protein structure determination prediction Tertiary protein structure protein

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Protein structure determination & prediction

Protein structure determination & prediction

Tertiary protein structure: protein folding Three main approaches: [1] experimental determination (X-ray crystallography, NMR)

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

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 k. D) -- Does not require crystallization

Steps in obtaining a protein structure Target selection Obtain, characterize protein Determine, refine, model

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

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

Nuclear magnetic resonance spectroscopy http: //en. wikipedia. org/wiki/Nuclear_magnetic_resonance

Article

Article

Ab initio protein prediction n Starts with an attempt to derive secondary structure from

Ab initio protein prediction n 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

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

Fold recognition (structural profiles) Attempts to find the best fit of a raw polypeptide sequence onto a library of known protein folds n 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 n

Threading n Takes the fold recognition process a step further: ¨ Empirical-energy functions for

Threading n 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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