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CSE182-L7

CSE182-L7. Protein sequencing and Mass Spectrometry. Announcements. Midterm 1: Nov 1, in class. Assignment 2: Online, due October 20. Trivia Quiz. What research won the Nobel prize in Chemistry in 2004? In 2002?. How are Proteins Sequenced? Mass Spec 101:. Nobel Citation 2002.

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CSE182-L7

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  1. CSE182-L7 Protein sequencing and Mass Spectrometry CSE182

  2. Announcements • Midterm 1: Nov 1, in class. • Assignment 2: Online, due October 20. CSE182

  3. Trivia Quiz • What research won the Nobel prize in Chemistry in 2004? • In 2002? CSE182

  4. How are Proteins Sequenced? Mass Spec 101: CSE182

  5. Nobel Citation 2002 CSE182

  6. Nobel Citation, 2002 CSE182

  7. Mass Spectrometry CSE182

  8. Enzymatic Digestion (Trypsin) + Fractionation Sample Preparation CSE182

  9. Single Stage MS Mass Spectrometry LC-MS: 1 MS spectrum / second CSE182

  10. Tandem MS Secondary Fragmentation Ionized parent peptide CSE182

  11. The peptide backbone The peptide backbone breaks to form fragments with characteristic masses. H...-HN-CH-CO-NH-CH-CO-NH-CH-CO-…OH Ri-1 Ri Ri+1 C-terminus N-terminus AA residuei-1 AA residuei+1 AA residuei CSE182

  12. Ionization The peptide backbone breaks to form fragments with characteristic masses. H+ H...-HN-CH-CO-NH-CH-CO-NH-CH-CO-…OH Ri-1 Ri Ri+1 C-terminus N-terminus AA residuei-1 AA residuei+1 AA residuei Ionized parent peptide CSE182

  13. Fragment ion generation The peptide backbone breaks to form fragments with characteristic masses. H+ H...-HN-CH-CONH-CH-CO-NH-CH-CO-…OH Ri-1 Ri Ri+1 C-terminus N-terminus AA residuei-1 AA residuei AA residuei+1 Ionized peptide fragment CSE182

  14. Tandem MS for Peptide ID 88 145 292 405 534 663 778 907 1020 1166 b ions S G F L E E D E L K 1166 1080 1022 875 762 633 504 389 260 147 y ions 100 % Intensity [M+2H]2+ 0 250 500 750 1000 m/z CSE182

  15. Peak Assignment 88 145 292 405 534 663 778 907 1020 1166 b ions S G F L E E D E L K 1166 1080 1022 875 762 633 504 389 260 147 y ions y6 100 Peak assignment implies Sequence (Residue tag) Reconstruction! y7 % Intensity [M+2H]2+ y5 b3 b4 y2 y3 b5 y4 y8 b8 b9 b6 b7 y9 0 250 500 750 1000 m/z CSE182

  16. Database Searching for peptide ID • For every peptide from a database • Generate a hypothetical spectrum • Compute a correlation between observed and experimental spectra • Choose the best • Database searching is very powerful and is the de facto standard for MS. • Sequest, Mascot, and many others CSE182

  17. Spectra: the real story • Noise Peaks • Ions, not prefixes & suffixes • Mass to charge ratio, and not mass • Multiply charged ions • Isotope patterns, not single peaks CSE182

  18. xn-i yn-i yn-i-1 vn-i wn-i zn-i -HN-CH-CO-NH-CH-CO-NH- CH-R’ Ri i+1 ai R” i+1 bi bi+1 ci di+1 low energy fragments high energy fragments Peptide fragmentation possibilities(ion types) CSE182

  19. Ion types, and offsets • P = prefix residue mass • S = Suffix residue mass • b-ions = P+1 • y-ions = S+19 • a-ions = P-27 CSE182

  20. Mass-Charge ratio • The X-axis is (M+Z)/Z • Z=1 implies that peak is at M+1 • Z=2 implies that peak is at (M+2)/2 • M=1000, Z=2, peak position is at 501 • Suppose you see a peak at 501. Is the mass 500, or is it 1000? CSE182

