1. Flavio Seno Dipartimento di Fisica e Astronomia Universita’ di Padova
Means, Methods and Results in the Statistical Mechanics of Polymeric Systems.
Toronto June 2012
Exploring the Universe of Protein Structures beyond the Protein Data Bank
Flavio Seno
Dipartimento di Fisica e Astronomia
Universita’ di Padova

2. Protein structures
What are their distinctive properties? secondary structures stabilized by hydrogen bonds Folds:arrangements of secondary structures in the space There is a limited set of folds: same folds used to perform different functions There is not macroscopic evolution: multiple separate discoveries during the course of evolution

3. ~ 7000 structures (new sequences) determined every year
Platonic folds : intrinsic features of the order of nature (Denton and Marshall ,Nature 2002)

4. “SIMILARITY OF PROTEIN STRUCTURES IMPOSED BY SOME PHYSICAL REGULARITIES” (Finkelstein-Ptitsyn 2002)
Are protein folds determined only by physical and geometrical laws ( crystal structures) and not by the chemistry of the amino-acid sequence?
Is it possible to reproduce them in terms of general principles? Maybe through an homopolymer that captures the main common features of all the aminoacids?
Are the observed folds in a one to one correspondence with the whole possible fold universe?
If not, why? Is there a selection principle?

5. Minimal Coarse-Grained Model T.X. Hoang, L. Marsella, A. Trovato, J.R. Banavar, A. Maritan, F.S. PNAS, vol 103, 6883 (2006)
tion
Representa C - a
Excluded volume (self-avoiding tube)
Hydrogen bonding geometric constraint
Hydrophobic interaction
Local bending penalty

6. Ground State Phase Diagram
Homopolypeptide structures in the
‘marginally compact’ phase
(compact + h-bonds) are protein-like

7. METADYNAMICS
A Laio, M Parrinello, Escaping free-energy minima PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF, 99, (2002)
HOW TO FIND STABLE MINIMA WHICH ARE SEPARATED BY BARRIERS THAT CANNOT CLEARED IN THE AVAILABLE SIMULATION TIME
THE METHOD IS BASED ON AN ARTIFICIAL DYNAMICS (METADYNAMICS)
1) IDENTIFY COLLECTIVE VARIABLES S WHICH ARE ASSUMED TO PROVIDE A RELEVANT COARSE GRAINED DESCRIPTION OF THE SYSTEM
2) TO BIAS THE DYNAMICS ALONG THESE VARIABLES. S
3) RUN IN PARALLEL SEVERAL MOLECULAR DYNAMICS
EACH BIASED WITH A METADYNAMIC POTENTIAL
4) SWAPS OF THE CONFIGURATIONS

8. ATOMISTIC MODEL 60 AMINO ACIDS POLYVALINE (VAL60)
Why VAL? (is small but not too much)
MD simulations with AMBER force field
and package GROMACS
Bias-exchange METADYNAMICS with 6
replicas
Six collective variables linked to secondary
structure elements

9. 50 microseconds molecular dynamics simulation We generate an ensemble of all-atom conformations
SIGNIFICANT SECONDARY STRUCTURE CONTENT AND SMALL RADIUS OF GYRATION

10. We verify they are local minima also for ALA-60 Structural quality resembles that of real protein
QUALITY MEASURE G-FACTOR
RAMACHANDRAN PLOT
FRAGMENT DISTANCE < 0.6 A
H-BOND ENERGY COMPUTED WITH PROCHECK
0.7 A

11. FIRST RESULT
FINDING BY MOLECULAR DYNAMICS AT AN ALL-ATOM LEVEL A LIBRARY OF PROTEIN LIKE STRUCTURES

12. RELATION BETWEEN VAL60 AND REAL PROTEINS
The Class Architecture Topology and Homologous superfamily protein structure classification (CATH) is one of the main databases providing hierarchical classification of protein domain structures.
300 FOLDS
40 < L<75
SIMILARITY: TM-SCORE (Zhang Scolnick 2005)
ALLIGNMENTS OF SECONDARY STRUCTURES ALLOWING INSERTIONS AND DELETIONS (COVERAGE)
TM=0.45
MINIMIZATION OF THE RELATIVE DISTANCE BETWEEN ALIGNED RESIDUES (RMSD)

13. 1x9b 1ib8 1g29 40 < L < 75 1uxy COMPARISON VAL60 VS CATH
300 FOLDS
1uxy

14. SECOND RESULT
THE COMPUTATIONAL SETUP USED IN THIS WORK ALLOW US TO EXPLORE THE MAJORITY OF THE FOLDS IN NATURE (AT LEAST FOR THESE LENGTHS)

15. NOT ALL VAL60 ARE PRESENT IN CATH!!!!!!!
COMPARISON
POLYVAL VS CATH
NOT ALL VAL60 ARE PRESENT IN CATH!!!!!!!
TM =0.45
VAL
CATH

