Skip to main content
SpringerLink
Log in

A computational docking study on the pH dependence of peptide binding to HLA-B27 sub-types differentially associated with ankylosing spondylitis

  • Published:
Journal of Computer-Aided Molecular Design Aims and scope Submit manuscript

Abstract

A single amino acid difference (Asp116His), having a key role in a pathogenesis pathway, distinguishes HLA-B*27:05 and HLA-B*27:09 sub-types as associated and non-associated with ankylosing spondylitis, respectively. In this study, molecular docking simulations were carried out with the aim of comprehending the differences in the binding behavior of both alleles at varying pH conditions. A library of modeled peptides was formed upon single point mutations aiming to address the effect of 20 naturally occurring amino acids at the binding core peptide positions. For both alleles, computational docking was applied using Autodock 4.2. Obtained free energies of binding (FEB) were compared within the peptide library and between the alleles at varying pH conditions. The amino acid preferences of each position were studied enlightening the role of each on binding. The preferred amino acids for each position of pVIPR were found to be harmonious with experimental studies. Our results indicate that, as the pH is lowered, the capacity of HLA-B*27:05 to bind peptides in the library is largely lost. Hydrogen bonding analysis suggests that the interaction between the main anchor positions of pVIPR and their respective binding pocket residues are affected from the pH the most, causing an overall shift in the FEB profiles.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Abbas AK, Lichtman AH, Pillai S (2012) Cellular and molecular immunology, 7th edn. Elsevier/Saunders, Philadelphia

    Google Scholar 

  2. Hulpke S, Tampé R (2013) The MHC I loading complex: a multitasking machinery in adaptive immunity. Trends Biochem Sci 38:412–420. doi:10.1016/j.tibs.2013.06.003

    Article  CAS  Google Scholar 

  3. Bevan MJ (1976) Cross-priming for a secondary cytotoxic response to minor H antigens with H-2 congenic cells which do not cross-react in the cytotoxic assay. J Exp Med 143:1283–1288. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2190184/

  4. Rock KL, Gamble S, Rothstein L (1990) Presentation of exogenous antigen with class I major histocompatibility complex molecules. Science 249(4971):918–921

    Article  CAS  Google Scholar 

  5. Heath WR, Carbone FR (2001) Cross-presentation, dendritic cells, tolerance and immunity. Annu Rev Immunol 19:47–64. doi:10.1146/annurev.immunol.19.1.47

    Article  CAS  Google Scholar 

  6. Sigal LJ, Crotty S, Andino R, Rock KL (1999) Cytotoxic T-cell immunity to virus-infected non-haematopoietic cells requires presentation of exogenous antigen. Nature 398(6722):77–80. doi:10.1038/18038

    Article  CAS  Google Scholar 

  7. Rock KL, Shen L (2005) Cross-presentation: underlying mechanisms and role in immune surveillance. Immunol Rev 207:166–183. doi:10.1111/j.0105-2896.2005.00301.x

    Article  CAS  Google Scholar 

  8. Di Pucchio T, Chatterjee B, Smed-Sörensen A, Clayton S, Palazzo A, Montes M, Xue Y, Mellman I, Banchereau J, Connolly JE (2008) Direct proteasome-independent cross-presentation of viral antigen by plasmacytoid dendritic cells on major histocompatibility complex class I. Nat Immunol 9:551–557. doi:10.1038/ni.1602

    Article  Google Scholar 

  9. Geisow MJ, Evans WH (1984) pH in the endosome. Measurements during pinocytosis and receptor-mediated endocytosis. Exp Cell Res 150(1):36–46. http://www.ncbi.nlm.nih.gov/pubmed/6198190

  10. Rötzschke O, Lau JM, Hofstätter M, Falk K, Strominger JL (2002) A pH-sensitive histidine residue as control element for ligand release from HLA-DR molecules. Proc Natl Acad Sci USA 99:16946–16950. doi:10.1073/pnas.212643999

