1 / 70

HLA

HLA. HLA. MHCs are the gatekeepers of the immune system. 1.) LOCATE: Present peptides that may be viral. 2.) ACTIVATE: Activate immune defense mechanisms. HLA. Class 1. Class 2. 8-10 AA 13-25 AA. # ~80 # ~40. Closed Open. HLA.

tryna
Download Presentation

HLA

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. HLA

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

  3. HLA Class 1 Class 2 8-10 AA 13-25 AA # ~80 # ~40 Closed Open

  4. 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

  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. What fits in an HLA?

  7. What fits in an HLA? Find out experimentally? # Class I HLA’s ≃ 80

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

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

  10. What fits in an HLA? Calculate theoretically? Binding Motifs: Hypothesis: HLA binding entirely determined by a few AA (1-3) on the peptide. Approach: Check peptide for anchor residue.

  11. What fits in an HLA? Calculate theoretically? 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]

  12. What fits in an HLA? Calculate theoretically? 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.

  13. What fits in an HLA? Calculate theoretically? Quantitative Matrices: 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

  14. What fits in an HLA? Calculate theoretically? Quantitative Matrices: ADCGTVMCE 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? Calculate theoretically? Quantitative Matrices: ADCGTVMCE 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

  16. What fits in an HLA? Calculate theoretically? Quantitative Matrices: ADCGTVMCE 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

  17. What fits in an HLA? Calculate theoretically? Quantitative Matrices: ADCGTVMCE 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

  18. What fits in an HLA? Calculate theoretically? Quantitative Matrices: ADCGTVMCE 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

  19. What fits in an HLA? Calculate theoretically? Quantitative Matrices: ADCGTVMCE 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

  20. What fits in an HLA? Calculate theoretically? Quantitative Matrices: ADCGTVMCE 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

  21. What fits in an HLA? Calculate theoretically? Quantitative Matrices: ADCGTVMCE 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

  22. What fits in an HLA? Calculate theoretically? Quantitative Matrices: ADCGTVMCE 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

  23. What fits in an HLA? Calculate theoretically? Quantitative Matrices: ADCGTVMCE 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

  24. What fits in an HLA? Calculate theoretically? Quantitative Matrices: ADCGTVMCE 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

  25. What fits in an HLA? Calculate theoretically? Quantitative Matrices: 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 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

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

  27. Vaccination

  28. 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

  29. 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

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

  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: No overlap with self-peptides

  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: Sequence is perfectly conserved

  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: Binds optimally to HLA

  34. HIV1-B

  35. HIV1-B Total AA length of proteins ≃ 3000 AA

  36. 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

  37. 1. Self Of peptides bound by HLAs, which viral 9-mer peptides are not in self? Self 9-mers bound by HLAs AAAAAAAI 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 . . .

  38. 1. Self Of peptides bound by HLAs, which viral 9-mer peptides are not in self? Viral 9-mers bound by HLAs AACWWAGIK 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 . . .

  39. 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.

  40. 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.

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

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

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

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

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

  46. 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] …

  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? Alignment Program: ClustalX v1.8 Selection of env Proteins, AA: 1 - 70

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

More Related