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Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10
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Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

Dec 21, 2015

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Page 1: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

Protein Structure and Prediction

Michael Strong, PhDNational Jewish Health11/16/10

Page 2: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

Experimental Approach

PQITLWKRPLVTIRIGGQLKEALLDTGADDTVLEEMNLPGKWKPKMIGGIGGFIKVRQYDQIPIEICGHKAIGTVLVGPT PVNIIGRNLLTQIGCTLNF

From Sequence to Structure

HIV Protease

HIV ProteaseWith Inhibitor

Page 3: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

Computational Approach

From Sequence to Structure

MNPNQKIITIGSVCMTIGMANLILQIGNIISIWISHSIQLGNQN QIETCNQSVITYENNTWVNQTYVNISNTNFAAGQSVVSVKLAGNSSLCPVSGWAIYSK DNSVRIGSKGDVFVIREPFISCSPLECRTFFLTQGALLNDKHSNGTIKDRSPYRTLMS CPIGEVPSPYNSRFESVAWSASACHDGINWLTIGISGPDNGAVAVLKYNGIITDTIKS WRNNILRTQESECACVNGSCFTVMTDGPSNGQASYKIFRIEKGKIVKSVEMNAPNYHY EECSCYPDSSEITCVCRDNWHGSNRPWVSFNQNLEYQIGYICSGIFGDNPRPNDKTGS CGPVSSNGANGVKGFSFKYGNGVWIGRTKSISSRNGFEMIWDPNGWTGTDNNFSIKQD IVGINEWSGYSGSFVQHPELTGLDCIRPCFWVELIRGRPKENTIWTSGSSISFCGVNS DTVGWSWPDGAELPFTIDK"

H1N1 NA

http://www.proteopedia.org/wiki/index.php/User:Michael_Strong/H1N1/NA

Page 4: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

Protein Building Blocks

Typical Protein Sequence MNPNQKIITIGSVCMTIGMANLILQIGNIISIWISHSIQLGNQN

Page 5: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

Protein Building Blocks

Page 6: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

Amino Acid Side Chain (R groups)

Page 7: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

Amino Acid Side Chain (R groups)

Page 8: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

Amino Acid Side Chain (R groups)

Page 9: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

DNA

Folded Protein

Most Proteins Spontaneously Fold

RNA

Some proteins chaperones for correct folding

Transcribed by RNA polymerase

Translated by Ribosome

Page 10: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

native state, Folded protein

spontaneous self-organisation (~1 second)

Most Proteins Spontaneously Fold

Folded protein

Unfolded protein

Denaturing conditions

Native conditions

Anfinsen’s Experiment

Page 11: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

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 …

Page 12: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

Most Proteins Spontaneously Fold

But Proteins lack easy rules for folding as compared to DNA

ProteinDNA

Page 13: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

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

Page 14: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

Common Secondary StructuresAlpha helix

Page 15: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

Common Secondary StructuresBeta Sheet

Page 16: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

Common Secondary StructuresLoop Regions

Loop

Page 17: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

Experimental Methods of Structure DeterminationX-ray crystallographyHigh resolution structure determination

Grow a protein Crystal

Page 18: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

Experimental Methods of Structure DeterminationX-ray crystallographyHigh resolution structure determination

Page 19: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

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)

Page 20: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

• 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

Page 21: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

• 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

Page 22: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

Database of Protein StructuresPDB – Protein Data Bank

Page 23: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

Database of Protein StructuresPDB – Protein Data Bank

64,036 protein structures as of 11/16/2010

Page 24: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

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

Page 25: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

GenBank Sequences

Page 26: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

• Atoms in pdb files are defined by their Cartesian coordinates:

Database of Protein StructuresPDB – Protein Data Bank Files

Page 27: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

Visualization of PDB filesPymol, Jmol, Chimera, etc

Page 28: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

Visualization of PDB filesPymol, Jmol, Chimera, etc

Page 29: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

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

Page 30: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

Secondary Structure Prediction1st and 2nd generation – looked at probability of amino acid to be in a helix, 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

3rd generation – 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%)

Page 31: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

Secondary Structure Prediction

But we really want to know how the protein folds in three dimensions

Page 32: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

But we really want to know how the protein folds in three dimensions

Page 33: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

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

Page 34: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

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

Page 35: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

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)

Page 36: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

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

Page 37: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

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)

Page 38: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

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)

Page 39: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

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)

Page 40: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

Quality AssessmentRamachandran Plot – Phi Psi anglesTo identify residues that may be in wrong conformationProcheck, What_check

Page 41: Protein Structure and Prediction Michael Strong, PhD National Jewish Health 11/16/10.

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