HLA MHCs are the gatekeepers of the immune system. 1.) LOCATE: Present peptides that may be viral....

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Transcript of HLA MHCs are the gatekeepers of the immune system. 1.) LOCATE: Present peptides that may be viral....

HLA

HLA

MHCs are the gatekeepers of the immune system.

1.) LOCATE: Present peptides that may be viral.

2.) ACTIVATE: Activate immune defense mechanisms.

HLAClass 1

8-10 AA 13-25 AA

Class 2

# ~80 # ~40 Closed Open

HLA

Understanding the HLA:

Structural chemistry (x-ray crystallography), biological processes, role within the immune system, binding behavior, statistical distribution.2 ways of looking at this:

1.) Descriptive

2.) Functional

HLA

Understanding the HLA:

Structural chemistry (x-ray crystallography), biological processes, role within the immune system, binding behavior, statistical distribution.2 ways of looking at this:

1.) Descriptive

2.) Functional

What fits in an HLA?

What fits in an HLA?

Find out experimentally?

# Class I HLA’s ≃ 80

What fits in an HLA?

Find out experimentally?

# Class I HLA’s ≃ 80

# Possible 9-mers:

20^9 = 512,000,000,000 ≃ 10^11

What fits in an HLA?

Calculate theoretically?

Binding Motifs

Quantitative Matrices

Molecular

Artificial Neural Network

Hidden Markov Models

What fits in an HLA?

Binding Motifs:

Hypothesis: HLA binding entirely determined by a few AA (1-3) on the peptide.

Approach: Check peptide for anchor residue.

Calculate theoretically?

What fits in an HLA?

Binding Motifs:

i.e A1 Serotype: X X [D/E] X X X [Y]

X X [D/E] X X X X [Y]

X X [D/E] X X X X X [Y]

Binds peptides: BK[D]LGGSD[Y]

AC[D]SWIH[Y]

Calculate theoretically?

What fits in an HLA?

Quantitative Matrices:

Hypothesis: Binding is determined by AA on the specific HLA.

Approach: Construct a virtual matrix and determine a threshold value. Check if product of AA values in virtual matrix exceed threshold.

Calculate theoretically?

What fits in an HLA?

Quantitative Matrices:

Calculate theoretically?

9-mer Coefficient Table for HLA_A3

Amino

Acid Type Position

1st 2n 3rd 4th 5th 6th 7th 8th 9th

A 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

C 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

D 0.300 0.100 1.000 1.000 1.000 1.000 1.000 1.000 0.100

E 0.300 0.300 1.000 1.500 1.000 1.000 1.000 1.000 0.100

F 1.000 0.100 5.000 1.000 3.000 3.000 3.000 1.000 10.000

G 3.000 0.100 1.000 1.500 1.000 1.000 0.300 1.000 0.100

. . .

V 1.000 10.000 1.500 1.000 1.500 3.000 1.000 1.000 1.000

W 1.000 0.100 5.000 1.000 3.000 1.000 3.000 1.000 1.000

Y 1.000 0.100 5.000 1.000 3.000 1.000 3.000 1.000 20.000

final

constant 0.002

What fits in an HLA?

Quantitative Matrices:

Calculate theoretically?

9-mer Coefficient Table for HLA_A3

Amino

Acid Type Position

1st 2n 3rd 4th 5th 6th 7th 8th 9th

A 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

C 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

D 0.300 0.100 1.000 1.000 1.000 1.000 1.000 1.000 0.100

E 0.300 0.300 1.000 1.500 1.000 1.000 1.000 1.000 0.100

F 1.000 0.100 5.000 1.000 3.000 3.000 3.000 1.000 10.000

G 3.000 0.100 1.000 1.500 1.000 1.000 0.300 1.000 0.100

. . .

V 1.000 10.000 1.500 1.000 1.500 3.000 1.000 1.000 1.000

W 1.000 0.100 5.000 1.000 3.000 1.000 3.000 1.000 1.000

Y 1.000 0.100 5.000 1.000 3.000 1.000 3.000 1.000 20.000

final

constant 0.002

ADCGTVMCE

What fits in an HLA?

