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The evolution of symmetry in protein
fold space
Presenter: Douglas Myers-Turnbull
undergraduate student, bioinformatics
Systematic detection of internal symmetry in proteins
using CE-Symm
Douglas Myers-Turnbulla, Spencer E. Blivenb, Peter W. Rosec, Zaid K.
Azidd, Philippe Youkharibachee, Philip E. Bournef,*, Andreas Prlicc,*
Journal of Molecular Biology, under second-pass review.
Symmetry is common
PDB IDs from left to right:
1VYM, 3HDP, 1G62, 1U6D, 3DDV
Why is symmetry so common?
 Enzymatic function
Why is symmetry so common?
 Enzymatic function
 Lowest energy state
Why is symmetry so common?
 Enzymatic function
 Lowest energy state
 Fewest kinetic barriers
Why is symmetry so common?
 Enzymatic function
 Lowest energy state
 Fewest kinetic barriers in folding
Easier to evolve complex structures from simple
building blocks
The evolution of symmetry in a β-trefoil
Building blocks of domains
Modular Evolution and the Origins of Symmetry:
“…symmetric protein structures can be constructed
from a set of basic ‘building blocks’ or subdomain
modules.”
What is a protodomain?
 A building block for domains
What is a protodomain?
 A building block for domains
 A subdomain that occurs across distant folds
What is a protodomain?
 A building block for domains
 A subdomain that occurs across distant folds
 Unlikely to have arisen by chance
Algorithms that detect symmetry
 sequence-based methods
Ex: DAVROS [Taylor et. al.]
 angle-based methods
Ex: Swelfe [Abraham et. al.]
 methods based on secondary structure
Ex: GANGSTA+ [Guerler et. al.]
 truly structural methods
Ex: SymD [Kim et. al.]
CE-Symm
 Align a structure against itself
CE-Symm
 Align a structure against itself
 Use Combinatorial Extension
A large benchmark set
 1,007 distinct SCOP superfamilies
A large benchmark set
 1,007 distinct SCOP superfamilies
 manually determined symmetry
CE-Symm is very accurate
Structural classification of proteins
 SCOP: class→fold→superfamily→family→domain
Structural classification of proteins
 SCOP: class→fold→superfamily→family→domain
 Different superfamilies of the same fold often have
substantial differences in structure
Normalization by superfamilies
 Normalize by number of domains per superfamily
Normalization by superfamilies
 Normalize by number of domains per superfamily
 A superfamily is symmetric if more than half of its
domains are symmetric.
A census of symmetry
SCOP class number of SFs % symmetric (SFs)
α 503 18.5%
β 354 24.6%
α/β 244 16.8%
α+β 549 14.3%
membrane 108 23.8%
overall 1824 18.0%
Complete results available at: http://source.rcsb.org
A census of symmetry
SCOP class number of SFs % symmetric (SFs)
α 503 18.5%
β 354 24.6%
α/β 244 16.8%
α+β 549 14.3%
membrane 108 23.8%
overall 1824 18.0%
Complete results available at: http://source.rcsb.org
A census of symmetry
SCOP class number of SFs % symmetric (SFs)
α 503 18.5%
β 354 24.6%
α/β 244 16.8%
α+β 549 14.3%
membrane 108 23.8%
overall 1824 18.0%
Complete results available at: http://source.rcsb.org
Symmetry and evolution
 How can we use this to learn about evolution?
Is this domain symmetric?
PDB ID: 3DDV. Zhang, R. et. al.
CE-Symm says it’s symmetric
Did we find a protodomain?
A protodomain?
Search for matching domains
A hit against another domain
It’s a β-propeller blade!
PDB ID: 1SHY. Stamos, J. et. al.
It’s a β-propeller blade!
PDB ID: 1SHY. Stamos, J. et. al.
