1. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU B cell epitopes and predictions Pernille Haste Andersen, Ph.d. student Immunological Bioinformatics CBS, DTU

2. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Outline What is a B-cell epitope? How can you predict B-cell epitopes? B-cell epitopes in rational vaccine design. –Case story: Using B-cell epitopes in rational vaccine design against HIV.

3. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU What is a B-cell epitope? B-cell epitopes Accessible structural feature of a pathogen molecule. Antibodies are developed to bind the epitope specifically using the complementary determining regions (CDRs). Antibody Fab fragment

4. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU The binding interactions  Salt bridges  Hydrogen bonds  Hydrophobic interactions  Van der Waals forces Binding strength

5. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU B-cell epitopes are dynamic  Many of the charged groups and hydrogen bonding partners are present on highly flexible amino acid side chains.  Most crystal structures of epitopes and antibodies in free and complexed forms have shown conformational rearrangements upon binding.  “Induced fit” model of interactions.

6. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU B-cell epitope classification Linear epitopes One segment of the amino acid chain Discontinuous epitope (with linear determinant) Discontinuous epitope Several small segments brought into proximity by the protein fold B-cell epitope – structural feature of a molecule or pathogen, accessible and recognizable by B-cells

7. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Binding of a discontinuous epitope Guinea Fowl Lysozyme KVFGRCELAAAMKRHGLDNYRGYSLGNWVCAAKFESNFNSQNRNTDGS DYGVLNSRWWCNDGRTPGSRNLCNIPCSALQSSDITATANCAKKIVSDG GMNAWVAWRKCKGTDVRVWIKGCRL Antibody FAB fragment complexed with Guinea Fowl Lysozyme (1FBI). Black: Light chain, Blue: Heavy chain, Yellow: Residues with atoms distanced < 5Å from FAB antibody fragments.

8. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU B-cell epitope annotation Linear epitopes: –Chop sequence into small pieces and measure binding to antibody Discontinuous epitopes: –Measure binding of whole protein to antibody The best annotation method : X-ray crystal structure of the antibody-epitope complex

9. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU B-cell epitope data bases Databases: AntiJen, IEDB, BciPep, Los Alamos HIV database, Protein Data Bank Large amount of data available for linear epitopes Few data available for discontinuous

10. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU B cell epitope prediction

11. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Sequence-based methods for prediction of linear epitopes  Protein hydrophobicity – hydrophilicity algorithms Parker, Fauchere, Janin, Kyte and Doolittle, Manavalan Sweet and Eisenberg, Goldman, Engelman and Steitz (GES), von Heijne  Protein flexibility prediction algorithm Karplus and Schulz  Protein secondary structure prediction algorithms GOR II method (Garnier and Robson), Chou and Fasman, Pellequer  Protein “antigenicity” prediction : Hopp and Woods, Welling TSQDLSVFPLASCCKDNIASTSVTLGCLVTG YLPMSTTVTWDTGSLNKNVTTFPTTFHETY GLHSIVSQVTASGKWAKQRFTCSVAHAES TAINKTFSACALNFIPPTVKLFHSSCNPVGD THTTIQLLCLISGYVPGDMEVIWLVDGQKA TNIFPYTAPGTKEGNVTSTHSELNITQGEW VSQKTYTCQVTYQGFTFKDEARKCSESDPR GVTSYLSPPSPL

12. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Propensity scales: The principle The Parker hydrophilicity scale Derived from experimental data D2.46 E1.86 N1.64 S1.50 Q1.37 G1.28 K1.26 T1.15 R0.87 P0.30 H0.30 C0.11 A0.03 Y-0.78 V-1.27 M-1.41 I-2.45 F-2.78 L-2.87 W-3.00 Hydrophilicity

13. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Propensity scales: The principle ….LISTFVDEKRPGSDIVEDLILKDENKTTVI…. (-2.78 + -1.27 + 2.46 +1.86 + 1.26 + 0.87 + 0.3)/7 = 0.39 Prediction scores: 0.38 0.1 0.6 0.9 1.0 1.2 2.6 1.0 0.9 0.5 -0.5 Epitope

14. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Evaluation of performance A Receiver Operator Curve (ROC) is useful for finding a good threshold and rank methods

15. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Turn prediction and B-cell epitopes Pellequer found that 50% of the epitopes in a data set of 11 proteins were located in turns Turn propensity scales for each position in the turn were used for epitope prediction. Pellequer et al., Immunology letters, 1993 1 2 3 4

16. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Blythe and Flower 2005 Extensive evaluation of propensity scales for epitope prediction Conclusion: –Basically all the classical scales perform close to random! –Other methods must be used for epitope prediction

17. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU BepiPred: CBS in-house tool Parker hydrophilicity scale Hidden Markow model Markow model based on linear epitopes extracted from the AntiJen database Combination of the Parker prediction scores and Markow model leads to prediction score Tested on the Pellequer dataset and epitopes in the HIV Los Alamos database

18. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Hidden Markow Model A C D ………… G S T V W Pos 17.28 Pos 29.39 Pos 3 0.3 Pos 4 5.2 Pos 5 7.9 ….LISTFVDEKRPGSDIVEDLILKDENKTTVI…. 2.46+1.86+1.26+0.87+0.3 = 6.75 Prediction value

19. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU ROC evaluation Evaluation on HIV Los Alamos data set

20. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU BepiPred performance Pellequer data set: –LevittAROC = 0.66 –ParkerAROC = 0.65 –BepiPredAROC = 0.68 HIV Los Alamos data set –LevittAROC = 0.57 –ParkerAROC = 0.59 –BepiPredAROC = 0.60

21. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU BepiPred BepiPred conclusion: –On both of the evaluation data sets, Bepipred was shown to perform better –Still the AROC value is low compared to T-cell epitope prediction tools! –Bepipred is available as a webserver: www.cbs.dtu.dk/services/BepiPred

22. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Prediction of linear epitopes Con only ~10% of epitopes can be classified as “linear” weakly immunogenic in most cases most epitope peptides do not provide antigen- neutralizing immunity in many cases represent hypervariable regions Pro easily predicted computationally easily identified experimentally immunodominant epitopes in many cases do not need 3D structural information easy to produce and check binding activity experimentally

23. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Sequence based prediction methods  Linear methods for prediction of B cell epitopes have low performances  The problem is analogous to the problems of representing the surface of the earth on a two-dimensional map  Reduction of the dimensions leads to distortions of scales, directions, distances  The world of B-cell epitopes is 3 dimensional and therefore more sophisticated methods must be developed Regenmortel 1996, Meth. of Enzym. 9.

24. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU So what is more sophisticated? Use of the three dimensional structure of the pathogen protein Analyze the structure to find surface exposed regions Additional use of information about conformational changes, glycosylation and trans-membrane helices

25. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU How can we get information about the three-dimensional structure? Structural determination X-ray crystallography NMR spectroscopy Both methods are time consuming and not easily done in a larger scale Structure prediction Homology modeling Fold recognition Less time consuming, but there is a possibility of incorrect predictions, specially in loop regions

26. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Protein structure prediction methods Homology/comparative modeling >25% sequence identity (seq 2 seq alignment) Fold-recognition/threading <25% sequence identity (Psi-blast search/ seq2str alignment) Ab initio structure prediction 0% sequence identity

27. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Annotation of protein surface Look at the surface of your protein Analyse for turns and loops Analyse for amino acid composition Find exposed Bepipred epitopes

28. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Q: What can antibodies recognize in a protein? A: Everything accessible to a 10 Å probe on a protein surface Novotny J. A static accessibility model of protein antigenicity. Int Rev Immunol 1987 Jul;2(4):379-89 probe Antibody Fab fragment Protrusion index

29. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Use the CEP server Conformational epitope server http://202.41.70.74:8080/cgi- bin/cep.pl Uses protein structure as input Finds stretches in sequences which are surface exposed

30. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Use the DiscoTope server CBS server for prediction of discontinuous epitopes –http://www.cbs.dtu.dk/services/DiscoTope/ Uses protein structure as input Combines propensity scale values of amino acids in discontinuous epitopes with surface exposure

31. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU

33. Malaria protein AMA1. Green: Predicted epitopes Black: Experimental epitopes

34. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Rational vaccine design >PATHOGEN PROTEIN KVFGRCELAAAMKRHGLDNYRG YSLGNWVCAAKFESNF Rational Vaccine Design

35. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Rational B-cell epitope design Protein target choice Structural analysis of antigen Known structure or homology model Precise domain structure Physical annotation (flexibility, electrostatics, hydrophobicity) Functional annotation (sequence variations, active sites, binding sites, glycosylation sites, etc.) Known 3D structure Model

36. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Rational B-cell epitope design Surface accessibility Protrusion index Conserved sequence Glycosylation status Protein target choice Structural annotation Epitope prediction and ranking

37. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Rational B-cell epitope design Protein target choice Structural annotation Epitope prediction and ranking Optimal Epitope presentation Fold minimization, or Design of structural mimics Choice of carrier (conjugates, DNA plasmids, virus like particles) Multiple chain protein engineering

38. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Multi-epitope protein design Rational optimization of epitope-VLP chimeric proteins: Design a library of possible linkers (<10 aa) Perform global energy optimization in VLP (virus-like particle) context Rank according to estimated energy strain B-cell epitope T-cell epitope

39. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Case story Using B-cell epitopes in the rational vaccine design against HIV The gp120-CD4 epitope

40. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU HIV gp120-CD4 epitope Binding of CD4 receptor Conformational changes in gp120 Opens chemokine- receptor binding site New highly conserved epitopes Kwong et al.(1998) Nature 393, 648-658

41. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Conformational changes in gp120 SIV gp120 no ligands Human gp120 complex with CD4 and 17b antibody Chen et al. Nature 2005 Kwong et al. Nature 1998

42. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU HIV gp120-CD4 epitope Elicit broadly cross- reactive neutralizing antibodies in rhesus macaques. This conjugate is too large(~400 aa) and still contains a number of irrelevant loops Fouts et al. (2000) Journal ofVirology, 74, 11427-11436 Fouts et al. (2002) Proc Natl Acad Sci U S A. 99, 11842-7. Efforts to design a epitope fusion protein

43. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU HIV gp120-CD4 epitope reduce to minimal stable fold (iterative) find alternative scaffold to present epitope (miniprotein mimic) Martin & Vita, Current Prot. An Pept. Science, 1: 403-430. Vita et al.(1999) PNAS 96:13091-6 Further optimization of the epitope:

44. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Conclusions Rational vaccines can be designed to induce strong and epitope-specific B-cell responses Selection of protective B-cell epitopes involves structural, functional and immunogenic analysis of the pathogenic proteins When you can: Use protein structure for prediction Structural modeling tools are helpful in prediction of epitopes, design of epitope mimics and optimal epitope presentation