Quantitative Matrices:

Calculate theoretically?

9-mer Coefficient Table for HLA_A3

Amino

Acid Type Position

1st 2n 3rd 4th 5th 6th 7th 8th 9th

A 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

C 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

D 0.300 0.100 1.000 1.000 1.000 1.000 1.000 1.000 0.100

E 0.300 0.300 1.000 1.500 1.000 1.000 1.000 1.000 0.100

F 1.000 0.100 5.000 1.000 3.000 3.000 3.000 1.000 10.000

G 3.000 0.100 1.000 1.500 1.000 1.000 0.300 1.000 0.100

. . .

V 1.000 10.000 1.500 1.000 1.500 3.000 1.000 1.000 1.000

W 1.000 0.100 5.000 1.000 3.000 1.000 3.000 1.000 1.000

Y 1.000 0.100 5.000 1.000 3.000 1.000 3.000 1.000 20.000

final

constant 0.002

ADCGTVMCE

What fits in an HLA?

Quantitative Matrices:

Calculate theoretically?

9-mer Coefficient Table for HLA_A3

Amino

Acid Type Position

1st 2n 3rd 4th 5th 6th 7th 8th 9th

A 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

C 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

D 0.300 0.100 1.000 1.000 1.000 1.000 1.000 1.000 0.100

E 0.300 0.300 1.000 1.500 1.000 1.000 1.000 1.000 0.100

F 1.000 0.100 5.000 1.000 3.000 3.000 3.000 1.000 10.000

G 3.000 0.100 1.000 1.500 1.000 1.000 0.300 1.000 0.100

. . .

V 1.000 10.000 1.500 1.000 1.500 3.000 1.000 1.000 1.000

W 1.000 0.100 5.000 1.000 3.000 1.000 3.000 1.000 1.000

Y 1.000 0.100 5.000 1.000 3.000 1.000 3.000 1.000 20.000

final

constant 0.002

ADCGTVMCE

What fits in an HLA?

Quantitative Matrices:

Calculate theoretically?

9-mer Coefficient Table for HLA_A3

Amino

Acid Type Position

1st 2n 3rd 4th 5th 6th 7th 8th 9th

A 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

C 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

D 0.300 0.100 1.000 1.000 1.000 1.000 1.000 1.000 0.100

E 0.300 0.300 1.000 1.500 1.000 1.000 1.000 1.000 0.100

F 1.000 0.100 5.000 1.000 3.000 3.000 3.000 1.000 10.000

G 3.000 0.100 1.000 1.500 1.000 1.000 0.300 1.000 0.100

. . .

V 1.000 10.000 1.500 1.000 1.500 3.000 1.000 1.000 1.000

W 1.000 0.100 5.000 1.000 3.000 1.000 3.000 1.000 1.000

Y 1.000 0.100 5.000 1.000 3.000 1.000 3.000 1.000 20.000

final

constant 0.002

ADCGTVMCE

What fits in an HLA?

Quantitative Matrices:

Calculate theoretically?

9-mer Coefficient Table for HLA_A3

Amino

Acid Type Position

1st 2n 3rd 4th 5th 6th 7th 8th 9th

A 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

C 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

D 0.300 0.100 1.000 1.000 1.000 1.000 1.000 1.000 0.100

E 0.300 0.300 1.000 1.500 1.000 1.000 1.000 1.000 0.100

F 1.000 0.100 5.000 1.000 3.000 3.000 3.000 1.000 10.000

G 3.000 0.100 1.000 1.500 1.000 1.000 0.300 1.000 0.100

. . .

V 1.000 10.000 1.500 1.000 1.500 3.000 1.000 1.000 1.000

W 1.000 0.100 5.000 1.000 3.000 1.000 3.000 1.000 1.000

Y 1.000 0.100 5.000 1.000 3.000 1.000 3.000 1.000 20.000

final

constant 0.002

ADCGTVMCE

What fits in an HLA?

Quantitative Matrices:

Calculate theoretically?