Identifying protodomains systematically
1. Identify subdomains of symmetric structures with
CE-Symm
Identifying protodomains systematically
1. Identify subdomains of symmetric structures with
CE-Symm
2. Identify hits against other domains
Identifying protodomains systematically
1. Identify subdomains of symmetric structures with
CE-Symm
2. Identify hits against other domains
3. Derive a non-redundant set of protodomains
CE-Symm is on the web
http://source.rcsb.org
Acknowledgments
 Dr. Andreas Prlic, San Diego Supercomputer Center
 Spencer Bliven, Bioinformatics and Systems Biology
 Dr. Peter Rose, Skaggs School of Pharmacy
 Zaid Aziz, Chemistry and Biochemistry
 Dr. Philippe Youkharibache, Life Sciences R&D
 Dr. Phil Bourne, Skaggs School of Pharmacy
CE-Symm
1. Disable main diagonal (δ = 20)
CE-Symm
1. Disable main diagonal (δ = 20)
2. Duplicate matrix
CE-Symm
1. Disable main diagonal (δ = 20)
2. Duplicate matrix
3. Superimpose matrices
Current limitation: order-detection
 CE-Symm sometimes reports the wrong order
Two methods for order-detection
 Method 1: apply alignment repeatedly until the
composition becomes approximately the identity
 Method 2: identify the lowest difference ε(θ):
Most symmetric architectures are old
Types of symmetry in the benchmark
Some functions are related to symmetry
CE-Symm identifies symmetric folds
id fold CE-Symm (%) SymD (%) GANGSTA (%)
d.58 Ferredoxin-like 72 19 23
b.1 Immunoglobulin-like 61 8.9 8.4
b.42 Beta-Trefoil 97 100 56
a.24 Four-helical bundle 73 51 25
d.131 DNA clamp 100 91 64
b.69 7-bladed beta propeller 100 100 37
c.1 TIM beta/alpha barrel 87 83 3.7
b.11 Gamma-Crystallin-like 92 75 83
A stable synthetic β-trefoil
 Native function was lost
A synthetic adiponectin trimer
 Native function increased!
Symmetry is commonplace
 Quaternary symmetry
 Symmetry around active sites
PDB ID: 3HDP. Satyanarayana, L et. al.
Symmetry is commonplace
 Quaternary symmetry
 Symmetry around active sites
PDB ID: 2GZL. Crane, C.M. et. al.
Symmetry is commonplace
 Quaternary symmetry
 Symmetry around active sites
 Nested symmetry
PDB ID: 2GG6. Funke, T. et. al.
Symmetry is commonplace
 Quaternary symmetry
 Symmetry around active sites
 Nested symmetry
PDB ID: 2GG6. Funke, T. et. al.

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CE-Symm, protein symmetry, and the evolution of protein folds

  • 1. The evolution of symmetry in protein fold space Presenter: Douglas Myers-Turnbull undergraduate student, bioinformatics Systematic detection of internal symmetry in proteins using CE-Symm Douglas Myers-Turnbulla, Spencer E. Blivenb, Peter W. Rosec, Zaid K. Azidd, Philippe Youkharibachee, Philip E. Bournef,*, Andreas Prlicc,* Journal of Molecular Biology, under second-pass review.
  • 2. Symmetry is common PDB IDs from left to right: 1VYM, 3HDP, 1G62, 1U6D, 3DDV
  • 3. Why is symmetry so common?  Enzymatic function
  • 4. Why is symmetry so common?  Enzymatic function  Lowest energy state
  • 5. Why is symmetry so common?  Enzymatic function  Lowest energy state  Fewest kinetic barriers
  • 6. Why is symmetry so common?  Enzymatic function  Lowest energy state  Fewest kinetic barriers in folding Easier to evolve complex structures from simple building blocks
  • 7. The evolution of symmetry in a β-trefoil
  • 8. Building blocks of domains Modular Evolution and the Origins of Symmetry: “…symmetric protein structures can be constructed from a set of basic ‘building blocks’ or subdomain modules.”
  • 9. What is a protodomain?  A building block for domains
  • 10. What is a protodomain?  A building block for domains  A subdomain that occurs across distant folds
  • 11. What is a protodomain?  A building block for domains  A subdomain that occurs across distant folds  Unlikely to have arisen by chance
  • 12. Algorithms that detect symmetry  sequence-based methods Ex: DAVROS [Taylor et. al.]  angle-based methods Ex: Swelfe [Abraham et. al.]  methods based on secondary structure Ex: GANGSTA+ [Guerler et. al.]  truly structural methods Ex: SymD [Kim et. al.]
  • 13. CE-Symm  Align a structure against itself
  • 14. CE-Symm  Align a structure against itself  Use Combinatorial Extension
  • 15. A large benchmark set  1,007 distinct SCOP superfamilies
  • 16. A large benchmark set  1,007 distinct SCOP superfamilies  manually determined symmetry
  • 17. CE-Symm is very accurate
  • 18. Structural classification of proteins  SCOP: class→fold→superfamily→family→domain
  • 19. Structural classification of proteins  SCOP: class→fold→superfamily→family→domain  Different superfamilies of the same fold often have substantial differences in structure
  • 20. Normalization by superfamilies  Normalize by number of domains per superfamily
  • 21. Normalization by superfamilies  Normalize by number of domains per superfamily  A superfamily is symmetric if more than half of its domains are symmetric.
