In silico prediction of linear B-cell epitopes on proteins

Methods in Molecular Biology

Volumn 1484, Issue , 2017, Pages 255-264

  El Manzalawy, Yasser ^a   Dobbs, Drena ^b   Honavar, Vasant G ^a  

^a PENNSYLVANIA STATE UNIVERSITY   (United States)

^b IOWA STATE UNIVERSITY   (United States)

Author keywords

Antibody protein interaction; B cell epitope prediction; Epitope mapping; Epitope prediction; Linear B cell epitope prediction

Indexed keywords

AMINO ACID; B LYMPHOCYTE ANTIGEN; ANTIBODY; ANTIGEN; EPITOPE; PROTEIN;

AMINO ACID SEQUENCE; ANTIBODY COMBINING SITE; ANTIBODY PRODUCTION; COMPUTER MODEL; MOLECULAR RECOGNITION; PROTEIN INTERACTION; PROTEIN STRUCTURE; B LYMPHOCYTE; BIOLOGY; CHEMISTRY; COMPUTER SIMULATION; EPITOPE MAPPING; GENETICS; IMMUNOLOGY; PROCEDURES;

AMINO ACID SEQUENCE; ANTIBODIES; ANTIGENS; B-LYMPHOCYTES; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; EPITOPE MAPPING; EPITOPES; PROTEINS;

EID: 84994310731     PISSN: 10643745     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-1-4939-6406-2_17     Document Type: Chapter

References (39)