9-mer Coefficient Table for HLA_A3

Amino

Acid Type Position

1st 2n 3rd 4th 5th 6th 7th 8th 9th

A 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

C 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

D 0.300 0.100 1.000 1.000 1.000 1.000 1.000 1.000 0.100

E 0.300 0.300 1.000 1.500 1.000 1.000 1.000 1.000 0.100

F 1.000 0.100 5.000 1.000 3.000 3.000 3.000 1.000 10.000

G 3.000 0.100 1.000 1.500 1.000 1.000 0.300 1.000 0.100

. . .

V 1.000 10.000 1.500 1.000 1.500 3.000 1.000 1.000 1.000

W 1.000 0.100 5.000 1.000 3.000 1.000 3.000 1.000 1.000

Y 1.000 0.100 5.000 1.000 3.000 1.000 3.000 1.000 20.000

final

constant 0.002

ADCGTVMCE

What fits in an HLA?

Quantitative Matrices:

Calculate theoretically?

9-mer Coefficient Table for HLA_A3

Amino

Acid Type Position

1st 2n 3rd 4th 5th 6th 7th 8th 9th

A 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

C 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

D 0.300 0.100 1.000 1.000 1.000 1.000 1.000 1.000 0.100

E 0.300 0.300 1.000 1.500 1.000 1.000 1.000 1.000 0.100

F 1.000 0.100 5.000 1.000 3.000 3.000 3.000 1.000 10.000

G 3.000 0.100 1.000 1.500 1.000 1.000 0.300 1.000 0.100

. . .

V 1.000 10.000 1.500 1.000 1.500 3.000 1.000 1.000 1.000

W 1.000 0.100 5.000 1.000 3.000 1.000 3.000 1.000 1.000

Y 1.000 0.100 5.000 1.000 3.000 1.000 3.000 1.000 20.000

final

constant 0.002

ADCGTVMCE

What fits in an HLA?

Quantitative Matrices:

Calculate theoretically?

9-mer Coefficient Table for HLA_A3

Amino

Acid Type Position

1st 2n 3rd 4th 5th 6th 7th 8th 9th

A 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

C 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

D 0.300 0.100 1.000 1.000 1.000 1.000 1.000 1.000 0.100

E 0.300 0.300 1.000 1.500 1.000 1.000 1.000 1.000 0.100

F 1.000 0.100 5.000 1.000 3.000 3.000 3.000 1.000 10.000

G 3.000 0.100 1.000 1.500 1.000 1.000 0.300 1.000 0.100

. . .

V 1.000 10.000 1.500 1.000 1.500 3.000 1.000 1.000 1.000

W 1.000 0.100 5.000 1.000 3.000 1.000 3.000 1.000 1.000

Y 1.000 0.100 5.000 1.000 3.000 1.000 3.000 1.000 20.000

final

constant 0.002

ADCGTVMCE

What fits in an HLA?

Quantitative Matrices:

Calculate theoretically?

9-mer Coefficient Table for HLA_A3

Amino

Acid Type Position

1st 2n 3rd 4th 5th 6th 7th 8th 9th

A 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

C 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

D 0.300 0.100 1.000 1.000 1.000 1.000 1.000 1.000 0.100

E 0.300 0.300 1.000 1.500 1.000 1.000 1.000 1.000 0.100

F 1.000 0.100 5.000 1.000 3.000 3.000 3.000 1.000 10.000

G 3.000 0.100 1.000 1.500 1.000 1.000 0.300 1.000 0.100

. . .

V 1.000 10.000 1.500 1.000 1.500 3.000 1.000 1.000 1.000

W 1.000 0.100 5.000 1.000 3.000 1.000 3.000 1.000 1.000

Y 1.000 0.100 5.000 1.000 3.000 1.000 3.000 1.000 20.000

final

constant 0.002

ADCGTVMCE

What fits in an HLA?

Quantitative Matrices:

Calculate theoretically?

9-mer Coefficient Table for HLA_A3

Amino

Acid Type Position

1st 2n 3rd 4th 5th 6th 7th 8th 9th

A 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

C 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

D 0.300 0.100 1.000 1.000 1.000 1.000 1.000 1.000 0.100

E 0.300 0.300 1.000 1.500 1.000 1.000 1.000 1.000 0.100

F 1.000 0.100 5.000 1.000 3.000 3.000 3.000 1.000 10.000

G 3.000 0.100 1.000 1.500 1.000 1.000 0.300 1.000 0.100

. . .

