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Workshop in Computational Structural Biology 2016 81813, 4 credit points Orly Marcu & Emma-joy Dodson Contents by Prof. Ora Schueler-Furman.

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Presentation on theme: "Workshop in Computational Structural Biology 2016 81813, 4 credit points Orly Marcu & Emma-joy Dodson Contents by Prof. Ora Schueler-Furman."— Presentation transcript:

1 Workshop in Computational Structural Biology 2016 81813, 4 credit points Orly Marcu & Emma-joy Dodson Contents by Prof. Ora Schueler-Furman

2 Introduction – When, Where, How? When & Where: – Thursdays, Givat Ram – Lecture & Exercise: 14:00- 18:00, Sprinzak computer class #2 – Lectures & exercises available on moodle2 http://moodle2.cs.huji.ac.il/nu15/ course/view.php?id=81813 How: – Make sure you have an account in CS ✓ Exercises -Submit 8/11 exercises -Due within 2 weeks -Submit by email to emma- joy.dodson@mail.huji.ac.il‏ emma- joy.dodson@mail.huji.ac.il‏ Contact: Orly 87063 orlymarcu@gmail.com Emma 87063 emma-joy.dodson@mail.huji.ac.il‏ Acknowledgements: Sources of figures and slides include slides from Branden & Tooze; some slides have been adapted from members of the Rosetta Community, especially from Jens Meiler Exercises in Pyrosetta have been adapted from teaching material by Jeff Gray

3 Structure prediction (mainly Rosetta; also I-TASSER, MODELLER): – from sequence alone to high resolution models (Ab-initio modeling) – From homologous structures to high resolution models What will we learn? MSKAVGIDLGTTYSC…… || MSKAVGIDLGTTYSC……

4 Protein design – Engineering novel proteins not found in nature to fit a desired fold/function What will we learn? Gordon et. Al. JACS (2012). Computational Design of an α ‑ Gliadin Peptidase

5 Protein-protein docking – achieve models of protein complexes given two monomers (Rosetta, PatchDock, PIPER, HADDOCK) Interface analysis and design – identify interface “hotspots” (via computational alanine scanning); change protein specificity What will we learn?

6 Optimization techniques: – Energy Minimization; concepts and implementation in Rosetta – Monte-Carlo methods Side chain modeling – Deterministic and heuristic methods for finding preferred side chain combinations given a certain backbone What will we learn? START energy conformations

7 Existing protocols, out of this course’s scope: Protein-ligand docking Membrane proteins modeling and design Peptide-protein docking DNA & RNA modeling Antibody modeling What we will not learn

8 The central dogma

9 The code: 4 bases, 64 triplets, 20 amino acids

10 4 Hierarchies of protein structure Anfinsen: sequence determines structure

11 The building blocks: amino acids

12 The building blocks: 20 amino acids Differ in size, polarity, charge, secondary structure propensity …

13 The simplest aa No sc Very flexible bb Special amino acids Cyclic aa sc Connects bb N Very constrained bb N CO CH HH N CH CH 2 H2CH2C

14 Aliphatic amino acids sc contains only carbon and hydrogen atoms hydrophobic

15 Amino acids with hydroxyl group

16 Negatively charged amino acids Different size → different tendency for 2. structure

17 Amide amino acids

18 Positively charged amino acids large sc pK a 11.1 pK a 12

19 Aromatic amino acids sc contains aromatic ring Figure from Wikipedia Figure from Proteopedia

20 Amino acids with sulfur

21 Cystine Oxidation of Sulfur atoms creates covalent disulfide bond (S-S bond) between two cysteines

22 Hydrogen bonding potential of amino acids

23 S-S bonds stabilize the protein A chain G I V E Q C C A S V C S L Y Q L E N E N Y C N s s s s B chain F V N Q H L C G S H L V E A L Y L V C G E R G F.. s s Insulin A chain N C B chain

24 Post-translational modifications Processing (pro-insulin/insulin) – control of protein activity Glycosylation – protein trafficking Phosphorylation (Tyr, Ser, Thr) – regulation of signaling Methylation, Acetylation – histone tagging ….

25 Metal binding proteins aa: HCDE Fe, Zn, Mg, Ca Fe – blood: red hemoglobin – electro-transfer: cytochrome c Zn – in DNA-binding “Zn-finger” proteins – Alcohol dehydrogenase: oxidation of alcohol 25

26 Primary sequence: concatenated amino acids

27

28 Formation of a peptide bond O - oxygen N - nitrogen O-O- +H3N+H3N R H CC O C || H - hydrogen C - carbon cpk colors

29 The geometry of the peptide backbone Peptide bond length and angles do not change Peptide dihedral angles define structure The peptide bond is planar & polar:   

30 Dihedral angles Dihedral angles  1 -  4 define side chain From wikipedia Dihedral angle: defines geometry of 4 atoms (given bond lengths and angles)

31 The geometry of the peptide backbone Peptide bond length and angles do not change Peptide dihedral angles define structure The peptide bond is planar & polar:  =180 o (trans) or 0 o (cis)   