  • 22. A census of symmetry SCOP class number of SFs % symmetric (SFs) α 503 18.5% β 354 24.6% α/β 244 16.8% α+β 549 14.3% membrane 108 23.8% overall 1824 18.0% Complete results available at: http://source.rcsb.org
  • 23. A census of symmetry SCOP class number of SFs % symmetric (SFs) α 503 18.5% β 354 24.6% α/β 244 16.8% α+β 549 14.3% membrane 108 23.8% overall 1824 18.0% Complete results available at: http://source.rcsb.org
  • 24. A census of symmetry SCOP class number of SFs % symmetric (SFs) α 503 18.5% β 354 24.6% α/β 244 16.8% α+β 549 14.3% membrane 108 23.8% overall 1824 18.0% Complete results available at: http://source.rcsb.org
  • 25. Symmetry and evolution  How can we use this to learn about evolution?
  • 26. Is this domain symmetric? PDB ID: 3DDV. Zhang, R. et. al.
  • 27. CE-Symm says it’s symmetric
  • 28. Did we find a protodomain? A protodomain?
  • 30. A hit against another domain
  • 31. It’s a β-propeller blade! PDB ID: 1SHY. Stamos, J. et. al.
  • 32. It’s a β-propeller blade! PDB ID: 1SHY. Stamos, J. et. al.
  • 33. Identifying protodomains systematically 1. Identify subdomains of symmetric structures with CE-Symm
  • 34. Identifying protodomains systematically 1. Identify subdomains of symmetric structures with CE-Symm 2. Identify hits against other domains
  • 35. Identifying protodomains systematically 1. Identify subdomains of symmetric structures with CE-Symm 2. Identify hits against other domains 3. Derive a non-redundant set of protodomains
  • 36. CE-Symm is on the web http://source.rcsb.org
  • 37. Acknowledgments  Dr. Andreas Prlic, San Diego Supercomputer Center  Spencer Bliven, Bioinformatics and Systems Biology  Dr. Peter Rose, Skaggs School of Pharmacy  Zaid Aziz, Chemistry and Biochemistry  Dr. Philippe Youkharibache, Life Sciences R&D  Dr. Phil Bourne, Skaggs School of Pharmacy
  • 38.
  • 39. CE-Symm 1. Disable main diagonal (δ = 20)
  • 40. CE-Symm 1. Disable main diagonal (δ = 20) 2. Duplicate matrix
  • 41. CE-Symm 1. Disable main diagonal (δ = 20) 2. Duplicate matrix 3. Superimpose matrices
  • 42. Current limitation: order-detection  CE-Symm sometimes reports the wrong order
  • 43. Two methods for order-detection  Method 1: apply alignment repeatedly until the composition becomes approximately the identity  Method 2: identify the lowest difference ε(θ):
  • 45. Types of symmetry in the benchmark
  • 46. Some functions are related to symmetry
  • 47. CE-Symm identifies symmetric folds id fold CE-Symm (%) SymD (%) GANGSTA (%) d.58 Ferredoxin-like 72 19 23 b.1 Immunoglobulin-like 61 8.9 8.4 b.42 Beta-Trefoil 97 100 56 a.24 Four-helical bundle 73 51 25 d.131 DNA clamp 100 91 64 b.69 7-bladed beta propeller 100 100 37 c.1 TIM beta/alpha barrel 87 83 3.7 b.11 Gamma-Crystallin-like 92 75 83
  • 48. A stable synthetic β-trefoil  Native function was lost
  • 49. A synthetic adiponectin trimer  Native function increased!
  • 50. Symmetry is commonplace  Quaternary symmetry  Symmetry around active sites PDB ID: 3HDP. Satyanarayana, L et. al.
  • 51. Symmetry is commonplace  Quaternary symmetry  Symmetry around active sites PDB ID: 2GZL. Crane, C.M. et. al.
  • 52. Symmetry is commonplace  Quaternary symmetry  Symmetry around active sites  Nested symmetry PDB ID: 2GG6. Funke, T. et. al.
  • 53. Symmetry is commonplace  Quaternary symmetry  Symmetry around active sites  Nested symmetry PDB ID: 2GG6. Funke, T. et. al.