V 1.000 10.000 1.500 1.000 1.500 3.000 1.000 1.000 1.000

W 1.000 0.100 5.000 1.000 3.000 1.000 3.000 1.000 1.000

Y 1.000 0.100 5.000 1.000 3.000 1.000 3.000 1.000 20.000

final

constant 0.002

ADCGTVMCE

What fits in an HLA?

Quantitative Matrices:

Calculate theoretically?

9-mer Coefficient Table for HLA_A3

Amino

Acid Type Position

1st 2n 3rd 4th 5th 6th 7th 8th 9th

A 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

C 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

D 0.300 0.100 1.000 1.000 1.000 1.000 1.000 1.000 0.100

E 0.300 0.300 1.000 1.500 1.000 1.000 1.000 1.000 0.100

F 1.000 0.100 5.000 1.000 3.000 3.000 3.000 1.000 10.000

G 3.000 0.100 1.000 1.500 1.000 1.000 0.300 1.000 0.100

. . .

V 1.000 10.000 1.500 1.000 1.500 3.000 1.000 1.000 1.000

W 1.000 0.100 5.000 1.000 3.000 1.000 3.000 1.000 1.000

Y 1.000 0.100 5.000 1.000 3.000 1.000 3.000 1.000 20.000

final

constant 0.002

ADCGTVMCE

What fits in an HLA?

Quantitative Matrices:

Calculate theoretically?

9-mer Coefficient Table for HLA_A3

Amino

Acid Type Position

1st 2n 3rd 4th 5th 6th 7th 8th 9th

A 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

C 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

D 0.300 0.100 1.000 1.000 1.000 1.000 1.000 1.000 0.100

E 0.300 0.300 1.000 1.500 1.000 1.000 1.000 1.000 0.100

F 1.000 0.100 5.000 1.000 3.000 3.000 3.000 1.000 10.000

G 3.000 0.100 1.000 1.500 1.000 1.000 0.300 1.000 0.100

. . .

V 1.000 10.000 1.500 1.000 1.500 3.000 1.000 1.000 1.000

W 1.000 0.100 5.000 1.000 3.000 1.000 3.000 1.000 1.000

Y 1.000 0.100 5.000 1.000 3.000 1.000 3.000 1.000 20.000

final

constant 0.002

ADCGTVMCE

1.0 x 0.1 x 1.0 x 1.5 x 3.0 x 3.0 x 3.0 x 1.0 x 10.0 x 0.002

= 0.081

What fits in an HLA?

Quantitative Matrices:

Calculate theoretically?

If 0.081 > threshold, then ADCGTVMCE is bound by class I HLA A3.

Vaccination

Vaccination

1.) Determine a ‘good’ viral peptide sequence.

2.) Create and inject these peptides.

- Candidate peptide bound and presented on HLA- Stimulate immune response

- Subject is protected from virus

Vaccination

What is a ‘good’ viral peptide sequence?

0.) Fits HLA

1.) Minimal overlap with self-peptides

2.) Preserved through genetic mutations

3.) Binds strongly to HLA

Vaccination

What is a ‘good’ viral peptide sequence?

0.) Fits HLA

1.) Minimal overlap with self-peptides

2.) Preserved through genetic mutations

3.) Binds strongly to HLA

Ideally: Fits all HLA (of type I or II)

Vaccination

What is a ‘good’ viral peptide sequence?

0.) Fits HLA

1.) Minimal overlap with self-peptides

2.) Preserved through genetic mutations

3.) Binds strongly to HLA

Ideally: No overlap with self-peptides

Vaccination

What is a ‘good’ viral peptide sequence?

0.) Fits HLA

1.) Minimal overlap with self-peptides

2.) Preserved through genetic mutations

3.) Binds strongly to HLA

Ideally: Sequence is perfectly conserved

Vaccination

What is a ‘good’ viral peptide sequence?

