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HLA MHCs are the gatekeepers of the immune system. 1.) LOCATE: Present peptides that may be viral. 2.) ACTIVATE: Activate immune defense mechanisms.

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Presentation on theme: "HLA MHCs are the gatekeepers of the immune system. 1.) LOCATE: Present peptides that may be viral. 2.) ACTIVATE: Activate immune defense mechanisms."— Presentation transcript:

1

2 HLA

3 MHCs are the gatekeepers of the immune system. 1.) LOCATE: Present peptides that may be viral. 2.) ACTIVATE: Activate immune defense mechanisms.

4 HLA Class 1 8-10 AA 13-25 AA Class 2 # ~80# ~40 ClosedOpen

5 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

6 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

7 What fits in an HLA?

8 Find out experimentally? # Class I HLA’s≃ 80

9 What fits in an HLA? Find out experimentally? # Class I HLA’s≃ 80 # Possible 9-mers: 20^9= 512,000,000,000 ≃ 10^11

10 What fits in an HLA? Calculate theoretically? Binding Motifs Quantitative Matrices Molecular Artificial Neural Network Hidden Markov Models

11 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?

12 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?

13 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?

14 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

15 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

16 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

17 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

18 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

19 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

20 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

21 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

22 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

23 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

24 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

25 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

26 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

27 What fits in an HLA? Quantitative Matrices: Calculate theoretically? If 0.081 > threshold, then ADCGTVMCE is bound by class I HLA A3.

28 Vaccination

29 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

30 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

31 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)

32 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

33 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

34 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

35 HIV1-B

36 Total AA length of proteins ≃ 3000 AA

37 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

38 1. Self Of peptides bound by HLAs, which viral 9-mer peptides are not in self? Self 9-mers bound by HLAs AAAAAAAIAAAAAAAALAAAAAAAAVAAAAAAAGV AAAAAAAHLAAAAAAAKMAAAAAAALVAAAAAAANI AAAAAAANLAAAAAAAPVAAAAAAASLAAAAAAAVI AAAAAAAVVAAAAAADKLAAAAAADKWAAAAAAFKL AAAAAAGELAAAAAAGGLAAAAAAGGVAAAAAAGKL AAAAAAGQIAAAAAAGRVAAAAAAGSLAAAAAAIGI AAAAAALALAAAAAALCVAAAAAALDLAAAAAALTL...

39 1. Self Of peptides bound by HLAs, which viral 9-mer peptides are not in self? Viral 9-mers bound by HLAs AACWWAGIKAACWWAGIKADDTVLEEMAELELAENR AETFYVDGAAETFYVDGAAETFYVDGAAETFYVDGA AETGQETAYAETGQETAYAEVIPAETGAEVIPAETG AFSPEVIPMAGDDCVASRAGERIVDIIAGERIVDII AGERIVDIIAGERIVDIIAGERIVDIIAGIKQEFGI AGIKQEFGIAGIKQEFGIAGIKQEFGIAGIRKVLFL AGIRKVLFLAGIRKVLFLAGIRKVLFLAGIRKVLFL...

40 1. Self Of peptides bound by HLAs, which viral 9-mer peptides are not in self? None! No viral 9-mer peptides are in self.

41 1. Self Of 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^-5 No autoimmune symptoms.

42 2. Conserved Which viral peptides sequences are preserved through genetic mutations?

43 2. Conserved Which viral peptides sequences are preserved through genetic mutations? Alignment Program: ClustalX v1.8 Selection of env Proteins, AA: 1 - 70

44 2. Conserved Which viral peptides sequences are preserved through genetic mutations? Alignment Program: ClustalX v1.8 Selection of env Proteins, AA: 100 - 160

45 2. Conserved Which viral peptides sequences are preserved through genetic mutations? Alignment Program: ClustalX v1.8 Selection of env Proteins, AA: 170 - 240

46 2. Conserved Which viral peptides sequences are preserved through genetic mutations? Alignment Program: ClustalX v1.8 Selection of env Proteins, AA: 800 -

47 2. Conserved Which 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] …

48 2. Conserved Which 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] …

49 2. Conserved Which viral peptides sequences are preserved through genetic mutations? Alignment Program: ClustalX v1.8 Selection of env Proteins, AA: 1 - 70

50 2. Conserved Which viral peptides sequences are preserved through genetic mutations? Alignment Program: ClustalX v1.8 Selection of env Proteins, AA: 100 - 160

51 2. Conserved Which viral peptides sequences are preserved through genetic mutations? Alignment Program: ClustalX v1.8 Selection of env Proteins, AA: 170 - 240

52 2. Conserved Which viral peptides sequences are preserved through genetic mutations? Alignment Program: ClustalX v1.8 Selection of env Proteins, AA: 800 -

53 2. Conserved Which viral peptides sequences are preserved through genetic mutations? Considering only those that are completely conserved Total # sequences = 537

54 2. Conserved Which viral peptides sequences are preserved through genetic mutations? Considering only those that are completely conserved Total # 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

55 2. Conserved Which viral peptides sequences are preserved through genetic mutations? Which of these conserved sequences make ‘good’ candidate peptides? DDTVLEEHKAIGTTHLEG - conserved 19 AA sequence DDTVLEEHKAIGTTHLEG peptides to be tested DDTVLEEHKAIGTTHLEG

56 0. Fitting the HLA

57 Can we fit all HLAs?

58 0. Fitting the HLA Can we fit all HLAs? For certain proteins: env, pol (1,2), gag, tat

59 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

60 0. Fitting the HLA Can we fit all HLAs? For certain proteins: Optimal set of candidate sequences for a given protein? env, pol (1,2), gag, tat

61 0. Fitting the HLA Can 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

62 0. Fitting the HLA # f S HLALeast : 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

63 0. Fitting the HLA # f S HLALeast : 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

64 0. Fitting the HLA # f S HLALeast : 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

65 0. Fitting the HLA # f S HLALeast : 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

66 0. Fitting the HLA # f S HLALeast : 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

67 0. Fitting the HLA # f S HLALeast : 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

68 0. Fitting the HLA # f S HLALeast : 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

69 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

70 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.


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