    Article  Google Scholar 

  11. Deutsch C, Taylor JS, Wilson DF (1982) Regulation of intracellular pH by human peripheral blood lymphocytes as measured by 19F NMR. Proc Natl Acad Sci USA 79(24):7944–7948. http://www.ncbi.nlm.nih.gov/pubmed/6961462

  12. Reich Z, Altman JD, Boniface JJ, Lyons DS, Kozono H, Ogg G, Morgan C, Davis MM (1997) Stability of empty and peptide-loaded class II major histocompatibility complex molecules at neutral and endosomal pH: comparison to class I proteins. Proc Natl Acad Sci USA 94(6):2495–2500. http://www.ncbi.nlm.nih.gov/pubmed/9122223

  13. Amigorena S, Savina A (2010) Intracellular mechanisms of antigen cross presentation in dendritic cells. Curr Opin Immunol 22:109–117. doi:10.1016/j.coi.2010.01.022

    Article  CAS  Google Scholar 

  14. Delamarre L, Pack M, Chang H, Mellman I, Trombetta ES (2005) Differential lysosomal proteolysis in antigen-presenting cells determines antigen fate. Science (New York, NY) 307:1630–1634. doi:10.1126/science.1108003

    Article  CAS  Google Scholar 

  15. Mantegazza AR, Savina A, Vermeulen M, Pérez L, Geffner J, Hermine O, Rosenzweig SD, Faure F, Amigorena S (2008) NADPH oxidase controls phagosomal pH and antigen cross-presentation in human dendritic cells. Blood 112:4712–4722. doi:10.1182/blood-2008-01-134791

    Article  CAS  Google Scholar 

  16. Savina A, Jancic C, Hugues S, Guermonprez P, Vargas P, Moura IC, Lennon-Duménil A-M, Seabra MC, Raposo G, Amigorena S (2006) NOX2 controls phagosomal pH to regulate antigen processing during crosspresentation by dendritic cells. Cell 126:205–218. doi:10.1016/j.cell.2006.05.035

    Article  CAS  Google Scholar 

  17. Gromme M, Uytdehaag FG, Janssen H, Calafat J, van Binnendijk RS, Kenter MJ, Tulp A, Verwoerd D, Neefjes J (1999) Recycling MHC class I molecules and endosomal peptide loading. Proc Natl Acad Sci USA 96(18):10326–10331. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC17887/

  18. Stryhn A, Pedersen LO, Romme T, Olsen AC, Nissen MH, Thorpe CJ, Buus S (1996) pH dependence of MHC class I-restricted peptide presentation. J Immunol (Baltimore, Md: 1950) 156:4191–4197. http://www.jimmunol.org/content/156/11/4191.full.pdf

  19. Ma W, Van den Eynde BJ (2014) Endosomal compartment: also a dock for MHC class I peptide loading. Eur J Immunol 44:650–653. doi:10.1002/eji.201444470

    Article  CAS  Google Scholar 

  20. Wälchli S, Kumari S, Fallang L-E, Sand KMK, Yang W, Landsverk OJB, Bakke O, Olweus J, Gregers TF (2014) Invariant chain as a vehicle to load antigenic peptides on human MHC class I for cytotoxic T-cell activation. Eur J Immunol 44:774–784. doi:10.1002/eji.201343671

    Article  Google Scholar 

  21. Duan F, Srivastava PK (2012) An invariant road to cross-presentation. Nat Immunol 13:207–208. doi:10.1038/ni.2235

    Article  CAS  Google Scholar 

  22. Sorrentino R, Bockmann RA, Fiorillo MT (2014) HLA-B27 and antigen presentation: at the crossroads between immune defense and autoimmunity. Mol Immunol 57(1):22–27. doi:10.1016/j.molimm.2013.06.017

    Article  CAS  Google Scholar 

  23. Bettosini F, Fiorillo MT, Magnacca A, Leone L, Torrisi MR, Sorrentino R (2005) The C terminus of the nucleoprotein of influenza A virus delivers antigens transduced by Tat to the trans-golgi network and promotes an efficient presentation through HLA class I. J Virol 79:15537–15546. doi:10.1128/JVI.79.24.15537-15546.2005