  21. Isotopic peaks • Ex: Consider peptide SAM • Mass = 308.12802 • You should see: • Instead, you see 308.13 308.13 310.13 CSE182

  22. Isotopes • C-12 is the most common. Suppose C-13 occurs with probability 1% • EX: SAM • Composition: C11 H22 N3 O5 S1 • What is the probability that you will see a single C-13? • Note that C,S,O,N all have isotopes. Can you compute the isotopic distribution? CSE182

  23. All atoms have isotopes • Isotopes of atoms • O16,18, C-12,13, S32,34…. • Each isotope has a frequency of occurrence • If a molecule (peptide) has a single copy of C-13, that will shift its peak by 1 Da • With multiple copies of a peptide, we have a distribution of intensities over a range of masses (Isotopic profile). • How can you compute the isotopic profile of a peak? CSE182

  24. Nc=50 +1 Isotope Calculation • Denote: • Nc : number of carbon atoms in the peptide • Pc : probability of occurrence of C-13 (~1%) • Then Nc=200 +1 CSE182

  25. Isotope Calculation Example • Suppose we consider Nitrogen, and Carbon • NN: number of Nitrogen atoms • PN: probability of occurrence of N-15 • Pr(peak at M) • Pr(peak at M+1)? • Pr(peak at M+2)? How do we generalize? How can we handle Oxygen (O-16,18)? CSE182

  26. General isotope computation • Definition: • Let pi,a be the abundance of the isotope with mass i Da above the least mass • Ex: P0,C : abundance of C-12, P2,O: O-18 etc. • Characteristic polynomial • Prob{M+i}: coefficient of xi in (x) (a binomial convolution) CSE182

  27. Isotopic Profile Application • In DxMS, hydrogen atoms are exchanged with deuterium • The rate of exchange indicates how buried the peptide is (in folded state) • Consider the observed characteristic polynomial of the isotope profile t1, t2, at various time points. Then • The estimates of p1,H can be obtained by a deconvolution • Such estimates at various time points should give the rate of incorporation of Deuterium, and therefore, the accessibility. CSE182

  28. Quiz • How can you determine the charge on a peptide? • Difference between the first and second isotope peak is 1/Z • Proposal: • Given a mass, predict a composition, and the isotopic profile • Do a ‘goodness of fit’ test to isolate the peaks corresponding to the isotope • Compute the difference CSE182

  29. Tandem MS summary • The basics of peptide ID using tandem MS is simple. • Correlate experimental with theoretical spectra • In practice, there might be many confounding problems. • A toolkit that resolves some of these problems will be useful. CSE182

  30. MS Quiz: • Why aren’t all tandem MS peaks of the same intensity? • Do the intensities for a peptide vary from spectrum to spectrum? CSE182

  31. De novo interpretation of mass spectra • The so called de novo algorithms focus exclusively on the D module. • There is no database (I/F). • Limited scoring and validation CSE182

  32. Computing possible prefixes • We know the parent mass M=401. • Consider a mass value 88 • Assume that it is a b-ion, or a y-ion • If b-ion, it corresponds to a prefix of the peptide with residue mass 88-1 = 87. • If y-ion, y=M-P+19. • Therefore the prefix has mass • P=M-y+19= 401-88+19=332 • Compute all possible Prefix Residue Masses (PRM) for all ions. CSE182

  33. Putative Prefix Masses Prefix Mass M=401 b y 88 87 332 145 144 275 147 146 273 276 275 144 • Only a subset of the prefix masses are correct. • The correct mass values form a ladder of amino-acid residues S G E K 0 87 144 273 401 CSE182

  34. Spectral Graph • Each prefix residue mass (PRM) corresponds to a node. • Two nodes are connected by an edge if the mass difference is a residue mass. • A path in the graph is a de novo interpretation of the spectrum 87 G 144 CSE182

