1. #19 - Protein Structure Basics & Classification
BCB 444/544
10/5/07
Lecture 19
A bit of: Protein Structure - Basics
Protein Structure Visualization, Classification & Comparison
#19_Oct05
BCB 444/544 F07 ISU Dobbs #19- Protein Structure Basics & Classification
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2. Required Reading (before lecture)
#19 - Protein Structure Basics & Classification
Required Reading (before lecture)
10/5/07
√Mon Oct 1 - Lecture 17
Protein Motifs & Domain Prediction
Chp 7 - pp 85-96
√ Wed Oct 3 - Lecture 18
Protein Structure: Basics (Note chg in Lecture Schedule online )
Chp 12 - pp
√Thurs Oct 4 & Fri Oct 5 - Lab 6 & Lecture 19
Protein Structure: Basics, Databases, Visualization, Classification & Comparison
Chp 13 - pp
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3. BCB 544 - Extra Required Reading
#19 - Protein Structure Basics & Classification
10/5/07
BCB Extra Required Reading
Assigned Mon Sept 24
BCB 544 Extra Required Reading Assignment:
for 544 Extra HW#1 Task 2
Pollard KS, …., Haussler D. (2006) An RNA gene expressed during cortical development evolved rapidly in humans. Nature 443:
doi: /nature05113
PDF available on class website - under Required Reading Link
BCB 444/544 F07 ISU Dobbs #19- Protein Structure Basics & Classification
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4. BCB 544 Projects (Optional for BCB 444)
#19 - Protein Structure Basics & Classification
10/5/07
BCB 544 Projects (Optional for BCB 444)
For a better idea about what's involved in the Team Projects, please look over last year's expectations for projects:
Criteria for evaluation of projects (oral presentations) are summarized here:
Please note: wrong URL (instead of that shown above) was included
in originally posted 544ExtraHW#1; corrected version is posted now
BCB 444/544 F07 ISU Dobbs #19- Protein Structure Basics & Classification
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5. Assignments & Announcements - #1
#19 - Protein Structure Basics & Classification
10/5/07
Assignments & Announcements - #1
Students registered for BCB 444: Two Grading Options
1) Take Final Exam per original Grading Policies
2) Instead of taking Final Exam - you may participate in a Team Research Project
If you choose #2, please do 3 things:
Contact Drena (in person)
Send to Michael Terribilini
Complete 544 Extra HW#1 - Task 1.1 by noon on Mon Oct 1
BCB 444/544 F07 ISU Dobbs #19- Protein Structure Basics & Classification
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6. Assignments & Announcements - #2
#19 - Protein Structure Basics & Classification
10/5/07
Assignments & Announcements - #2
BCB 444s (Standard):
200 pts Midterm Exams = 100 points each
200 Homework & Laboratory assignments = 200 points
100 Final Exam
500 pts Total for BCB 444
BCB 444p (Project):
190 Team Research Project
590 pts Total for BCB 444p
BCB 544: 200 pts Midterm Exams = 100 points each
200 Homework & Laboratory assignments
200 Discussion Questions & Team Research Projects
700 pts Total for BCB 544
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7. Assignments & Announcements #3
#19 - Protein Structure Basics & Classification
10/5/07
Assignments & Announcements #3
ALL: HomeWork #3
Due: Mon Oct 8 by 5 PM
HW544: HW544Extra #1
√Due: Task Mon Oct 1 by noon
Due: Task 1.2 & Task 2 - Fri Oct 12 by 5 PM (not Monday)
444 "Project-instead-of-Final" students should also submit:
HW544Extra #1
Due: Task Mon Oct 8 by noon
Due: Task Fri Oct 12 by 5 PM (not Monday)
Task 2 NOT required!
