1. Structural Biology: What does 3D tell us? Stephen J Everse University of Vermont

2. Training –PhD & Postdoc with Russell F. Doolittle, UCSD structure of fragment D of fibrinogen structures of double-D of fibrin –Joined the faculty at UVM in 1998 Structural biologist (crystallographer) Current projects –factor Va –thioredoxin reductase –transferrin The life of a bio-chemist!!

3. Everse Group Maria Cristina Bravo Brian Eckenroth, Ph.D.

4. Fundamental Questions l How do protein cofactors modulate enzymes? l What determines and mediates protein-protein and protein-membrane interactions? l How is a protein’s function defined by structure? l How does structure prescribe the binding affinity of a metal?

5. Coagulation Cascade Factor XII Prekallikrein HMW Kininogen “Surface” Factor XIa HMW Kininogen Membrane Ca 2+ Zn 2+ Factor IXa Factor VIIIa Membrane Ca 2+ Intrinsic Pathway Extrinsic Pathway Factor VIIa Tissue Factor Membrane Ca 2+ Extrinsic Tenase Factor Xa Factor Va Membrane Ca 2+ Prothrombinase IX IXa XI XIa X Xa Intrinsic Tenase Contact Activation Pathway II IIa “Thrombin”

6. Ca 2+ 20 FXa “Prothrombinase” FVa HC FVa LC Ca 2+ FVa HC FXa FVa LC Ca 2+ 300,000 Prothrombin  -Thrombin Prothrombinase Components Relative Rate of Prothrombin Activation FXa 1 Ca 2+ 2 W. Gould @2000

7. Cu 2+ Ca 2+ A1 C1 C2 A3 Bovine Factor Va i Funded by: NIH American Society of Hematology

8. Prothrombinase (Va + Xa) A3 A1 A2 C2 C1 Hypothetical model

9. Thioredoxin reductase DmTR Eckenroth et al. Biochemistry 2007

10. Outline Determining a 3D structure –X-ray crystallography Structural elements Modeling a 3D structure

11. PrimarySecondaryTertiaryQuaternary Amino acid sequence. Alpha helices & Beta sheets, Loops. Arrangement of secondary elements in 3D space. Packing of several polypeptide chains. Given an amino acid sequence, we are interested in its secondary structures, and how they are arranged in higher structures. Protein Structures

12. Secondary Structure  Helix First predicted by Linus Pauling. Modeled on basis x-ray data which provided accurate geometries, bond lengths, and angles. Modeled before Kendrew’s structure; 3.6 residues/ turn, 5.4Å/ turn; The main chain forms a central cylinder with R-groups projecting out; Variable lengths: from 4 to 40+ residues with the average helix length is 10 residues (3 turns).

13. Secondary Structure The  Sheet Unlike  helix,  sheet composed of secondary structure elements distant in structure; The  strands are located next to each other Hydrogen bonds can form between C=O groups of one strand and NH groups of an adjacent strand. Two different orientations –all strands run same direction: “parallel” –strands in alternating orientation: the “antiparallel”.

14.  -Turns Type I: Also referred to as a  turn: H- bond between Acyl O of AA1 and NH of AA4; Type II, glycine must occupy the AA3 position due to steric effects; Type III is equivalent to 3 10 helix; Types I & III constitute some 70% of all  turns; Proline is typically found in the second position, and most  turns have Asp, Asn, or Gly at the third position.

15. Other Secondary Structural Elements Random coil Loop  -turn –defined for 3 residues i, i+1, i+2 if a hydrogen bond exists between residues i and i+2 and the phi and psi angles of residue i+1 fall within 40 degrees of one of the following 2 classes turn type phi(i+1) psi(i+1) classic 75.0 -64.0 inverse -79.0 69.0 Disordered structure

16. Viewing Structures C  or CA Ball-and-stickCPK

17. Ribbon and Topology Diagrams Representations of Secondary Structures  -helix  -strand N C

18. Tools for Viewing Structures Jmol –http://jmol.sourceforge.net PyMOL –http://pymol.sourceforge.net Swiss PDB viewer –http://www.expasy.ch/spdbv Mage/KiNG –http://kinemage.biochem.duke.edu/software/mage.php –http://kinemage.biochem.duke.edu/software/king.php Rasmol –http://www.umass.edu/microbio/rasmol/

19. RCSB http://www.rcsb.org/

20. GRASP Graphical Representation and Analysis of Structural Properties Red = negative surface charge Blue = positive surface charge

21. Consurf The ConSurf server enables the identification of functionally important regions on the surface of a protein or domain, of known three-dimensional (3D) structure, based on the phylogenetic relations between its close sequence homologues; A multiple sequence alignment (MSA) is used to build a phylogenetic tree consistent with the MSA and calculates conservation scores with either an empirical Bayesian or the Maximum Likelihood method. http://consurf.tau.ac.il/

22. Movies http://pymol.org

23. Proteopedia

24. Higher Level Structures: Motifs & Domains Motif is a simple combination of a few secondary structures, that appear in several different proteins in nature. A collection of motifs forms a domain. Domain is a more complex combination of secondary structures. It has a very specific function (contains an active site). A protein may contain more than one domain.