    Article  CAS  Google Scholar 

  24. Magnacca A, Persiconi I, Nurzia E, Caristi S, Meloni F, Barnaba V, Paladini F, Raimondo D, Fiorillo MT, Sorrentino R (2012) Characterization of a proteasome and TAP-independent presentation of intracellular epitopes by HLA-B27 molecules. J Biol Chem 287:30358–30367. doi:10.1074/jbc.M112.384339

    Article  CAS  Google Scholar 

  25. Leonhardt RM, Fiegl D, Rufer E, Karger A, Bettin B, Knittler MR (2010) Post-endoplasmic reticulum rescue of unstable MHC class I requires proprotein convertase PC7. J Immunol 184(6):2985–2998. doi:10.4049/jimmunol.0900308

    Article  CAS  Google Scholar 

  26. Ramos M, Lopez de Castro JA (2002) HLA-B27 and the pathogenesis of spondyloarthritis. Tissue Antigens 60(3):191–205. http://www.ncbi.nlm.nih.gov/pubmed/12445302

  27. Ziegler A, Loll B, Misselwitz R, Uchanska-Ziegler B (2009) Implications of structural and thermodynamic studies of HLA-B27 subtypes exhibiting differential association with ankylosing spondylitis. Adv Exp Med Biol 649:177–195. http://www.ncbi.nlm.nih.gov/pubmed/19731629

  28. Uchanska-Ziegler B, Loll B, Fabian H, Hee CS, Saenger W, Ziegler A (2012) HLA class I-associated diseases with a suspected autoimmune etiology: HLA-B27 subtypes as a model system. Eur J Cell Biol 91(4):274–286. doi:10.1016/j.ejcb.2011.03.003

    Article  CAS  Google Scholar 

  29. Brewerton DA, Hart FD, Nicholls A, Caffrey M, James DC, Sturrock RD (1973) Ankylosing spondylitis and HL-A 27. Lancet 1(7809):904–907. http://www.ncbi.nlm.nih.gov/pubmed/4123836

  30. Ohno S, Ohguchi M, Hirose S, Matsuda H, Wakisaka A, Aizawa M (1982) Close association of HLA-Bw51 with Behcet’s disease. Arch Ophthalmol 100(9):1455–1458. http://www.ncbi.nlm.nih.gov/pubmed/6956266

  31. Lafuente EM, Reche PA (2009) Prediction of MHC-peptide binding: a systematic and comprehensive overview. Curr Pharm Des 15(28):3209–3220. http://www.ncbi.nlm.nih.gov/pubmed/19860671

  32. Tong JC, Tan TW, Ranganathan S (2007) Methods and protocols for prediction of immunogenic epitopes. Brief Bioinform 8(2):96–108. doi:10.1093/bib/bbl038

    Article  CAS  Google Scholar 

  33. Liao WW, Arthur JW (2011) Predicting peptide binding to major histocompatibility complex molecules. Autoimmun Rev 10(8):469–473. doi:10.1016/j.autrev.2011.02.003

    Article  CAS  Google Scholar 

  34. Lin HH, Ray S, Tongchusak S, Reinherz EL, Brusic V (2008) Evaluation of MHC class I peptide binding prediction servers: applications for vaccine research. BMC Immunol 9:8. doi:10.1186/1471-2172-9-8

    Article  Google Scholar 

  35. Peters B, Bui HH, Frankild S, Nielson M, Lundegaard C, Kostem E, Basch D, Lamberth K, Harndahl M, Fleri W, Wilson SS, Sidney J, Lund O, Buus S, Sette A (2006) A community resource benchmarking predictions of peptide binding to MHC-I molecules. PLoS Comput Biol 2(6):e65. doi:10.1371/journal.pcbi.0020065

    Article  Google Scholar 

  36. Berman H, Henrick K, Nakamura H (2003) Announcing the worldwide Protein Data Bank. Nat Struct Biol 10(12):980. doi:10.1038/Nsb1203-980