0.) Fits HLA

1.) Minimal overlap with self-peptides

2.) Preserved through genetic mutations

3.) Binds strongly to HLA

Ideally: Binds optimally to HLA

HIV1-B

HIV1-B

Total AA length of proteins ≃ 3000 AA

HIV1-B

Peptides considered from protein segments.

Considered within class 1 HLAs only.

Quantitative matrix of 9-mers.Parker, K. C., M. A. Bednarek, and J. E. Coligan. 1994. Scheme for ranking potential HLA-A2 binding peptides based on independent binding of individual peptide side-chains. J. Immunol. 152:163

1. SelfOf peptides bound by HLAs, which viral 9-mer peptides are not in self?

Self 9-mers bound by HLAsAAAAAAAI AAAAAAAAL AAAAAAAAV AAAAAAAGV

AAAAAAAHL AAAAAAAKM AAAAAAALV AAAAAAANI

AAAAAAANL AAAAAAAPV AAAAAAASL AAAAAAAVI

AAAAAAAVV AAAAAADKL AAAAAADKW AAAAAAFKL

AAAAAAGEL AAAAAAGGL AAAAAAGGV AAAAAAGKL

AAAAAAGQI AAAAAAGRV AAAAAAGSL AAAAAAIGI

AAAAAALAL AAAAAALCV AAAAAALDL AAAAAALTL

. . .

1. SelfOf peptides bound by HLAs, which viral 9-mer peptides are not in self?

Viral 9-mers bound by HLAsAACWWAGIK AACWWAGIK ADDTVLEEM AELELAENR

AETFYVDGA AETFYVDGA AETFYVDGA AETFYVDGA

AETGQETAY AETGQETAY AEVIPAETG AEVIPAETG

AFSPEVIPM AGDDCVASR AGERIVDII AGERIVDII

AGERIVDII AGERIVDII AGERIVDII AGIKQEFGI

AGIKQEFGI AGIKQEFGI AGIKQEFGI AGIRKVLFL

AGIRKVLFL AGIRKVLFL AGIRKVLFL AGIRKVLFL

. . .

1. SelfOf peptides bound by HLAs, which viral 9-mer peptides are not in self?

None!

No viral 9-mer peptides are in self.

1. SelfOf peptides bound by HLAs, which viral 9-mer peptides are not in self?

# Possible 9-mers:

20^9 = 512,000,000,000 ≃ 10^11# Human 9-mers:

= 2,981,644 = 10^6# Human / # Possible 9-mers = 10^-5No autoimmune symptoms.