16. THIS MIGHT JUST DEPEND ON THE CHOSEN SIMILARITY THRESHOLD
DO STRUCUTRAL DESCRIPTORS DISCRIMINATE BETWEEN CATH AND VAL60?
CONTACT ORDER:
Average sequence separation between contacting residues
(related to folding rates Plaxco Simons Baker 1998)
Real protein strucures were selected under a bias towards low CO
- protein structures are selected to be topologically less entangled

17. THIS MIGHT JUST DEPEND ON THE CHOSEN SIMILARITY THRESHOLD
DO STRUCUTRAL DESCRIPTORS DISCRIMINATE BETWEEN CATH AND VAL60?
CONTACT ORDER:
Average sequence separation between contacting residues
(related to folding rates Plaxco Simons Baker 1998)
Real protein strucures were selected under a bias towards low CO
- protein structures are selected to be topologically less entangled

18. THIS MIGHT JUST DEPEND ON THE CHOSEN SIMILARITY THRESHOLD
DO STRUCUTRAL DESCRIPTORS DISCRIMINATE BETWEEN CATH AND VAL60?
CONTACT ORDER:
Average sequence separation between contacting residues
(related to folding rates Plaxco Simons Baker 1998)
Real protein strucures were selected under a bias towards low CO
- protein structures are selected to be topologically less entangled

19. THIRD RESULT
THERE IS NO ONE-TO-ONE CORRESPONDENCE BETWEEN PDB LIBRARY AND THE ENSEMBLE OF COMPACT STRUCUTRES WITH SIGNIFICANT SECONDARY STRUCUTURE CONTENT (VAL60)

20. SUMMARY WHY VAL60 SET IS REPRESENTATIVE OF REAL PROTEINS
(PROTEINS FOLDS SELECTED BY GEOMETRY AND SIMMETRY AND NOT BY CHEMISTRY OF THE SEQUENCE)
KNOWN FOLDS FORM ONLY A SMALL FRACTION OF THE FULL DATABASE
NATURAL FOLDS ARE CHARACTERIZED BY SMALL CONTACT ORDER
WHY
KINETIC ACCESSIBILITY
HIGHER CO HIGHER TENDENCY TO AGGREGATE?

21. APPLICATIONS REALISTIC DECOYS DESIGN NEW PROTEINS
CHECK PREDICTIONS IN SYNTHETIC BIOLOGY
MODELS FOR MISFOLDED STRUCTURES RELATED TO NEURODEGENERATIVE DISEASES

24. COLLABORATORS PILAR COSSIO (NIH WASHINGTON)
ALESSANDRO LAIO (SISSA TRIESTE)
DANIELE GRANATA (SISSA TRIESTE)
FABIO PIETRUCCI (CECAM – LAUSANNE)
AMOS MARITAN (PADOVA)
ANTONIO TROVATO (PADOVA)
Plos Computational Biology vol.6 e (2010)
Scientific Reports 2, Art. No. 351 (2012)

25. CORRELATION BETWEEN POTENTIAL ENERGY AND CONTACT ORDER FOR VAL60 AND ALA60 STRUCUTRES

26. Similarity between the VAL60 and CATH databases

27. CATH and VAL60 are explored with equal probability

30. Distribution of the radius of gyration for the VAL60, VAL60+WATER,ALA60 and CATH 55–65 sets of structures.

31. Cα RMSD distributions for the 30,000 VAL60 and the 1500 ALA60 minimized through SD.

32. Probability of finding a structure in the VAL60 trajectory for different CO classes.

33. Number of independent structures

34. Bias Exchange Metadynamics
S Piana, A Laio, A bias-exchange approach to protein folding JOURNAL OF PHYSICAL CHEMISTRY B, 111, 4553 (2007)
IT IS AN APPROACH DESIGNED FOR ACCELATING RARE EVENTS IN VERY COMPLEXES CASES IN WHICH THE VARIABLES THAT ARE RELVANT FOR THE PROCESS ARE MORE THAN 2 OR 3
List all the collective variables
Run in parallel several molecular dynamics each biased with a metadynamic potential
Swaps of the configuration

35. Are compact hydrogen-bonded polypetide structures in one-to-one correspondence with protein structures from the Protein Data Bank (PDB)?
Homopolypeptide ( side chain:C-beta atoms) with a very minimal potential consisting of H-bonding, excluded volume, and a uniform, pairwise attractive potential between side chains.
YES!?
PNAS 103, (2006)

36. Compact versus marginally compact phase
Homopolymer
energy
Pre-sculpted
free energy
landscape
marginally compact conformations

37. Compact versus marginally compact phase
Protein-like sequence
energy
Pre-sculpted
free energy
landscape
marginal compact conformations
native state