    Article  CAS  Google Scholar 

  37. Patronov A, Dimitrov I, Flower DR, Doytchinova I (2012) Peptide binding to HLA-DP proteins at pH 5.0 and pH 7.0: a quantitative molecular docking study. BMC Struct Biol 12:20. doi:10.1186/1472-6807-12-20

    Article  CAS  Google Scholar 

  38. Damato M, Fiorillo MT, Carcassi C, Mathieu A, Zuccarelli A, Bitti PP, Tosi R, Sorrentino R (1995) Relevance of residue-116 of Hla-B27 in determining susceptibility to ankylosing-spondylitis. Eur J Immunol 25(11):3199–3201. doi:10.1002/eji.1830251133

    Article  CAS  Google Scholar 

  39. Khan MA (2002) Update on spondyloarthropathies. Ann Intern Med 136(12):896–907. http://www.ncbi.nlm.nih.gov/pubmed/12069564

  40. Falk K, Rotzschke O, Stevanovic S, Jung G, Rammensee HG (1991) Allele-specific motifs revealed by sequencing of self-peptides eluted from MHC molecules. Nature 351(6324):290–296. doi:10.1038/351290a0

    Article  CAS  Google Scholar 

  41. Pohlmann T, Bockmann RA, Grubmuller H, Uchanska-Ziegler B, Ziegler A, Alexiev U (2004) Differential peptide dynamics is linked to major histocompatibility complex polymorphism. J Biol Chem 279(27):28197–28201. doi:10.1074/jbc.C400128200

    Article  Google Scholar 

  42. Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ (2009) AutoDock4 and AutoDockTools4: automated docking with selective receptor flexibility. J Comput Chem 30(16):2785–2791. doi:10.1002/Jcc.21256

    Article  CAS  Google Scholar 

  43. Hulsmeyer M, Fiorillo MT, Bettosini F, Sorrentino R, Saenger W, Ziegler A, Uchanska-Ziegler B (2004) Dual, HLA-B27 subtype-dependent conformation of a self-peptide. J Exp Med 199(2):271–281. doi:10.1084/jem.20031690

    Article  Google Scholar 

  44. The PyMOL Molecular Graphics System Vrp, Schrödinger, LLC

  45. Sondergaard CR, Olsson MHM, Rostkowski M, Jensen JH (2011) Improved treatment of ligands and coupling effects in empirical calculation and rationalization of pK(a) values. J Chem Theory Comput 7(7):2284–2295. doi:10.1021/Ct200133y

    Article  CAS  Google Scholar 

  46. Patronov A, Dimitrov I, Flower DR, Doytchinova I (2011) Peptide binding prediction for the human class II MHC allele HLA-DP2: a molecular docking approach. BMC Struct Biol 11:32. doi:10.1186/1472-6807-11-32

    Article  CAS  Google Scholar 

  47. Vita R, Overton JA, Greenbaum JA, Ponomarenko J, Clark JD, Cantrell JR, Wheeler DK, Gabbard JL, Hix D, Sette A, Peters B (2015) The immune epitope database (IEDB) 3.0. Nucleic Acids Res 43(Database issue):D405-412. doi:10.1093/nar/gku938

  48. Schittenhelm RB, Sian TCCLK, Wilmann PG, Dudek NL, Purcell AW (2015) Revisiting the arthritogenic peptide theory: quantitative not qualitative changes in the peptide repertoire of HLA-B27 allotypes. Arthritis Rheumatol (Hoboken, NJ) 67:702–713. doi:10.1002/art.38963

  49. Durrant JD, McCammon JA (2011) HBonanza: a computer algorithm for molecular-dynamics-trajectory hydrogen-bond analysis. J Mol Graph Model 31:5–9. doi:10.1016/j.jmgm.2011.07.008

    Article  CAS  Google Scholar 

  50. McDonald IK, Thornton JM (1994) Satisfying hydrogen bonding potential in proteins. J Mol Biol 238(5):777–793. doi:10.1006/jmbi.1994.1334