2. ConservedWhich viral peptides sequences are preserved through genetic mutations?

2. ConservedWhich viral peptides sequences are preserved through genetic mutations? Alignment Program: ClustalX

v1.8

Selection of env Proteins, AA: 1 - 70

2. ConservedWhich viral peptides sequences are preserved through genetic mutations? Alignment Program: ClustalX

v1.8

Selection of env Proteins, AA: 100 - 160

2. ConservedWhich viral peptides sequences are preserved through genetic mutations? Alignment Program: ClustalX

v1.8

Selection of env Proteins, AA: 170 - 240

2. ConservedWhich viral peptides sequences are preserved through genetic mutations? Alignment Program: ClustalX

v1.8

Selection of env Proteins, AA: 800 -

2. ConservedWhich viral peptides sequences are preserved through genetic mutations?

Align protein sequences: Match conserved segments to each other

Virus 1: [A] [B] [C] [Y] [A] [B] [C] …

Virus 1’: [A] [B] [C] [A] [Y] [A] [B] [C] …

2. ConservedWhich viral peptides sequences are preserved through genetic mutations?

Align protein sequences: Match conserved segments to each other

Virus 1: [A] [B] [C] --- [Y] [A] [B] [C] …

Virus 1’: [A] [B] [C] [A] [Y] [A] [B] [C] …

2. ConservedWhich viral peptides sequences are preserved through genetic mutations? Alignment Program: ClustalX

v1.8

Selection of env Proteins, AA: 1 - 70

2. ConservedWhich viral peptides sequences are preserved through genetic mutations? Alignment Program: ClustalX

v1.8

Selection of env Proteins, AA: 100 - 160

2. ConservedWhich viral peptides sequences are preserved through genetic mutations? Alignment Program: ClustalX

v1.8

Selection of env Proteins, AA: 170 - 240

2. ConservedWhich viral peptides sequences are preserved through genetic mutations? Alignment Program: ClustalX

v1.8

Selection of env Proteins, AA: 800 -

2. ConservedWhich viral peptides sequences are preserved through genetic mutations?

Considering only those that are completely conservedTotal # sequences = 537

2. ConservedWhich viral peptides sequences are preserved through genetic mutations?

Considering only those that are completely conservedTotal # sequences > 8 AA = 76

1 : 177 2 : 93 3 : 71 4 : 50 5 : 28 6 : 18 7 : 14 8 : 10 9 : 6 10 : 3 11 : 9

12 : 3 13 : 3 14 : 3 15 : 5 16 : 3 17 : 1 18 : 2 19 : 2 20 : 3 22 : 1 23 : 2

24 : 1 25 : 4 26 : 3 29 : 1 30 : 4 34 : 1 37 : 1 38 : 1 40 : 1 41 : 1 43 : 1

47 : 1 48 : 2 49 : 1 51 : 1 52 : 1 57 : 1 59 : 1 60 : 1 72 : 1 87 : 1

2. ConservedWhich viral peptides sequences are preserved through genetic mutations?

Which of these conserved sequences make ‘good’ candidate peptides?

DDTVLEEHKAIGTTHLEG - conserved 19 AA sequenceDDTVLEEHKAIGTTHLEGDDTVLEEHKAIGTTHLEG

DDTVLEEHKAIGTTHLEG

DDTVLEEHKAIGTTHLEGDDTVLEEHKAIGTTHLEG

DDTVLEEHKAIGTTHLEGDDTVLEEHKAIGTTHLEGDDTVLEEHKAIGTTHLEGDDTVLEEHKAIGTTHLEG

peptides to be tested

DDTVLEEHKAIGTTHLEG

0. Fitting the HLA

0. Fitting the HLACan we fit all HLAs?

0. Fitting the HLACan we fit all HLAs?For certain proteins:

env, pol (1,2), gag, tat

0. Fitting the HLA # f S HLA

1 1 CSGKLICTT 4

2 2 CVKLTPLCV 10 1

3 1 DNWRSELYK 19

4 3 FLGAAGSTM 7 19 33

5 3 GAAGSTMGA 6 2 27

6 1 GCSGKLICT 10

7 1 GFLGAAGST 13

8 10 GIVQQQNNL 33 2 3 11 13 18 19 26 30 32

9 7 IVQQQNNLL 33 1 11 13 18 22 32

10 10 KLTPLCVTL 7 3 11 12 13 18 19 24 32 33

11 1 LGFLGAAGS 2

12 9 LTVWGIKQL 9 2 3 11 13 18 26 30 32

13 1 NVSTVQCTH 1

14 1 NWRSELYKY 13

15 2 RSELYKYKV 4 20

16 1 SGIVQQQNN 2

17 3 STVQCTHGI 3 2 27

18 1 VKLTPLCVT 26

19 1 WGCSGKLIC 5

20 1 WGIKQLQAR 16

21 2 WRSELYKYK 24

0. Fitting the HLACan we fit all HLAs?For certain proteins:

Optimal set of candidate sequences for a given protein?

env, pol (1,2), gag, tat

0. Fitting the HLACan we fit all HLAs?For certain proteins:

Optimal set of candidate sequences for a given protein?