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8. QUESTIONS re: HW#3? Due Mon
#19 - Protein Structure Basics & Classification
10/5/07
QUESTIONS re: HW#3? Due Mon
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9. HMM example from Eddy HMM paper: Toy HMM for Splice Site Prediction
#19 - Protein Structure Basics & Classification
10/5/07
This is a new slide
HMM example from Eddy HMM paper: Toy HMM for Splice Site Prediction
BCB 444/544 F07 ISU Dobbs #19- Protein Structure Basics & Classification
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10. An HMM for Occasionally Dishonest Casino
#19 - Protein Structure Basics & Classification
An HMM for Occasionally Dishonest Casino
10/5/07
Transition probabilities
Prob(Fair  Loaded) = 0.01
Prob(Loaded  Fair) = 0.2
But, where do you start? "Begin" state not shown
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11. Occasionally Dishonest Casino - HW#3
#19 - Protein Structure Basics & Classification
Occasionally Dishonest Casino - HW#3
10/5/07
"Begin" state? 50:50 chance of starting with F vs L die
BCB 444/544 F07 ISU Dobbs #19- Protein Structure Basics & Classification
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12. Calculating Different Paths to an Observed Sequence
#19 - Protein Structure Basics & Classification
10/5/07
This slide has been changed
Calculating Different Paths to an Observed Sequence
Calculations such as those shown below are used to fill a matrix
with probability values for every state at every position
transition probability
emission probability
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13. #19 - Protein Structure Basics & Classification
10/5/07
Calculate optimal path? Construct a matrix of probability values for every state at every residue
How: one way = Viterbi Algorithm
Initialization (i = 0)
Recursion (i = 1, , L): For each state k
Termination:
To find *, use trace-back, as in dynamic programming
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14. Viterbi for Calculating Most Probable Path*
#19 - Protein Structure Basics & Classification
Viterbi for Calculating Most Probable Path*
10/5/07 1  x 6 2 
(1/6)(1/2)
= 1/12
(1/2)(1/2)
= 1/4
(1/6)max{(1/12)0.99,
(1/4)0.2} =
(1/10)max{(1/12)0.01,
(1/4)0.8}
= 0.02 B F L
(1/6)max{ 0.99,
0.020.2} =
(1/2)max{ 0.01,
0.020.8}
= 0.08
* Path within HMM that matches query sequence with highest probability
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15. #19 - Protein Structure Basics & Classification
Total Probability
10/5/07
Several different paths can result in observation x
Probability that our model will emit x is:
BCB 444/544 F07 ISU Dobbs #19- Protein Structure Basics & Classification
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16. Calculating the Total Probability:
#19 - Protein Structure Basics & Classification
10/5/07
This slide has bee changed
Calculating the Total Probability:
Note: This not the same as matrix on previous slide!
Here, last column contains sums for each row 1  x 6 2 
(1/6)(1/2)
= 1/12
(1/2)(1/2)
= 1/4
(1/6)sum{(1/12)0.99,
(1/4)0.2} =
(1/10)sum{(1/12)0.01,
(1/4)0.8} = B F L
(1/6)sum{ 0.99,
0.2} =
(1/2)sum{ 0.01,
0.8} =
Total probability =
= = 0.012
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17. A few more Details re: Profiles & HMMs
#19 - Protein Structure Basics & Classification
10/5/07
A few more Details re: Profiles & HMMs
Smoothing or "Regularization" - method used to avoid "over-fitting"
Common problem in machine learning (data-driven) approaches
Limited training sample size causes over-representation of observed characters while "ignoring" unobserved characters
Result? Miss members of family not yet sampled
(too many false negative hits)
Pseudocounts - adding artificial values for 'extra' amino acid(s) not observed in the training set
Treated as a 'real' values in calculating probabilities
Improve predictive power of profiles & HMMs
Dirichlet mixture - commonly used mathematical model to simulate the aa distribution in a sequence alignment
To "correct" problems in an observed alignment based on limited number of sequences
BCB 444/544 F07 ISU Dobbs #19- Protein Structure Basics & Classification
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18. Chp 7 - Protein Motifs & Domain Prediction
#19 - Protein Structure Basics & Classification
10/5/07
Chp 7 - Protein Motifs & Domain Prediction
SECTION II SEQUENCE ALIGNMENT
Xiong: Chp 7
Protein Motifs and Domain Prediction
√Identification of Motifs & Domains in MSAs
√Motif & Domain Databases Using Regular Expressions
√Motif & Domain Databases Using Statistical Models
Protein Family Databases
Motif Discovery in Unaligned Sequences
√Sequence Logos
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19. #19 - Protein Structure Basics & Classification
10/5/07
Motifs & Domains
Motif - short conserved sequence pattern
Associated with distinct function in protein or DNA
Avg = 10 residues (usually 6-20 residues)
e.g., zinc finger motif - in protein
e.g., TATA box - in DNA
Domain - "longer" conserved sequence pattern, defined as a independent functional and/or structural unit
Avg = 100 residues (range from in proteins)
e.g., kinase domain or transmembrane domain - in protein
Domains may (or may not) include motifs
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20. #19 - Protein Structure Basics & Classification
10/5/07
2 Approaches for Representing "Consensus" Information in Motifs & Domains
Regular expression - symbolic representation of information from MSA
e.g., protein phosphorylation site motif: [S,T]- X- [R,K]
Symbols represent specific or unspecified residues, spaces, etc.
2 mechanisms for matching:
Exact
"Fuzzy" (inexact, approximate) - flexible, more permissive to detect "near matches"
Statistical model - includes probability information derived from MSA
e.g., PSSM, Profile, or HMM
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21. Motif & Domain Databases
#19 - Protein Structure Basics & Classification
10/5/07
Motif & Domain Databases
Based on regular expressions:
Prosite (Interpro includes Prosite, PRINTS, etc)
Emofit
Limitation: these don't take probability info into account
Based on statistical models:
PRINTS
BLOCKS
ProDom
Pfam
SMART
CDART
Reverse PsiBLAST
READ your textbook & try some of these at home; there are distinct advantages/disadvantages associated with each
TAKE HOME LESSON:
Always try several methods!
