[PDF] - Biologically active oligomeric assemblies Torsten.Schwede@unibas.ch PDF Document

SLIDE 1

Torsten.Schwede@unibas.ch

Biologically active oligomeric assemblies

1. Oligomeric Assemblies / Quaternary Structures

! The coordinates present in a PDB entry (e.g. solved by X- ray crystallography or NMR) do not necessarily represent the correct oligomeric assembly of the macromolecule. ! Many proteins are active as (homo- or hetero-) complexes. ! How do we determine the correct oligomeric assembly from PDB entries based on

" NMR or " X-ray crystallography ?

SLIDE 2

Crystal = translated Unit Cell

More than 80% of protein structures are solved by means of X-ray diffraction on crystals. An X-ray diffraction experiment produces atomic coordinates of the crystal’s Asymmetric Unit (ASU). In general, neither ASU nor Unit Cell has any relation to Biological Units, or stable protein complexes which act as units in physiological processes. Is there a way to infer Biological Unit from the protein crystallography data?

Unit Cell = all space symmetry group mates of ASU PDB file

(slides courtesy of Eugene Krissinel & Kim Henrick, MSD-EBI)

X X-

ray crystallography

ray crystallography

1. Oligomeric Assemblies / Quaternary Structures

Crystal interfaces Crystal interfaces

Stability of protein complexes depends on properties of protein-protein interfaces, such as

free energy of formation !Gint
solvation energy gain !GS
interface area
hydrogen bonds and salt bridges

across the interface

hydrophobic specificity

(slides courtesy of Eugene Krissinel & Kim Henrick, MSD-EBI)

1. Oligomeric Assemblies / Quaternary Structures

SLIDE 3

Interface assessment Interface assessment

A crystal may be viewed as a packing of assemblies with biologically insignificant contacts between them. Protein assembly is a packing of monomeric units with biologically relevant interfaces between them.

(slides courtesy of Eugene Krissinel & Kim Henrick, MSD-EBI)

1. Oligomeric Assemblies / Quaternary Structures

At first glance At first glance … …

… the solution is simple as 1-2:

1. Evaluate all protein contacts (interfaces) in crystal
2. Leave only the strongest (“biologically relevant”) ones
and what you get will have chances to be a stable protein complex.

Small technical problem: How to discriminate between “real” (biologically relevant) and “superficial” (inter-assembly, or crystal packing) interfaces?

(slides courtesy of Eugene Krissinel & Kim Henrick, MSD-EBI)

1. Oligomeric Assemblies / Quaternary Structures

SLIDE 4

20 40 60 80 1000 2000 3000 4000 5000 6000 7000

PDB entry Buried ASA [Å2]

dimers monomers

Real and superficial protein interfaces Real and superficial protein interfaces

Most often used discrimination criteria

interface area.

A cut-off at 900 Å2 gives about 80% success rate of discrimination between monomers and dimers. Big proteins would be always sticky if this criteria is true …

(slides courtesy of Eugene Krissinel & Kim Henrick, MSD-EBI)

1.1. MSD-PISA

20 40 60 80

80
60
40
20

PDB entry Free Enerfgy Gain [kcal/M]

dimers monomers

Free energy gain of interface formation. A cut-off at -8 kcal/M gives about 82% success rate of discrimination between monomers and dimers. Can energy measure be uniform for all weights and shapes?

Real and superficial protein interfaces Real and superficial protein interfaces

(slides courtesy of Eugene Krissinel & Kim Henrick, MSD-EBI)

1.1. MSD-PISA

SLIDE 5

20 40 60 80 0.2 0.4 0.6 0.8

PDB entry P-value of Hydrophobic Patch

dimers monomers

Real and superficial protein interfaces Real and superficial protein interfaces

P-value of hydrophobic patches. A measure of probability for the interface to be more hydrophobic than found. A cut-off at 0.2 gives about 60% success rate

f discrimination

between monomers and dimers.

(slides courtesy of Eugene Krissinel & Kim Henrick, MSD-EBI)

1.1. MSD-PISA

" No ultimate discriminating parameter for the identification of biologically relevant protein interfaces may be proposed at present even for dimeric complexes

Jones, S. & Thornton, J.M. (1996) Principles of protein-protein interactions, Proc. Natl. Acad. Sci. USA, 93, 13-20.

" Formation of N>2 -meric complexes is most probably a corporate process involving a set of interfaces. Therefore significance of an interface should not be detached from the context of protein complex

Real and superficial protein interfaces Real and superficial protein interfaces

(slides courtesy of Eugene Krissinel & Kim Henrick, MSD-EBI)

1.1. MSD-PISA

SLIDE 6

Making assemblies from significant interfaces Making assemblies from significant interfaces

" PQS server @ MSD-EBI (Kim Henrick) Trends in Biochem. Sci. (1998) 23, 358

Method: recursive splitting of the largest complexes as allowed by crystal

symmetry. Termination criteria is derived from the individual statistical scores of

crystal contacts. The results are not curated.