    Article  CAS  Google Scholar 

  51. Narzi D, Winkler K, Saidowsky J, Misselwitz R, Ziegler A, Bockmann RA, Alexiev U (2008) Molecular determinants of major histocompatibility complex class I complex stability—shaping antigenic features through short and long range electrostatic interactions. J Biol Chem 283(34):23093–23103. doi:10.1074/jbc.M710234200

    Article  CAS  Google Scholar 

  52. Wereszczynski J, McCammon JA (2012) Statistical mechanics and molecular dynamics in evaluating thermodynamic properties of biomolecular recognition. Q Rev Biophys 45(1):1–25. doi:10.1017/S0033583511000096

    Article  CAS  Google Scholar 

  53. Huey R, Morris GM, Olson AJ, Goodsell DS (2007) A semiempirical free energy force field with charge-based desolvation. J Comput Chem 28(6):1145–1152. doi:10.1002/jcc.20634

    Article  CAS  Google Scholar 

  54. Fabian H, Huser H, Narzi D, Misselwitz R, Loll B, Ziegler A, Bockmann RA, Uchanska-Ziegler B, Naumann D (2008) HLA-B27 subtypes differentially associated with disease exhibit conformational differences in solution. J Mol Biol 376(3):798–810. doi:10.1016/j.jmb.2007.12.009

    Article  CAS  Google Scholar 

  55. de Castro JAL (2007) HLA-B27 and the pathogenesis of spondyloarthropathies. Immunol Lett 108(1):27–33. doi:10.1016/j.imlet.2006.10.004

    Article  Google Scholar 

  56. Fiorillo MT, Maragno M, Butler R, Dupuis ML, Sorrentino R (2000) CD8(+) T-cell autoreactivity to an HLA-B27-restricted self-epitope correlates with ankylosing spondylitis. J Clin Investig 106(1):47–53. doi:10.1172/JCI9295

    Article  CAS  Google Scholar 

  57. Fiorillo MT, Ruckert C, Hulsmeyer M, Sorrentino R, Saenger W, Ziegler A, Uchanska-Ziegler B (2005) Allele-dependent similarity between viral and self-peptide presentation by HLA-B27 subtypes. J Biol Chem 280(4):2962–2971. doi:10.1074/jbc.M410807200

    Article  CAS  Google Scholar 

  58. Madden DR, Gorga JC, Strominger JL, Wiley DC (1991) The structure of HLA-B27 reveals nonamer self-peptides bound in an extended conformation. Nature 353(6342):321–325. doi:10.1038/353321a0

    Article  CAS  Google Scholar 

  59. Fukazawa T, Wang J, Huang F, Wen J, Tyan D, Williams KM, Raybourne RB, Yu DT (1994) Testing the importance of each residue in a HLA-B27-binding peptide using monoclonal antibodies. J Immunol 152(3):1190–1196. http://www.ncbi.nlm.nih.gov/pubmed/8301123

  60. Khan MA, Ball EJ (2002) Genetic aspects of ankylosing spondylitis. Best Pract Res Clin Rheumatol 16(4):675–690

    Article  CAS  Google Scholar 

Download references

Acknowledgments

This work was supported by TUBITAK under Grant 113M293.

Author information

Authors and Affiliations

  1. Faculty of Engineering, Department of Bioengineering, Goztepe Campus, MC-373, Marmara University, 34722, Goztepe, Istanbul, Turkey

    Onur Serçinoğlu, Gülin Özcan, Zeynep Kutlu Kabaş & Pemra Ozbek

Authors
  1. Onur Serçinoğlu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Gülin Özcan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zeynep Kutlu Kabaş
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Pemra Ozbek
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Pemra Ozbek.

Ethics declarations

Conflict of interest

No conflicting financial interests exist.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 727 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Serçinoğlu, O., Özcan, G., Kabaş, Z.K. et al. A computational docking study on the pH dependence of peptide binding to HLA-B27 sub-types differentially associated with ankylosing spondylitis. J Comput Aided Mol Des 30, 569–581 (2016). https://doi.org/10.1007/s10822-016-9934-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10822-016-9934-z

Keywords

Search

Navigation