Classical network algorithm : Min-cost-Max-flow

env, pol (1,2), gag, tat

0. Fitting the HLA # f S HLA Least :

1 1 CSGKLICTT 4 15 10 8 5 4 2

2 2 CVKLTPLCV 10 1

3 1 DNWRSELYK 19

4 3 FLGAAGSTM 7 19 33

5 3 GAAGSTMGA 6 2 27

6 1 GCSGKLICT 10

7 1 GFLGAAGST 13

8 10 GIVQQQNNL 33 2 3 11 13 18 19 26 30 32

9 7 IVQQQNNLL 33 1 11 13 18 22 32

10 10 KLTPLCVTL 7 3 11 12 13 18 19 24 32 33

11 1 LGFLGAAGS 2

12 9 LTVWGIKQL 9 2 3 11 13 18 26 30 32

13 1 NVSTVQCTH 1

14 1 NWRSELYKY 13

15 2 RSELYKYKV 4 20

16 1 SGIVQQQNN 2

17 3 STVQCTHGI 3 2 27

18 1 VKLTPLCVT 26

19 1 WGCSGKLIC 5

20 1 WGIKQLQAR 16

21 2 WRSELYKYK 24

0. Fitting the HLA # f S HLA Least :

1 1 CSGKLICTT 4 15 10 8 5 4 2

2 2 CVKLTPLCV 10 1

3 1 DNWRSELYK 19

4 3 FLGAAGSTM 7 19 33

5 3 GAAGSTMGA 6 2 27

6 1 GCSGKLICT 10

7 1 GFLGAAGST 13

8 10 GIVQQQNNL 33 2 3 11 13 18 19 26 30 32

9 7 IVQQQNNLL 33 1 11 13 18 22 32

10 10 KLTPLCVTL 7 3 11 12 13 18 19 24 32 33

11 1 LGFLGAAGS 2

12 9 LTVWGIKQL 9 2 3 11 13 18 26 30 32

13 1 NVSTVQCTH 1

14 1 NWRSELYKY 13

15 2 RSELYKYKV 4 20

16 1 SGIVQQQNN 2

17 3 STVQCTHGI 3 2 27

18 1 VKLTPLCVT 26

19 1 WGCSGKLIC 5

20 1 WGIKQLQAR 16

21 2 WRSELYKYK 24

0. Fitting the HLA # f S HLA Least :

1 1 CSGKLICTT 4 15 10 8 5 4 2

2 2 CVKLTPLCV 10 1

3 1 DNWRSELYK 19

4 3 FLGAAGSTM 7 19 33

5 3 GAAGSTMGA 6 2 27

6 1 GCSGKLICT 10

7 1 GFLGAAGST 13

8 10 GIVQQQNNL 33 2 3 11 13 18 19 26 30 32

9 7 IVQQQNNLL 33 1 11 13 18 22 32

10 10 KLTPLCVTL 7 3 11 12 13 18 19 24 32 33

11 1 LGFLGAAGS 2

12 9 LTVWGIKQL 9 2 3 11 13 18 26 30 32

13 1 NVSTVQCTH 1

14 1 NWRSELYKY 13

15 2 RSELYKYKV 4 20

16 1 SGIVQQQNN 2

17 3 STVQCTHGI 3 2 27

18 1 VKLTPLCVT 26

19 1 WGCSGKLIC 5

20 1 WGIKQLQAR 16

21 2 WRSELYKYK 24

0. Fitting the HLA # f S HLA Least :

1 1 CSGKLICTT 4 15 10 8 5 4 2

2 2 CVKLTPLCV 10 1

3 1 DNWRSELYK 19

4 3 FLGAAGSTM 7 19 33

5 3 GAAGSTMGA 6 2 27

6 1 GCSGKLICT 10

7 1 GFLGAAGST 13

8 10 GIVQQQNNL 33 2 3 11 13 18 19 26 30 32

9 7 IVQQQNNLL 33 1 11 13 18 22 32

10 10 KLTPLCVTL 7 3 11 12 13 18 19 24 32 33

11 1 LGFLGAAGS 2

12 9 LTVWGIKQL 9 2 3 11 13 18 26 30 32

13 1 NVSTVQCTH 1

14 1 NWRSELYKY 13

15 2 RSELYKYKV 4 20

16 1 SGIVQQQNN 2

17 3 STVQCTHGI 3 2 27

18 1 VKLTPLCVT 26

19 1 WGCSGKLIC 5