(not just one!)
BCB 444/544 F07 ISU Dobbs #19- Protein Structure Basics & Classification
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22. Protein Family Databases
#19 - Protein Structure Basics & Classification
10/5/07
Protein Family Databases
In addition to databases of "related" protein sequences, based on shared motifs or domains (Pfam, BLOCKS, CDART), some databases "cluster" sequences into families based on near full-length sequence comparisons
COGs - Clusters of Orthologous Groups (at NCBI)
Mostly Prokaryotic sequences
KOG = newer Eukaryotic version
COGnitor - softwared to search database
ProtoNet - also clusters of homologous protein sequences
Advantages: tree-like hierarchical structure
Provide GO (gene ontology) annotations
Provides InterPro keywords
BCB 444/544 F07 ISU Dobbs #19- Protein Structure Basics & Classification
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23. Motif Discovery in Unaligned Sequences
#19 - Protein Structure Basics & Classification
10/5/07
Motif Discovery in Unaligned Sequences
Expectation Maximization - generate"random" alignment of all sequences, derive PSSM, iteratively match individual sequences to PSSM to edit & improve it
Problems? Can hit a local optimum (premature convergence)
Sensitive to initial alignment
MEME - Multiple EM for Motif Elicitation - modified EM, avoids local optimum issues; two step procedure
Gibbs Sampling - generate "trial" PSSM from random alignment first, as in EM, but leave one sequence out of initial alignment, then iteratively match PSSM to left-out sequences
Gibbs Sampler - web-based motif search via Gibbs sampling
Not mentioned in textbook:
Stochastic context-free grammers
Other "state of the art"pproaches in recent literature, but not available in web-based servers (yet)
BCB 444/544 F07 ISU Dobbs #19- Protein Structure Basics & Classification
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24. Chp 12 - Protein Structure Basics
#19 - Protein Structure Basics & Classification
10/5/07
Chp 12 - Protein Structure Basics
SECTION V STRUCTURAL BIOINFORMATICS
Xiong: Chp 12
Protein Structure Basics
LAB 6
Introduction to Protein DataBank - PDB
PyMol
Cn3D?
BCB 444/544 F07 ISU Dobbs #19- Protein Structure Basics & Classification
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25. Chp 12 - Protein Structure Basics
#19 - Protein Structure Basics & Classification
10/5/07
Chp 12 - Protein Structure Basics
SECTION V STRUCTURAL BIOINFORMATICS
Xiong: Chp 12
Protein Structure Basics
Amino Acids
Peptide Bond Formation
Dihedral Angles
Hierarchy
Secondary Structures
Tertiary Structures
Determination of Protein 3-Dimensional Structure
Protein Structure DataBank (PDB)
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26. Protein Structure & Function
#19 - Protein Structure Basics & Classification
Protein Structure & Function
10/5/07
Protein structure - primarily determined by sequence
Protein function - primarily determined by structure
Globular proteins: compact hydrophobic core & hydrophilic surface
Membrane proteins: special hydrophobic surfaces
Folded proteins are only marginally stable
Some proteins do not assume a stable "fold" until they bind to something = Intrinsically disordered
Predicting protein structure and function can be very hard -- & fun!