25. Super-secondary Structures or Motifs

26. Domains "Within a single subunit [polypeptide chain], contiguous portions of the polypeptide chain frequently fold into compact, local semi- independent units called domains." - Richardson, 1981 Domains are: can be built from structural motifs; independently folding elements; functional units; separable by proteases. Typically, globular proteins are organized into one or more domains. EGF domain from p-selectin

27. Evolutionarily Conserved Domains Often certain structural themes (domains) repeat themselves, but not always in proteins that have similar biological functions. This phenomenon of repeating structures is consistent with the notion that the proteins are genetically related, and that they arose from one another or from a common ancestor. In looking at the amino acid sequences, sometimes there are obvious homologies, and you could predict that the 3-D structures would be similar. But sometimes virtually identical 3-D structures have no sequence similarities at all!

28. Rates of Change Not all proteins change at the same rate; Why? Functional pressures –Surface residues are observed to change most frequently; –Interior less frequently;

29. Sequence  Structure  Function Many sequences can give same structure  Side chain pattern more important than sequence When homology is high (>50%), likely to have same structure and function (Structural Genomics)  Cores conserved  Surfaces and loops more variable *3-D shape more conserved than sequence* *There are a limited number of structural frameworks* W. Chazin © 2003

30. Degree of Evolutionary Conservation Less conserved Information poor More conserved Information rich DNA seqProtein seqStructureFunction ACAGTTACAC CGGCTATGTA CTATACTTTG HDSFKLPVMS KFDWEMFKPC GKFLDSGKLG S. Lovell © 2002

31. How is a 3D structure determined ? 1. Experimental methods (Best approach): X-rays crystallography - stable fold, good quality crystals. NMR - stable fold, not suitable for large molecule. 2. In-silico methods (partial solutions - based on similarity): Sequence or profile alignment - uses similar sequences, limited use of 3D information. Threading - needs 3D structure, combinatorial complexity. Ab-initio structure prediction - not always successful.

32. Experimental Determination of Atomic Resolution Structures X-ray X-rays Diffraction Pattern  Direct detection of atom positions  Crystals NMR RF Resonance H0H0  Indirect detection of H-H distances  In solution

33. Position Signal Resolving Power: The ability to see two points that are separated by a given distance as distinct Resolution of two points separated by a distance d requires radiation with a wavelength on the order of d or shorter: d wavelength Mark Rould © 2007 Resolving Power

34. Lenses require a difference in refractive index between the air and lens material in order to 'bend' and redirect light (or any other form of electromagnetic radiation.) The refractive index for x-rays is almost exactly 1.00 for all materials. ∆ There are no lenses for xrays. n air n glass n air Mark Rould © 2007 X-ray Microscopes?

35. Scattering = Fourier Transform of specimen Lens applies a second Fourier Transform to the scattered rays to give the image Mark Rould © 2007 Light Scattering and Lenses are Described by Fourier Transforms Since X-rays cannot be focused by lenses and refractive index of X-rays in all materials is very close to 1.0 how do we get an atomic image?

36. X-ray Diffraction with “The Fourier Duck” Images by Kevin Cowtan http://www.yorvic.york.ac.uk/~cowtan The molecule The diffraction pattern

37. Animal Magic Images by Kevin Cowtan http://www.yorvic.york.ac.uk/~cowtan The CAT (molecule) The diffraction pattern

38. X-Ray Detector Computer Mark Rould © 2007 Solution: Measure Scattered Rays, Use Fourier Transform to Mimic Lens Transforms

39. A single molecule is a very weak scatterer of X-rays. Most of the X-rays will pass through the molecule without being diffracted. Those rays which are diffracted are too weak to be detected. Solution: Analyzing diffraction from crystals instead of single molecules. A crystal is made of a three-dimensional repeat of ordered molecules (10 14 ) whose signals reinforce each other. The resulting diffracted rays are strong enough to be detected. A Problem… Sylvie Doublié © 2000 3D repeating lattice; Unit cell is the smallest unit of the lattice; Come in all shapes and sizes. Crystals come from slowly precipitating the biological molecule out of solution under conditions that will not damage or denature it (sometimes). A Crystal

40. X-rays Computer Crystallographer Electron density map Model Scattered rays Detector Object Putting it all together: X-ray diffraction Sylvie Doublié © 2000 Diffraction pattern is a collection of diffraction spots (reflections) Rubisco diffraction pattern

41. 3-D view of macromolecules at near atomic resolution. The result of a successful structural project is a “structure” or model of the macromolecule in the crystal. You can assign: - secondary structure elements - position and conformation of side chains - position of ligands, inhibitors, metals etc. A model allows you: - to understand biochemical and genetic data (i.e., structural basis of functional changes in mutant or modified macromolecule). - generate hypotheses regarding the roles of particular residues or domains What information does structure give you? Sylvie Doublié © 2000

42. What did I just say????!!! A structure is a “MODEL”!! What does that mean? –It is someone’s interpretation of the primary data!!!