20 1 WGIKQLQAR 16

21 2 WRSELYKYK 24

0. Fitting the HLA # f S HLA Least :

1 1 CSGKLICTT 4 15 10 8 5 4 2

2 2 CVKLTPLCV 10 1

3 1 DNWRSELYK 19

4 3 FLGAAGSTM 7 19 33

5 3 GAAGSTMGA 6 2 27

6 1 GCSGKLICT 10

7 1 GFLGAAGST 13

8 10 GIVQQQNNL 33 2 3 11 13 18 19 26 30 32

9 7 IVQQQNNLL 33 1 11 13 18 22 32

10 10 KLTPLCVTL 7 3 11 12 13 18 19 24 32 33

11 1 LGFLGAAGS 2

12 9 LTVWGIKQL 9 2 3 11 13 18 26 30 32

13 1 NVSTVQCTH 1

14 1 NWRSELYKY 13

15 2 RSELYKYKV 4 20

16 1 SGIVQQQNN 2

17 3 STVQCTHGI 3 2 27

18 1 VKLTPLCVT 26

19 1 WGCSGKLIC 5

20 1 WGIKQLQAR 16

21 2 WRSELYKYK 24

0. Fitting the HLA # f S HLA Least :

1 1 CSGKLICTT 4 15 10 8 5 4 2

2 2 CVKLTPLCV 10 1

3 1 DNWRSELYK 19

4 3 FLGAAGSTM 7 19 33

5 3 GAAGSTMGA 6 2 27

6 1 GCSGKLICT 10

7 1 GFLGAAGST 13

8 10 GIVQQQNNL 33 2 3 11 13 18 19 26 30 32

9 7 IVQQQNNLL 33 1 11 13 18 22 32

10 10 KLTPLCVTL 7 3 11 12 13 18 19 24 32 33

11 1 LGFLGAAGS 2

12 9 LTVWGIKQL 9 2 3 11 13 18 26 30 32

13 1 NVSTVQCTH 1

14 1 NWRSELYKY 13

15 2 RSELYKYKV 4 20

16 1 SGIVQQQNN 2

17 3 STVQCTHGI 3 2 27

18 1 VKLTPLCVT 26

19 1 WGCSGKLIC 5

20 1 WGIKQLQAR 16

21 2 WRSELYKYK 24

0. Fitting the HLA # f S HLA Least :

1 1 CSGKLICTT 4 15 10 8 5 4 2

2 2 CVKLTPLCV 10 1

3 1 DNWRSELYK 19

4 3 FLGAAGSTM 7 19 33

5 3 GAAGSTMGA 6 2 27

6 1 GCSGKLICT 10

7 1 GFLGAAGST 13

8 10 GIVQQQNNL 33 2 3 11 13 18 19 26 30 32

9 7 IVQQQNNLL 33 1 11 13 18 22 32

10 10 KLTPLCVTL 7 3 11 12 13 18 19 24 32 33

11 1 LGFLGAAGS 2

12 9 LTVWGIKQL 9 2 3 11 13 18 26 30 32

13 1 NVSTVQCTH 1

14 1 NWRSELYKY 13

15 2 RSELYKYKV 4 20

16 1 SGIVQQQNN 2

17 3 STVQCTHGI 3 2 27

18 1 VKLTPLCVT 26

19 1 WGCSGKLIC 5

20 1 WGIKQLQAR 16

21 2 WRSELYKYK 24

Candidate sequences

CVKLTPLCV // FLGAAGSTM // GAAGSTMGA // GIVQQQNNL // KLTPLCVTL // RSELYKYKV

HIV1-B env Protein (all)

HIV1-B tat Protein (1,2,15,16,17,19,27)EPWKHPGSQ // GISYGRKKR

HIV1-B pol(1) Protein (all) 14

HIV1-B pol(2) Protein (all) 11

HIV1-B gag Protein (all but 15, 19, 21) 9

Implementation

“Sequence signals for generation of antigenic peptides by the proteasome: implications for proteasomal cleavage mechanism.”Altuvia Y, Margalit H

CVKLTPLCV // FLGAAGSTM // GAAGSTMGA // GIVQQQNNL // KLTPLCVTL // RSELYKYKV

// = Cleave signal.