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Protein Structure and Prediction
Michael Strong, Ph.D.Integrated Center for Genes, Environment, and HealthNational Jewish Health
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Why do we care about protein structuresStructure leads to Function – Enzymes, Structural (Cell Wall), Protein Interactions (host-pathogen), Replication, Transcription, Translation
(Binds to receptors on a cell surface, attached carbohydrades help it evade immune system)
Shapes the virus, enables budding
Protects the RNA viral genome
Ebola Virus-RNA genome-Encodes 7 proteins
To make new copies of RNA genome
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Why do we care about protein structuresCombining Structure and Genomic Information- Help us understand phylogeny and implications of mutations
Science 12 September 2014: Vol. 345 no. 6202 pp. 1369-1372
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Why do we care about protein structuresCombining Structure and Genomic Information- Help us understand phylogeny and implications of mutations
Drug Resistance
Rifampin
Tuberculosis
rpoB drug target
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Why do we care about protein structuresCombining Structure and Genomic Information- Help us understand phylogeny and implications of mutations
Homology model of CFTR structure, with common mutation F508 .PNAS 3256–3261, 105:9
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Experimental Approach
PQITLWKRPLVTIRIGGQLKEALLDTGADDTVLEEMNLPGKWKPKMIGGIGGFIKVRQYDQIPIEICGHKAIGTVLVGPT PVNIIGRNLLTQIGCTLNF
From Sequence to Structure
HIV Protease
HIV ProteaseWith Inhibitor
X-ray CrystallographyNMRCryo-Electron Microscopy
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Computational Approach
From Sequence to Structure
MNPNQKIITIGSVCMTIGMANLILQIGNIISIWISHSIQLGNQN QIETCNQSVITYENNTWVNQTYVNISNTNFAAGQSVVSVKLAGNSSLCPVSGWAIYSK DNSVRIGSKGDVFVIREPFISCSPLECRTFFLTQGALLNDKHSNGTIKDRSPYRTLMS CPIGEVPSPYNSRFESVAWSASACHDGINWLTIGISGPDNGAVAVLKYNGIITDTIKS WRNNILRTQESECACVNGSCFTVMTDGPSNGQASYKIFRIEKGKIVKSVEMNAPNYHY EECSCYPDSSEITCVCRDNWHGSNRPWVSFNQNLEYQIGYICSGIFGDNPRPNDKTGS CGPVSSNGANGVKGFSFKYGNGVWIGRTKSISSRNGFEMIWDPNGWTGTDNNFSIKQD IVGINEWSGYSGSFVQHPELTGLDCIRPCFWVELIRGRPKENTIWTSGSSISFCGVNS DTVGWSWPDGAELPFTIDK"
H1N1 NA
Homology ModelingProtein ThreadingAb initio
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Protein Building Blocks
Typical Protein Sequence MNPNQKIITIGSVCMTIGMANLILQIGNIISIWISHSIQLGNQN
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Protein Building Blocks
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Amino Acid Side Chain (R groups)
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Amino Acid Side Chain (R groups)
DisulfideBonds
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Amino Acid Side Chain (R groups)
-acidic
+basic
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DNA
Folded Protein
Most Proteins Spontaneously Fold
RNA
Some proteins need chaperones for correct folding
Transcribed by RNA polymerase
Translated by Ribosome
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native state, Folded protein
spontaneous self-organisation (~1 second)
Most Proteins Spontaneously Fold
Folded protein
Unfolded protein
Denaturing conditions
Native conditions
ChristianAnfinsen’s Experiment1950s
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Most Proteins Spontaneously Fold
Important to Computational Biologists, because this suggests that all information relating to the correct folding of a protein is contained in it’s primary amino acid sequence, but …
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Most Proteins Spontaneously Fold
But Proteins lack easy rules for folding as compared to DNA
ProteinDNA
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Many Factors Influence Protein Folding
Protein
Proteins Assume the Lowest Energy Structure
Factors that influence folding include:1.Hydrophobic Interactions / collapse (particularly within the core)2.Hydrogen bonds – lead to secondary structures3.Disulfide Bonds (Cysteine residues)4.Salt Bridges / Ionic Interactions (among charged residues)5.Multimeric interactions with same type or other proteins
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Common Secondary StructuresAlpha helix
