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

2. From Sequence to Structure
HIV Protease
With Inhibitor
HIV Protease
Experimental
Approach
PQITLWKRPLVTIRIGGQLKEALLDTGADDTVLEEMNLPGKWKPKMIGGIGGFIKVRQYDQIPIEICGHKAIGTVLVGPT PVNIIGRNLLTQIGCTLNF

3. From Sequence to Structure
H1N1 NA
MNPNQKIITIGSVCMTIGMANLILQIGNIISIWISHSIQLGNQN QIETCNQSVITYENNTWVNQTYVNISNTNFAAGQSVVSVKLAGNSSLCPVSGWAIYSK DNSVRIGSKGDVFVIREPFISCSPLECRTFFLTQGALLNDKHSNGTIKDRSPYRTLMS CPIGEVPSPYNSRFESVAWSASACHDGINWLTIGISGPDNGAVAVLKYNGIITDTIKS WRNNILRTQESECACVNGSCFTVMTDGPSNGQASYKIFRIEKGKIVKSVEMNAPNYHY EECSCYPDSSEITCVCRDNWHGSNRPWVSFNQNLEYQIGYICSGIFGDNPRPNDKTGS CGPVSSNGANGVKGFSFKYGNGVWIGRTKSISSRNGFEMIWDPNGWTGTDNNFSIKQD IVGINEWSGYSGSFVQHPELTGLDCIRPCFWVELIRGRPKENTIWTSGSSISFCGVNS DTVGWSWPDGAELPFTIDK"
Computational
Approach

4. Protein Building Blocks
Typical Protein Sequence MNPNQKIITIGSVCMTIGMANLILQIGNIISIWISHSIQLGNQN

5. Protein Building Blocks

6. Amino Acid Side Chain (R groups)

7. Amino Acid Side Chain (R groups)

8. Amino Acid Side Chain (R groups)

9. Most Proteins Spontaneously Fold
DNA
Transcribed by RNA polymerase
RNA
Translated by Ribosome
Folded Protein
Some proteins chaperones for correct folding

10. Most Proteins Spontaneously Fold
Folded protein
Anfinsen’s Experiment
native state, Folded protein
spontaneous self-organisation
(~1 second)
Denaturing conditions
Unfolded protein
Native conditions

11. 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 …

12. Most Proteins Spontaneously Fold
But Proteins lack easy rules for folding as compared to DNA
DNA
Protein

13. Many Factors Influence Protein Folding
Proteins Assume the Lowest Energy Structure
Factors that influence folding include:
Hydrophobic Interactions / collapse (particularly within the core)
Hydrogen bonds – lead to secondary structures
Disulfide Bonds (Cysteine residues)
Salt Bridges / Ionic Interactions (among charged residues)
Multimeric interactions with same type or other proteins
Protein

14. Common Secondary Structures
Alpha helix

15. Common Secondary Structures
Beta Sheet

16. Common Secondary Structures Loop Regions

17. Experimental Methods of Structure Determination X-ray crystallography
High resolution structure determination
Grow a protein Crystal

18. Experimental Methods of Structure Determination
X-ray crystallography
High resolution structure determination

19. Experimental Methods of Structure Determination X-ray crystallography
High 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)

20. Experimental Methods of Structure Determination
NMR – Nuclear Magnetic Resonance
High resolution structure determination
Smaller Proteins than X-ray
Distances between pairs of hydrogen atoms
Lots of information about dynamics
Requires soluble, non-aggregating material
Assignment sometimes difficult
NOE cross-peak if they are within 5.0 Å

21. Experimental Methods of Structure Determination
Cryo Electron Microscopy
Low to medium resolution structure determination
Low to medium resolution ~10-15Å
Limited information about dynamics
Can be used for very large molecules and complexes

22. Database of Protein Structures
PDB – Protein Data Bank

23. Database of Protein Structures PDB – Protein Data Bank
64,036 protein structures as of 11/16/2010

24. Database of Protein Structures PDB – Protein Data Bank
Even so, the number of solved structures greatly lags behind the rate of new genes being sequenced … Solution: Computational Structural Methods

25. GenBank Sequences

26. Database of Protein Structures PDB – Protein Data Bank Files
Atoms in pdb files are defined by their Cartesian coordinates:

27. Visualization of PDB files
Pymol, Jmol, Chimera, etc

28. Visualization of PDB files
Pymol, Jmol, Chimera, etc

29. From Sequence to Structure
H1N1 NA
MNPNQKIITIGSVCMTIGMANLILQIGNIISIWISHSIQLGNQN QIETCNQSVITYENNTWVNQTYVNISNTNFAAGQSVVSVKLAGNSSLCPVSGWAIYSK DNSVRIGSKGDVFVIREPFISCSPLECRTFFLTQGALLNDKHSNGTIKDRSPYRTLMS CPIGEVPSPYNSRFESVAWSASACHDGINWLTIGISGPDNGAVAVLKYNGIITDTIKS WRNNILRTQESECACVNGSCFTVMTDGPSNGQASYKIFRIEKGKIVKSVEMNAPNYHY EECSCYPDSSEITCVCRDNWHGSNRPWVSFNQNLEYQIGYICSGIFGDNPRPNDKTGS CGPVSSNGANGVKGFSFKYGNGVWIGRTKSISSRNGFEMIWDPNGWTGTDNNFSIKQD IVGINEWSGYSGSFVQHPELTGLDCIRPCFWVELIRGRPKENTIWTSGSSISFCGVNS DTVGWSWPDGAELPFTIDK"
Secondary Structure Prediction
Alpha Helix, Beta Strand, or Other
Tertiary Predictions:
Homology Modeling
Fold Recognition
De Novo Protein Structure Prediction
Computational
Approach

30. Secondary Structure Prediction
1st 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 % 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%)

31. Secondary Structure Prediction
But we really want to know how the protein folds in three dimensions

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

33. 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

34. 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

35. Comparative Modeling “Homology Modeling”
Steps include:
Template recognition and initial alignment
Alignment Correction (Multiple Sequence Alignment can Help)
Backbone Generation (transfer coordinates from template)
Loop Modeling (loops hard to predict with insertions)
Side Chain Modeling (usually similar tortion angles at high sequenc ID)
Model Optimization (minor energy minimization steps or restrain some atom positions)
Model Validation (Higher ID more accurate usually, Calculate energy, or normality index (bond length, tortion angles))
Iteration (to refine)

36. Protein Threading, Fold Recognition
Often, seemingly unrelated proteins adopt similar folds.
-Divergent evolution, convergent evolution. For sequences with low or no sequence homology
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)

37. Fold recognition NK-lysin (1nkl) Bacteriocin T102/as48 (1e68)
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 Å
5% ID
NK-lysin (1nkl)
Bacteriocin T102/as48 (1e68)

38. 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 sequence
In 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)

39. Rosetta structure prediction
2 phases
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. Refinement
B. Then structures clustered based on RMSD
C. Center of the Largest Clusters chosen as representative folds (likely to be correct fold)

40. Ramachandran Plot – Phi Psi angles
Quality Assessment
Ramachandran Plot – Phi Psi angles
To identify residues that may be in wrong conformation
Procheck, What_check

41. DALI Structural Alignments
Align Protein Structures, Structure Superposition
Generates a comparison matrix (transform protein into a 2D array of distances between C-alpha atoms. Z score reflects reliability, lowest RMSD identified