  35. 0 273 332 401 87 144 146 275 100 200 300 S G E K Spectral Graph • Each peak, when assigned to a prefix/suffix ion type generates a unique prefix residue mass. • Spectral graph: • Each node u defines a putative prefix residue M(u). • (u,v) in E if M(v)-M(u) is the residue mass of an a.a. (tag) or 0. • Paths in the spectral graph correspond to a interpretation CSE182

  36. 0 273 332 401 87 144 146 275 100 200 300 S G E K Re-defining de novo interpretation • Find a subset of nodes in spectral graph s.t. • 0, M are included • Each peak contributes at most one node (interpretation)(*) • Each adjacent pair (when sorted by mass) is connected by an edge (valid residue mass) • An appropriate objective function (ex: the number of peaks interpreted) is maximized 87 G 144 CSE182

  37. 0 273 332 401 87 144 146 275 100 200 300 S G E K Two problems • Too many nodes. • Only a small fraction are correspond to b/y ions (leading to true PRMs) (learning problem) • Even if the b/y ions were correctly predicted, each peak generates multiple possibilities, only one of which is correct. We need to find a path that uses each peak only once (algorithmic problem). • In general, the forbidden pairs problem is NP-hard CSE182

  38. However,.. • The b,y ions have a special non-interleaving property • Consider pairs (b1,y1), (b2,y2) • If (b1 < b2), then y1 > y2 CSE182

  39. 100 0 400 200 Non-Intersecting Forbidden pairs 332 300 87 S • If we consider only b,y ions, ‘forbidden’ node pairs are non-intersecting, • The de novo problem can be solved efficiently using a dynamic programming technique. G E K CSE182

  40. The forbidden pairs method • There may be many paths that avoid forbidden pairs. • We choose a path that maximizes an objective function, • EX: the number of peaks interpreted CSE182

  41. 332 100 300 0 400 200 87 The forbidden pairs method • Sort the PRMs according to increasing mass values. • For each node u, f(u) represents the forbidden pair • Let m(u) denote the mass value of the PRM. f(u) u CSE182

  42. D.P. for forbidden pairs • Consider all pairs u,v • m[u] <= M/2, m[v] >M/2 • Define S(u,v) as the best score of a forbidden pair path from 0->u, v->M • Is it sufficient to compute S(u,v) for all u,v? 332 100 300 0 400 200 87 u v CSE182

  43. D.P. for forbidden pairs • Note that the best interpretation is given by 332 100 300 0 400 200 87 u v CSE182

  44. D.P. for forbidden pairs • Note that we have one of two cases. • Either u < f(v) (and f(u) > v) • Or, u > f(v) (and f(u) < v) • Case 1. • Extend u, do not touch f(v) 100 300 0 f(u) 400 200 u v CSE182

  45. The complete algorithm for all u /*increasing mass values from 0 to M/2 */ for all v /*decreasing mass values from M to M/2 */ if (u > f[v]) else if (u < f[v]) If (u,v)E /*maxI is the score of the best interpretation*/ maxI = max {maxI,S[u,v]} CSE182

  46. De Novo: Second issue • Given only b,y ions, a forbidden pairs path will solve the problem. • However, recall that there are MANY other ion types. • Typical length of peptide: 15 • Typical # peaks? 50-150? • #b/y ions? • Most ions are “Other” • a ions, neutral losses, isotopic peaks…. CSE182

  47. De novo: Weighting nodes in Spectrum Graph • Factors determining if the ion is b or y • Intensity • Support ions • Isotopic peaks (InsPecT’) CSE182

  48. De novo: Weighting nodes • A probabilistic network to model support ions (Pepnovo) CSE182

  49. De Novo Interpretation Summary • The main challenge is to separate b/y ions from everything else (weighting nodes), and separating the prefix ions from the suffix ions (Forbidden Pairs). • As always, the abstract idea must be supplemented with many details. • Noise peaks, incomplete fragmentation • In reality, a PRM is first scored on its likelihood of being correct, and the forbidden pair method is applied subsequently. CSE182

  50. CSE182

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