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Common Secondary StructuresBeta Sheet
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Common Secondary StructuresLoop Regions
Loop
Strong M et al, Proc National Academy of Sciences vol. 103 no. 21, 8060–8065, 2006
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Example - Hemoglobin
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Fluoroquinolone Target gyrACrystal Structure
Rifampin targetrpoBHomology Model
Diversity of Protein Structures
Streptomycin resistancegidB Homology model
Isoniazid TargetinhACrystal Structure
EthionamideTarget, inhACrystal StructureIsoniazid Activating
Enzyme, KatGCrystal Structure
Streptomycin ResistancerpsL Homology model
PyrazinamideActivating enzymepncACrystal Structure
A B C D
E F G H
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Experimental Methods of Structure DeterminationX-ray crystallographyHigh resolution structure determination
Grow a protein Crystal
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Experimental Methods of Structure DeterminationX-ray crystallographyHigh resolution structure determination
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Experimental Methods of Structure DeterminationX-ray crystallographyHigh resolution structure determination
•Intensities and phases of all reflections are combined in a Fourier transform to provide maps of electron density
Phases determined by using heavy metals or selenomethionine (MAD)
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• Smaller Proteins than X-ray • Distances between pairs of hydrogen
atoms• Lots of information about dynamics• Requires soluble, non-aggregating
material• Assignment sometimes
difficult
Experimental Methods of Structure DeterminationNMR – Nuclear Magnetic ResonanceHigh resolution structure determination
NOE cross-peak if they are within 5.0 Å
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• Low to medium resolution ~10-15Å
• Limited information about dynamics
• Can be used for very large molecules and complexes
Experimental Methods of Structure DeterminationCryo Electron MicroscopyLow to medium resolution structure determination
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Database of Protein StructuresPDB – Protein Data Bank
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Database of Protein StructuresPDB – Protein Data Bank
104,125 structures as of 10/20/2014
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Database of Protein StructuresPDB – Protein Data Bank
Even so, the number of solved structures greatly lags behind the rate of new genes being sequenced … Solution: Computational Structural Methods
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GenBank Sequences
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• Atoms in pdb files are defined by their Cartesian coordinates:
Database of Protein StructuresPDB – Protein Data Bank Files
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Visualization of PDB filesPymol, Jmol, Chimera, etc
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Visualization of PDB filesPymol, Jmol, Chimera, etc
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DALI Structural AlignmentsAlign Protein Structures, Structure SuperpositionGenerates a comparison matrix (transform protein into a 2D array of distances between C-alpha atoms. Z score reflects reliability, lowest RMSD identified
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Computational Approach
From Sequence to Structure
MNPNQKIITIGSVCMTIGMANLILQIGNIISIWISHSIQLGNQN QIETCNQSVITYENNTWVNQTYVNISNTNFAAGQSVVSVKLAGNSSLCPVSGWAIYSK DNSVRIGSKGDVFVIREPFISCSPLECRTFFLTQGALLNDKHSNGTIKDRSPYRTLMS CPIGEVPSPYNSRFESVAWSASACHDGINWLTIGISGPDNGAVAVLKYNGIITDTIKS WRNNILRTQESECACVNGSCFTVMTDGPSNGQASYKIFRIEKGKIVKSVEMNAPNYHY EECSCYPDSSEITCVCRDNWHGSNRPWVSFNQNLEYQIGYICSGIFGDNPRPNDKTGS CGPVSSNGANGVKGFSFKYGNGVWIGRTKSISSRNGFEMIWDPNGWTGTDNNFSIKQD IVGINEWSGYSGSFVQHPELTGLDCIRPCFWVELIRGRPKENTIWTSGSSISFCGVNS DTVGWSWPDGAELPFTIDK"
H1N1 NA
Secondary Structure PredictionAlpha Helix, Beta Strand, or Other
Tertiary Predictions:
1.Homology Modeling2.Fold Recognition3.De Novo Protein Structure Prediction
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Secondary Structure Prediction-probability of amino acid to be in a alpha helix, Beta strand, or other (coil/loop) based on known structures.