" PITA software @ Thornton group EBI (Hannes Ponstingl) J. Appl. Cryst. (2003) 36, 1116

Method: progressive build-up by addition of monomeric chains that suit the selection criteria. The results are partly curated.

Despite failure to find an ultimate measure for interface biological relevance, two approaches were developed that use scoring of individual interfaces:

(slides courtesy of Eugene Krissinel & Kim Henrick, MSD-EBI)

1.1. MSD-PISA

" It is not properties of individual interfaces but rather chemical stability

f protein complex in general that really matters

" Protein chains will most likely associate into largest complexes that are still stable " A protein complex is stable if its free energy of dissociation is positive:

Chemical stability of protein complexes Chemical stability of protein complexes

int

# ! $ ! $ % ! S T G Gdiss

How to calculate !Gdiss?

(slides courtesy of Eugene Krissinel & Kim Henrick, MSD-EBI)

1.1. MSD-PISA

SLIDE 7

Protein affinity Protein affinity

& ' & '

sb sb hb hb n i i s n s

N E N E A G A A A G G $ $ ! $ ! % !

(

%1 2 1 int

, !

Solvation energy of protein complex Solvation energies of dissociated subunits Free energy

f H-bond

formation Number of H- bonds between dissociated subunits Free energy

f salt bridge

formation Number of salt bridges between dissociated subunits

& '

3 2 1

A A A

3 2 1

A A A ) )

Dissociation into stable subunits with minimum

diss

G !

Choice of dissociation subunits:

!Gint is function of protein interfaces

(slides courtesy of Eugene Krissinel & Kim Henrick, MSD-EBI)

1.1. MSD-PISA

Solvation Solvation free energy free energy

& '

(

$ ! % !

k r k k k s

a a A G *

Atomic solvation parameters Atom’s accessible surface area Atom’s accessible surface area in reference (unfolded) state

protein solvent

k

a

Eisenberg, D. & McLachlan, A.D. (1986) Nature 319, 199-203.

k

(slides courtesy of Eugene Krissinel & Kim Henrick, MSD-EBI)

1.1. MSD-PISA

SLIDE 8

Entropy of macromolecules in solutions Entropy of macromolecules in solutions

& '

a S I S m S S

surf S rot trans

) ) % * , ˆ

Translational entropy Rotational entropy Sidechain entropy Mass Solvent-accessible surface area Tensor of inertia

& ' & '

m R c m S

t trans

log 2 3 ) +

& '

2 3 2 1

log 2 , ˆ

S r S rot

I I I R c I S * * ) +

& '

Fa a Ssurf +

Murray C.W. and Verdonik M.L. (2002)

J. Comput.-Aided Mol. Design 16, 741-753.

Symmetry number

ct , cr and F are semi-empirical parameters

(slides courtesy of Eugene Krissinel & Kim Henrick, MSD-EBI)

1.1. MSD-PISA

Entropy of dissociation Entropy of dissociation

& ' & '

n n i i

A A A S A S S !

2 1 1

,

(

%

$ % !

Fitted parameter Fitted parameter Mass of i-th subunit

& '

) ,

.

/ 1 ) $ %

( 2

i i i i

m m R

C n log 1

2 3

& ' & ' & ' & '

buried A A A A I A A I R

Fa

n S k n k i i S k i k

) , ,

.

/ / 1

2 2 2

! !

1 2 1 2

log

2 * *

k-th principal moment of inertia of i-th subunit

!S is function of protein complex

(slides courtesy of Eugene Krissinel & Kim Henrick, MSD-EBI)

1.1. MSD-PISA

SLIDE 9

How to identify an assembly in crystal? How to identify an assembly in crystal?

We now know (or we think that we know) how to evaluate chemical stability of protein complexes. Given a 3D-arrangement of protein chains, we can now say whether there are chances that this arrangement is a stable assembly, or biological unit.

But how to get potential assemblies in first place?

(slides courtesy of Eugene Krissinel & Kim Henrick, MSD-EBI)

1.1. MSD-PISA

Enumerating assemblies in crystal Enumerating assemblies in crystal

" crystal is represented as a periodic graph with monomeric chains as vertices and interfaces as edges " each set of assemblies is identified by engaged interface types " all assemblies may be enumerated by a backtracking scheme engaging all possible combinations of different interface types

Example: crystal with 3 interface types

Assembly set Engaged interface types 1 000

only monomers

2 001

dimer N1

3 010

dimer N2

4 011 Assembly set Engaged interface types 5 100

dimer N3

6 101 7 110 8 111

all crystal

(slides courtesy of Eugene Krissinel & Kim Henrick, MSD-EBI)