32 The search for the native fold The Levinthal paradox: a 100 residue protein would require 10 16 seconds to explore all possible conformations and choose the native one. Quick collapse to intermediate state, followed by accurate contacts formation Quick collapses followed by unfolding until near native state achieved

33 Ramachandran plot Glycine: flexible backboneAll except Glycine   33

34 Ramachandran plot   34

35 Secondary structure: local interactions

36 Secondary structure – built from backbone hydrogen bonds

37  helix discovered 1951 by Pauling 5-40 aa long average: 10aa right handed O i -NH i+4 : bb atoms satisfied  helix: i - i+5 3 10 helix: i - i+3 1.5Å/res Favored: Glu, Ala, Leu, Arg, Met, Lys Disfavored: Asn, Thr, Cys, Asp, Gly

38 Frequent amino acids at the N-terminus of  helices Pro Blocks the continuation of the helix by its side chain Asn, Ser Block the continuation of the helix by hydrogen bonding with the donor (NH) of N 3 N cap, N 1, N 2, N 3 …….C cap 38

39  helix: dipole binds negative charges at N-terminus

40 Helices of different character 1.buried 2.partially exposed 3.exposed 40

41 Representation: helical wheel 41 1.buried 2.partially exposed: amphipathic helix 3.exposed

42  -sheet Involves several regions in sequence Residue side chains point up/down/up.. O i -NH j Parallel and anti-parallel sheets 42 Favored: Tyr, Thr, Ile, Phe, Trp Disfavored: Glu, Ala, Asp, Gly, Pro

43 Antiparallel  -sheet Parallel Hbonds Pleated 43

44 Beta-hairpin Loops Connect strands in antiparallel sheet G,N,D GGS,T 44

45 Parallel  -sheet less stable than antiparallel sheet angled hbonds 45

46 Connecting elements of secondary structure define tertiary structure 46

47 Tertiary structure defines protein function

48 Loops connect helices and strands at surface of molecule more flexible contain functional sites 48

49 Important bonds for protein folding and stability Dipole moments attract each other by van der Waals force (transient and very weak: 0.1-0.2 kcal.mol) Hydrophobic interaction – hydrophobic groups/ molecules tend to cluster together and shield themselves from the hydrophilic solvent Dipole moments attract each other by van der Waals force (transient and very weak: 0.1-0.2 kcal.mol) Hydrophobic interaction – hydrophobic groups/ molecules tend to cluster together and shield themselves from the hydrophilic solvent

50 Formation of the aformentioned bonds contributes to the enthalpy of the system, decreasing protein enropy Interplay of enthalpy and entropy in protein folding change in Gibbs free energy change in enthaply change in the entropic term

51 The hydrophobic effect A central effect in protein folding Driven by entropy – gain of water molecules entropy Water molecules near hydrophobic elements have less freedom to form and break hydrogen bonds with neighboring waters More water molecules not in direct contact with hydrophobic elements Figures from post by Dr. Steve Mack on www.madsci.orgwww.madsci.org

52 Super secondary structures – Greek Key Motif Most common topology for 2 hairpins 52

53 Super Secondary Structures-  Motif connects strands in parallel sheet always right-handed 53

54 Repeated  motif creates  -meander: TIM barrel 54

55 The quaternary structure of a protein defines its biological functional unit 55

56 Quaternary structure: Hemoglobin consists of 4 distinct chains

57 Quaternary structure: assembly of protein domains (from two distinct protein chains, or two domains in one protein sequence) Glyceraldehyde phosphate dehydrogenase: domain 1 binds the substance to be metabolized, domain 2 binds a cofactor

58 1. Introduction to Computational Structural Biology Experimental determination of protein structure: X-ray diffraction and NMR

59 X-ray diffraction Rotation of crystal enables recording different diffractions Resolution measures diffraction angles; higher angle peaks  higher resolution

60 X-ray diffraction If direction is such that -> Constructive addition -> Reflection spot in the diffraction pattern Wavelength of x-ray ~ crystal plane separations Rotation of crystal relative to beam allows recording of different diffractions Diffraction maps are translated to electron density maps using Fourier Transform Resolution measures diffraction angles (high angle peaks – high resolution data)

61 X-ray diffraction Iterative refinement allows improvement of structure R-factor measures quality Fo – observed Fc - calculated

62 NMR (Nuclear Magnetic Resonance) NMR-active nuclei (w spins) 1 H, 13 C, 15N Application of magnetic field reorients spins – measure resonance between close nuclei Extract constraints & determine structure more constraints – better defined structure

63 Experimental determination of structure X-ray crystallography Determines electron density – positions of atoms in structure Highly accurate Technically challenging Depends on crystal (static; artifacts?) NMR Determines constraints between labeled spins Allows measure of structure in solution

64 Progress in experimental determination of structures 1950’s first protein structure solved by Kendrew & Perutz: sperm whale myoglobin Today: ~114,000 structures solved, most by x-ray crystallography


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