Protein sequencing and Mass Spectrometry
Sample Preparation
Enzymatic Digestion
(Trypsin)
+
Fractionation
Single Stage MS
Mass
Spectrometry
LC-MS: 1 MS spectrum / second
Tandem MS
Secondary Fragmentation
Ionized parent peptide
The peptide backbone
The peptide backbone breaks to form
fragments with characteristic masses.
H...-HN-CH-CO-NH-CH-CO-NH-CH-CO-…OH
N-terminus
Ri-1
AA residuei-1
Ri
AA residuei
Ri+1
AA residuei+1
C-terminus
Ionization
The peptide backbone breaks to form
fragments with characteristic masses.
H+
H...-HN-CH-CO-NH-CH-CO-NH-CH-CO-…OH
N-terminus
Ri-1
AA residuei-1
Ri
AA residuei
Ri+1
AA residuei+1
Ionized parent peptide
C-terminus
Fragment ion generation
The peptide backbone breaks to form
fragments with characteristic masses.
H+
H...-HN-CH-CO
N-terminus
Ri-1
AA residuei-1
NH-CH-CO-NH-CH-CO-…OH
Ri
AA residuei
Ri+1
AA residuei+1
Ionized peptide fragment
C-terminus
Tandem MS for Peptide ID
88
S
1166
145
G
1080
292
F
1022
405
L
875
534
E
762
663
E
633
778
D
504
907
E
389
1020
L
260
1166
K
147
% Intensity
100
[M+2H]2+
0
250
500
750
m/z
1000
b ions
y ions
Peak Assignment
88
S
1166
145
G
1080
292
F
1022
405
L
875
534
E
762
663
E
633
778
D
504
907
E
389
1020
L
260
1166
K
147
b ions
y ions
y6
100
% Intensity
Peak assignment implies
Sequence (Residue tag)
Reconstruction!
[M+2H]2+
y5
b3
y2
y7
y3
b4
y4 b5
b6
b7
b8
b9 y8
0
250
500
750
m/z
1000
y9
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
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
Peptide fragmentation possibilities
(ion types)
xn-i
yn-i
vn-i
yn-i-1
wn-i
zn-i
-HN-CH-CO-NH-CH-CO-NHRi
CH-R’
i+1
ai
R”
i+1
bi
low energy fragments
ci
di+1
bi+1
high energy fragments
Ion types, and offsets
•
•
•
•
•
P = prefix residue mass
S = Suffix residue mass
b-ions = P+1
y-ions = S+19
a-ions = P-27
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?
Spectral Graph
87
G
144
• 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
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
0
87
100
S
273275
144 146
G
200
E
332
300
K
401
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
G
87
0
87
273275
144 146
100
S
144
G
200
E
332
300
K
401
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
0
87
100
S
273275
144 146
G
200
E
332
300
K
401
However,..
• The b,y ions have a special non-interleaving
property
• Consider pairs (b1,y1), (b2,y2)
– If (b1 < b2), then y1 > y2
Non-Intersecting Forbidden pairs
0
87
S
•
•
100
G
200
E
300
332
400
K
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.
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
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.
0
87
100
u
200
300
332
f(u)
400
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?
0
87
100
u
200
300
332
400
v
D.P. for forbidden pairs
• Note that the best interpretation is given by
max ((u,v )E ) S(u,v)

0
87
100
300
200
u
v
332
400
D.P. for forbidden pairs
•
Note that we have one of two cases.
•
Case 1.
1.
2.
Either u < f(v) (and f(u) > v)
Or, u > f(v) (and f(u) < v)
–
Extend u, do not touch f(v)
S(u,v)  max
u':(u,u')E
(
)
u' f (v)
S(u,u')  1

0
u
100
300
200
v
f(u)
400
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])
S[u,v]  max (w,u)E  S[w,v]  1


 w f (v ) 
else if (u < f[v])
S[u,v]  max (v,w )E  S[u,w]  1
 If (u,v)E


 w f (u) 
/*maxI is the score of the best interpretation*/
maxI = max {maxI,S[u,v]}