-Chou-Fasman (short runs of amino acids), GOR (Bayesian, takes neighbors into account)
- helices – no prolines, periodicity 3.6 residues/turn- strands – alternating hydropathy, or ends hydrophillic and
center hydrophobic-other – small, polar, flexible residues, and prolines
But, stalled at 55- 60% accuracy
Also used position specific profiles based on multiple sequence alignments (evolutionary information) (ie insertion/deletion more likely to be in coil/turn), PSI BLAST and HMM, NN and SVM (improved to about 75-80%)
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Secondary Structure Prediction
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But we really want to know how the protein folds in three dimensions
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CASP - Critical Assessment of Techniques for Protein Structure Prediction
• Started in 1994, Helped push the field of structure prediction•“Contest-like” setup•Catagories include:
•Homology Modeling / Comparative Modeling•Fold Recognition / Threading•Ab Initio, De novo•Partially vs. Automated Methods (now quite similar results)
Goal: Predict structures of solved but unpublished/unreleased structures (used to evaluate predictions. Every year, predictions / algorithms get better
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Comparative Modeling “Homology Modeling”• Proteins that have similar sequences (i.e., related by evolution) are likely to have similar three-dimensional structures
1. BLAST sequence of Interest against PDB to identify a template•Multiple templates can be used if desired•Templates with Ligands bound can be used to identify binding sites and interacting residues in the homology model
Sequence identity required depends on protein length. A good rule of thumb is to have at least 40% sequence identity. Higher sequence identity is best. Lower than 25% is not reliable (zone of uncertainty)
Above 75% sequence identity, usually quite reliable homology model
Accurate sequence alignments very important
Programs include Modeller and Swiss Model
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Comparative Modeling “Homology Modeling”
Steps include:1.Template recognition and initial alignment2.Alignment Correction (Multiple Sequence Alignment can Help)3.Backbone Generation (transfer coordinates from template)4.Loop Modeling (loops hard to predict with insertions)5.Side Chain Modeling (usually similar tortion angles at high sequenc ID)6.Model Optimization (minor energy minimization steps or restrain some atom positions)7.Model Validation (Higher ID more accurate usually, Calculate energy, or normality index (bond length, tortion angles))8.Iteration (to refine)
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Protein Threading§ Generalization of homology modeling method• Homology Modeling: Align sequence to sequence• Threading: Align sequence to structure (templates)For each alignment, the probability that that each amino acid residue would occur in such an environment is calculated based on observed preferences in determined structures.§ Rationale:• Limited number of basic folds found in nature• Amino acid preferences for different structural environments provides sufficient information to choose the best-fitting protein fold (structure)
Protein Threading, Fold RecognitionOften, seemingly unrelated proteins adopt similar folds.-Divergent evolution, convergent evolution. For sequences with low or no sequence homology
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Fold recognition• The number of possible protein structures/folds is limited (large number of sequences but relatively few folds (some estimate ~1000)) (most apparent when 50% of structures with no seq homology were solved and had folds similar to known structures) 90% of new structures deposited in PDB have similar folds to those already known
• Proteins that do not have similar sequences sometimes have similar three-dimensional structures (such as B-barrel TIM fold)
• A sequence whose structure is not known is fitted directly (or “threaded”) onto a known structure and the “goodness of fit” is evaluated using a discriminatory function
• Need ways to move model closer to the native structure
3.6 Å5% ID
NK-lysin (1nkl) Bacteriocin T102/as48 (1e68)
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Ab initio prediction of protein structure – concept
Difficult because search space is huge. Much larger conformational space
Goal: Predict Structure only given its amino acid sequenceIn theory: Lowest Energy Conformation
• Go from sequence to structure by sampling the conformational space in a reasonable manner and select a native-like conformation using a good discrimination function
Difficult for sequences larger that 150aa
Rosetta (David Baker lab) one of best (CASP evaluation)
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Rosetta structure prediction2 phases1.Low-resolution phase – statistical scoring function and fragment assembly
A. local structure conformations using info from PDB (3 and 9mer stretches)
B. multiple fragment substitution simulated annealing – to find best arrangement of the fragments (Monte Carlo Search)
C. low resolution ensemble of decoy conformations
2. Atomic refinement phase using rotamers and small backbone angle moves (in populated regions of Ramachandran plot)
A. RefinementB. Then structures clustered based on RMSD C. Center of the Largest Clusters chosen as
representative folds (likely to be correct fold)
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Quality AssessmentRamachandran Plot – Phi Psi anglesTo identify residues that may be in wrong conformationProcheck, What_check