43. So what happens when we can’t get an NMR or X-ray structure?

44. 2˚ & 3˚ Structure Prediction

45. Secondary (2 o ) Structure Table 10 ----

46. Secondary Structure Prediction One of the first fields to emerge in bioinformatics (~1967) Grew from a simple observation that certain amino acids or combinations of amino acids seemed to prefer to be in certain secondary structures Subject of hundreds of papers and dozens of books, many methods…

47. Simplified C-F Algorithm Select a window of 7 residues Calculate average P  over this window and assign that value to the central residue Repeat the calculation for P  and P c Slide the window down one residue and repeat until sequence is complete Analyze resulting “plot” and assign secondary structure (H, B, C) for each residue to highest value

48. Limitations of Chou-Fasman Does not take into account long range information (>3 residues away) Does not take into account sequence content or probable structure class Assumes simple additive probability (not true in nature) Does not include related sequences or alignments in prediction process Only about 55% accurate (on good days)

49. Protein Principles Proteins reflect millions of years of evolution. Most proteins belong to large evolutionary families. 3D structure is better conserved than sequence during evolution. Similarities between sequences or between structures may reveal information about shared biological functions of a protein family.

50. The PhD Algorithm Search the SWISS-PROT database and select high scoring homologues Create a sequence “profile” from the resulting multiple alignment Include global sequence info in the profile Input the profile into a trained two-layer neural network to predict the structure and to “clean-up” the prediction http://www.predictprotein.org/

51. Prediction Performance

52. Best of the Best PredictProtein-PHD (72%) –http://www.predictprotein.org/ Jpred (73-75%) –http://www.compbio.dundee.ac.uk/www- jpred/index.html SAM-T08 (75%) –http://compbio.soe.ucsc.edu/SAM_T08/T08- query.html PSIpred (77%) –http://bioinf.cs.ucl.ac.uk/psipred/psiform.html

53. Structure Prediction Threading A protein fold recognition technique that involves incrementally replacing the sequence of a known protein structure with a query sequence of unknown structure. Why threading? Secondary structure is more conserved than primary structure Tertiary structure is more conserved than secondary structure T H R E A D

54. An Approach SAS Calculations DSSP - Database of Secondary Structures for Proteins –http://swift.cmbi.ru.nl/gv/start/index.html VADAR - Volume Area Dihedral Angle Reporter –http://redpoll.pharmacy.ualberta.ca/vadar/ GetArea –http://curie.utmb.edu/getarea.html Naccess - Atomic Solvent Accessible Area Calculations –http://www.bioinf.msnchester.ac.uk/naccess

55. 3D Threading Servers Generate 3D models or coordinates of possible models based on input sequence PredictProtein-PHDacc –http://www.predictprotein.org PredAcc –http://mobyle.rpbs.univ-paris-diderot.fr/cgi- bin/portal.py?form=PredAcc Loopp (version 2) –http://cbsuapps.tc.cornell.edu/loopp.aspx Phyre –http://www.sbg.bio.ic.ac.uk/~phyre/ SwissModel –http://swissmodel.expasy.org/ All require email addresses since the process may take hours to complete

56. Ab Initio Folding Two Central Problems –Sampling conformational space (10 100 ) –The energy minimum problem The Sampling Problem (Solutions) –Lattice models, off-lattice models, simplified chain methods, parallelism The Energy Problem (Solutions) –Threading energies, packing assessment, topology assessment

57. Lattice Folding

59. http://folding.stanford.edu/

60. For the gamers out there… http://fold.it/portal/

61. Print & Online Resources Crystallography Made Crystal Clear, by Gale Rhodes http://www.usm.maine.edu/~rhodes/CMCC/index.html http://ruppweb.dyndns.org/Xray/101index.html Online tutorial with interactive applets and quizzes. http://www.ysbl.york.ac.uk/~cowtan/fourier/fourier.html Nice pictures demonstrating Fourier transforms http://ucxray.berkeley.edu/~jamesh/movies/ Cool movies demonstrating key points about diffraction, resolution, data quality, and refinement. http://www-structmed.cimr.cam.ac.uk/course.html Notes from a macromolecular crystallography course taught in Cambridge