1.1. MSD-PISA

SLIDE 10

Clever backtracking Clever backtracking

The number of different interface types may reach a hundred. The algorithm is not going to complete backtracking of 2100 combinations unless it is clever enough to " check geometry and engage induced interfaces as soon as they emerge " check geometry and terminate backtracking if assembly contains two identical chains in parallel

rientations

" see the future and terminate backtracking if there are no stable assemblies down the current branch

f the recursion tree

Engaged interfaces Induced interface Otherwise assembly will be infinite due to translation symmetry in crystal Based on the observation that entropy of dissociation of unstable assemblies only increases down the recursion tree … only then the algorithm completes in 0.1 secs to 1.5 hours depending on the structure …

(slides courtesy of Eugene Krissinel & Kim Henrick, MSD-EBI)

1.1. MSD-PISA

PISA workflow summary PISA workflow summary

1. Calculate properties of all structures
2. Calculate all crystal contacts and their properties
3. Find all assemblies which are possible in given crystal
4. Evaluate all assemblies for chemical stability and

leave only potentially stable ones

5. Range assemblies by chances to be a biological unit

(slides courtesy of Eugene Krissinel & Kim Henrick, MSD-EBI)

1.1. MSD-PISA

SLIDE 11

Benchmark results Benchmark results

Assembly classification on the benchmark set of 218 structures published in

Ponstingl, H., Kabir, T. and Thornton, J. (2003) Automatic inference of protein quaternary structures from crystals. J. Appl. Cryst. 36, 1116-1122.

1mer 2mer 3mer 4mer 6mer Other Sum Correct 1mer 50 4 1 55 91% 2mer 6 68+11 2+1 76+12 90% 3mer 1 22 1 24 92% 4mer 2 3 27+6 32+6 87% 6mer 1 10+2 11+2 92% Total: 198+20 90%

198+20 <=> 198 homomers and 20 heteromers

Fitted parameters:

hb

E

sb

E

1. Free energy of a H-bond :
2. Free energy of a salt bridge :
3. Constant entropy term :
4. Surface entropy factor :

F T 3 C T 3

= 0.51 kcal/mol = 0.21 kcal/mol = 11.7 kcal/mol = 0.57·10-3 kcal/(mol*Å2)

Classification error in !Gdiss : ± 5 kcal/mol

(slides courtesy of Eugene Krissinel & Kim Henrick, MSD-EBI)

1.1. MSD-PISA 1mer 2mer 3mer 4mer 5mer 6mer 8mer 10mer 12mer Other Sum Correct 1mer 131 11 4 2 2 150 87% 2mer 12+6 88+12 1 4 1 2 105+21 79% 3mer 1 2 6+2 1 7+5 67% 4mer 1+1 5+2 25+5 1+2 32+10 71% 5mer 1 2+1 2+2 75% 6mer 1 2+1 13+2 15+4 79% 8mer 1 0+2 1+2 67% 10mer 2 2 100% 12mer 2 5+1 7+1 75% Total: 321+45 81%

What is beyond the benchmark set? What is beyond the benchmark set?

Classification results obtained for 366 recent depositions into PDB in reference to manual classification in MSD-EBI :

321+45 <=> 321 homomers and 45 heteromers Classification error in !Gdiss : ± 5 kcal/mol

(slides courtesy of Eugene Krissinel & Kim Henrick, MSD-EBI)

1.1. MSD-PISA

SLIDE 12

Is it ever going to be 100%? Is it ever going to be 100%?

" theoretical models for protein affinity and entropy change upon protein complexation are primitive " coordinate (experimental) data is of a limited accuracy " there is no feasible way to take conformations in crystal into account " experimental data on multimeric states is very limited and not always reliable - calibration of parameters is difficult " protein assemblies may exist in some environments and dissociate in

ther - a definite answer is simply not there

Nobody should be that naive, because :

(slides courtesy of Eugene Krissinel & Kim Henrick, MSD-EBI)

1.1. MSD-PISA

Web Web-

server PISA

server PISA

http://www.ebi.ac.uk/msd-srv/prot_int/pistart.html

(slides courtesy of Eugene Krissinel & Kim Henrick, MSD-EBI)

1.1. MSD-PISA

SLIDE 13

(slides courtesy of Eugene Krissinel & Kim Henrick, MSD-EBI)

1.1. MSD-PISA

(slides courtesy of Eugene Krissinel & Kim Henrick, MSD-EBI)

1.1. MSD-PISA

SLIDE 14

(slides courtesy of Eugene Krissinel & Kim Henrick, MSD-EBI)

1.1. MSD-PISA

! And what about Protein / DNA complexes?

" Support for Protein-DNA/RNA and DNA/RNA-DNA/RNA interactions added to PISA 1.05 (17/02/2006 )

1.1. MSD-PISA

SLIDE 15

Conclusions Conclusions

" Stable protein complexes, which are likely to be biological units, may be calculated from protein crystallography data at 80-90% success rate " Biological relevance of a particular protein interface cannot be reliably inferred from the interface properties only. Instead, one should conclude about significance of an interface from the analysis of the relevant protein assemblies

(slides courtesy of Eugene Krissinel & Kim Henrick, MSD-EBI)

1.1. MSD-PISA