BCB 444/544 F07 ISU Dobbs #19- Protein Structure Basics & Classification
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27. 4 Basic Levels of Protein Structure
#19 - Protein Structure Basics & Classification
4 Basic Levels of Protein Structure
10/5/07
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28. Primary & Secondary Structure
#19 - Protein Structure Basics & Classification
10/5/07
Primary & Secondary Structure
Primary
Linear sequence of amino acids
Description of covalent bonds linking aa’s
Secondary
Local spatial arrangement of amino acids
Description of short-range non-covalent interactions
Periodic structural patterns: -helix, b-sheet
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29. Tertiary & Quaternary Structure
#19 - Protein Structure Basics & Classification
Tertiary & Quaternary Structure
10/5/07
Tertiary
Overall 3-D "fold" of a single polypeptide chain
Spatial arrangement of 2’ structural elements; packing of these into compact "domains"
Description of long-range non-covalent interactions (plus disulfide bonds)
Quaternary
In proteins with > 1 polypeptide chain, spatial arrangement of subunits
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30. "Additional" Structural Levels
#19 - Protein Structure Basics & Classification
"Additional" Structural Levels
10/5/07
Super-secondary elements
Motifs
Domains
Foldons
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31. #19 - Protein Structure Basics & Classification
Amino Acids
10/5/07
Each of 20 different amino acids has different "R-Group" or side chain attached to Ca
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32. Peptide Bond is Rigid and Planar
#19 - Protein Structure Basics & Classification
Peptide Bond is Rigid and Planar
10/5/07
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33. Hydrophobic Amino Acids
#19 - Protein Structure Basics & Classification
Hydrophobic Amino Acids
10/5/07
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34. #19 - Protein Structure Basics & Classification
Charged Amino Acids
10/5/07
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35. #19 - Protein Structure Basics & Classification
Polar Amino Acids
10/5/07
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36. Certain Side-chain Configurations are Energetically Favored (Rotamers)
#19 - Protein Structure Basics & Classification
10/5/07
Ramachandran plot:
"Allowable" psi & phi angles
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37. Glycine is Smallest Amino Acid R group = H atom
#19 - Protein Structure Basics & Classification
Glycine is Smallest Amino Acid R group = H atom
10/5/07
Glycine residues increase backbone flexibility because they have no R group
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38. #19 - Protein Structure Basics & Classification
Proline is Cyclic
10/5/07
Proline residues reduce flexibility of polypeptide chain
Proline cis-trans isomerization is often a rate-limiting step in protein folding
Recent work suggests it also may also regulate ligand binding in native proteins Andreotti (BBMB)
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39. Cysteines can Form Disulfide (S-S) Bonds
#19 - Protein Structure Basics & Classification
Cysteines can Form Disulfide (S-S) Bonds
10/5/07
Disulfide bonds (covalent) stabilize
3-D structures
In eukaryotes, disulfide bonds are often found in secreted proteins or extracellular domains
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40. Globular Proteins Have a Compact Hydrophobic Core
#19 - Protein Structure Basics & Classification
Globular Proteins Have a Compact Hydrophobic Core
10/5/07
Packing of hydrophobic side chains into interior is main driving force for folding
Problem? Polypeptide backbone is highly polar (hydrophilic) due to polar -NH and C=O in each peptide unit (which are charged at neutral pH=7, found in biological systems); these polar groups must be neutralized
Solution? Form regular secondary structures,
e.g., -helix, b-sheet, stabilized by H-bonds
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41. Exterior Surface of Globular Proteins is Generally Hydrophilic
#19 - Protein Structure Basics & Classification
10/5/07
Exterior Surface of Globular Proteins is Generally Hydrophilic
Hydrophobic core formed by packed secondary structural elements provides compact, stable core
"Functional groups" of protein are attached to this framework; exterior has more flexible regions (loops) and polar/charged residues
Hydrophobic "patches" on protein surface are often involved in protein-protein interactions
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42. Protein Secondary Structures
#19 - Protein Structure Basics & Classification
Protein Secondary Structures
10/5/07
Helices
Sheets
Loops
Coils
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43. Helix: Stabilized by H-bonds between every ~ 4th residue in Backbone
#19 - Protein Structure Basics & Classification
Helix: Stabilized by H-bonds between every ~ 4th residue in Backbone
10/5/07
C = black
O = red
N = blue
H = white
Look! - Charges on backbone are "neutralized"
by hydrogen bonds (H-bonds) - red fuzzy vertical bonds
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44. Certain Amino Acids are "Preferred" & Others are Rare in Helices
#19 - Protein Structure Basics & Classification
10/5/07
Certain Amino Acids are "Preferred" & Others are Rare in Helices
Ala, Glu, Leu, Met = good helix formers
Pro, Gly Tyr, Ser = very poor
Amino acid composition & distribution varies, depending on on location of helix in 3-D structure
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45. -Sheets - also Stabilized by H-bonds Between Backbone Atoms
#19 - Protein Structure Basics & Classification
10/5/07
-Sheets - also Stabilized by H-bonds Between Backbone Atoms
Anti-parallel
Parallel
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46. #19 - Protein Structure Basics & Classification
10/5/07
Loops
Connect helices and sheets
Vary in length and 3-D configurations
Are located on surface of structure
Are more "tolerant" of mutations
Are more flexible and can adopt multiple conformations
Tend to have charged and polar amino acids
Are frequently components of active sites
Some fall into distinct structural families (e.g., hairpin loops, reverse turns)
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47. #19 - Protein Structure Basics & Classification
Coils
10/5/07
Regions of 2' structure that are not helices, sheets, or recognizable turns
Intrinsically disordered regions appear to play important functional roles
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48. Chp 13 - Protein Structure Basics
#19 - Protein Structure Basics & Classification
10/5/07
Chp 13 - Protein Structure Basics
SECTION V STRUCTURAL BIOINFORMATICS
Xiong: Chp 13
Protein Structure Visualization, Comparison & Classfication
Protein Structural Visualization
Protein Structure Comparison
Protein Structure Classification
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