1. Abbas AK, Lichtman AH, Pillai S (2014) Cellular and molecular immunology: with student consult online access. Elsevier Health Sciences, Philadelphia, PA
2. Abbott WM, Damschroder MM, Lowe DC (2014) Current approaches to fine mapping of antigen–antibody interactions. Immunology 142(4):526–535
3. Reineke U, Schutkowski M (2009) Epitope mapping protocols, vol 524, Methods in molecular biology. Humana Press, New York
4. EL-Manzalawy Y, Honavar V (2010) Recent advances in B-cell epitope prediction methods. Immunome Res Suppl 2:S2
5. Walter G (1986) Production and use of antibodies against synthetic peptides. J Immunol Methods 88(2):149–161
6. Wu X, Li X, Zhang Q, Wulin S, Bai X, Zhang T, Wang Y, Liu M, Zhang Y (2015) Identification of a conserved B-cell epitope on duck hepatitis A type 1 virus VP1 protein. PLoS One 10(2):e0118041
7. Palumbo E, Fiaschi L, Brunelli B, Marchi S, Savino S, Pizza M (2012) Antigen identification starting from the genome: a “Reverse Vaccinology” approach applied to MenB. In: Neisseria meningitidis: advanced methods and protocols. Methods in molecular biology, vol 799. Springer, pp 361–403
8. Donati C, Rappuoli R (2013) Reverse vaccinology in the 21st century: improvements over the original design. Ann N Y Acad Sci 1285(1):115–132
9. Xiang Z, He Y (2013) Genome-wide prediction of vaccine targets for human herpes simplex viruses using Vaxign reverse vaccinology. BMC Bioinformatics 14(Suppl 4):S2
10. Emini EA, Hughes JV, Perlow D, Boger J (1985) Induction of hepatitis A virusneutralizing antibody by a virus-specific synthetic peptide. J Virol 55(3):836–839
11. Karplus P, Schulz G (1985) Prediction of chain flexibility in proteins. Naturwissenschaften 72(4):212–213
12. Parker J, Guo D, Hodges R (1986) New hydrophilicity scale derived from high-performance liquid chromatography peptide retention data: correlation of predicted surface residues with antigenicity and X-ray-derived accessible sites. Biochemistry 25(19):5425–5432
13. Saha S, Raghava G (2004) BcePred: prediction of continuous B-cell epitopes in antigenic sequences using physico-chemical properties. In: Artificial immune systems. Lecture notes in computer science, vol 3239. Springer, pp 197–204
14. Larsen J, Lund O, Nielsen M (2006) Improved method for predicting linear B-cell epitopes. Immunome Res 2(2):1–7
15. EL-Manzalawy Y, Dobbs D, Honavar V (2008) Predicting linear B-cell epitopes using string kernels. J Mol Recognit 21(4):243–255
16. EL-Manzalawy Y, Dobbs D, Honavar V (2008) Predicting flexible length linear B-cell epitopes. In: Computational systems bioinformatics. NIH Public Access, pp 121–132
17. Sweredoski MJ, Baldi P (2009) COBEpro: a novel system for predicting continuous B-cell epitopes. Protein Eng Design Select 22(3):113–120
18. Singh H, Ansari HR, Raghava GP (2013) Improved method for linear B-cell epitope prediction using Antigen’s primary sequence. PLoS One 8(5):e62216
19. EL-Manzalawy Y, Honavar V (2014) Building classifier ensembles for B-cell epitope prediction. In: Immunoinformatics. Methods in molecular biology, vol 1184. Springer, pp 285–294
20. Esmaielbeiki R, Krawczyk K, Knapp B, Nebel J-C, Deane CM (2015) Progress and challenges in predicting protein interfaces. Brief Bioinformatics bbv027
21. Xue LC, Dobbs D, Bonvin A, Honavar V (2015) Protein-protein interface predictions by data-driven methods: a review. FEBS Lett 589(23):3516–3526
22. Yao B, Zheng D, Liang S, Zhang C (2013) Conformational B-cell epitope prediction on antigen protein structures: a review of current algorithms and comparison with common binding site prediction methods. PLoS One 8(4):e62249
23. Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat T, Weissig H, Shindyalov IN, Bourne PE (2000) The protein data bank. Nucleic Acids Res 28(1):235–242
24. Gao J, Faraggi E, Zhou Y, Ruan J, Kurgan L (2012) BEST: improved prediction of B-cell epitopes from antigen sequences. PLoS One 7(6):e40104
25. Ansari HR, Raghava G (2010) Identification of conformational B-cell epitopes in an antigen from its primary sequence. Immunome Res 6(6):1–9
26. Sela-Culang I, Ofran Y, Peters B (2015) Antibody specific epitope prediction—emergence of a new paradigm. Curr Opin Virol 11:98–102
27. Xue LC, Dobbs D, Honavar V (2011) HomPPI: a class of sequence homology based protein-protein interface prediction methods. BMC Bioinformatics 12(1):244
28. Minhas A, ul Amir F, Geiss BJ, Ben-Hur A (2014) PAIRpred: partner-specific prediction of interacting residues from sequence and structure. Proteins 82(7):1142–1155
29. El-Manzalawy Y, Dobbs D, Honavar V (2011) Predicting MHC-II binding affinity using multiple instance regression. Comput Biol Bioinformatics IEEE/ACM Trans 8(4):1067–1079
30. Trolle T, Metushi IG, Greenbaum JA, Kim Y, Sidney J, Lund O, Sette A, Peters B, Nielsen M (2015) Automated benchmarking of peptide-MHC class I binding predictions. Bioinformatics btv123
31. Rubinstein ND, Mayrose I, Halperin D, Yekutieli D, Gershoni JM, Pupko T (2008) Computational characterization of B-cell epitopes. Mol Immunol 45(12):3477–3489
32. Chen J, Liu H, Yang J, Chou K-C (2007) Prediction of linear B-cell epitopes using amino acid pair antigenicity scale. Amino Acids 33(3):423–428
33. Zhang Q, Wang P, Kim Y, Haste-Andersen P, Beaver J, Bourne PE, Bui H-H, Buus S, Frankild S, Greenbaum J (2008) Immune epitope database analysis resource (IEDB-AR). Nucleic Acids Res 36(suppl 2):W513–W518
34. Krawczyk K, Liu X, Baker T, Shi J, Deane CM (2014) Improving B-cell epitope prediction and its application to global antibody-antigen docking. Bioinformatics 30(16):2288–2294
35. Zhao L, Li J (2010) Mining for the antibodyantigen interacting associations that predict the B cell epitopes. BMC Struct Biol 10(Suppl 1):S6
36. Zhao L, Wong L, Li J (2011) Antibodyspecified B-cell epitope prediction in line with the principle of context-awareness. Comput Biol Bioinformatics IEEE/ACM Trans 8(6):1483–1494
37. Sela-Culang I, Benhnia MR-E-I, Matho MH, Kaever T, Maybeno M, Schlossman A, Nimrod G, Li S, Xiang Y, Zajonc D (2014) Using a combined computational-experimental approach to predict antibody-specific B cell epitopes. Structure 22(4):646–657
38. Herraez A (2006) Biomolecules in the computer: Jmol to the rescue. Biochem Mol Biol Educ 34(4):255–261
39. DeLano WL (2002) Pymol: an open-source molecular graphics tool. CCP4 Newslett Protein Crystallogr 40:82–92