Skip to main content
SpringerLink
Log in

Computer-Aided Antibody Design: An Overview

  • Chapter
  • First Online:
Recombinant Antibodies for Infectious Diseases

Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 1053))

Abstract

The use of monoclonal antibody as the next generation protein therapeutics with remarkable success has surged the development of antibody engineering to design molecules for optimizing affinity, better efficacy, greater safety and therapeutic function. Therefore, computational methods have become increasingly important to generate hypotheses, interpret and guide experimental works. In this chapter, we discussed the overall antibody design by computational approches.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 189.00
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Abhinandan KR, Martin AC (2010) Analysis and prediction of VH/VL packing in antibodies. Protein Eng Des Sel 23:689–697. https://doi.org/10.1093/protein/gzq043

    Article  CAS  PubMed  Google Scholar 

  2. Al-Lazikani B, Lesk AM, Chothia C (1997) Standard conformations for the canonical structures of immunoglobulins. J Mol Biol 273:927–948. https://doi.org/10.1006/jmbi.1997.1354

    Article  CAS  PubMed  Google Scholar 

  3. Almagro JC, Beavers MP, Hernandez-Guzman F, Maier J, Shaulsky J, Butenhof K, Labute P, Thorsteinson N, Kelly K, Teplyakov A, Luo J, Sweet R, Gilliland GL (2011) Antibody modeling assessment. Proteins 79:3050–3066

    Article  CAS  PubMed  Google Scholar 

  4. Almagro JC, Teplyakov A, Luo J, Sweet RW, Kodangattil S, Hernandez-Guzman F, Gilliland GL (2014) Second antibody modeling assessment (AMA-II). Proteins 82:1553–1562

    Article  CAS  PubMed  Google Scholar 

  5. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ (1990) Basic local alignment search tool. J Mol Biol 215:403–410. https://doi.org/10.1016/S0022-2836(05)80360-2[pii]

    Article  CAS  PubMed  Google Scholar 

  6. Andersen PH, Nielsen M, Lund O (2006) Prediction of residues in discontinuous B-cell epitopes using protein 3D structures. Protein Sci 15:2558–2567. https://doi.org/10.1110/ps.062405906

  7. Ansari HR, Flower DR, Raghava G (2010) AntigenDB: an immunoinformatics database of pathogen antigens. Nucleic Acids Res 38:D847–D853

    Article  CAS  PubMed  Google Scholar 

  8. Barderas R, Desmet J, Timmerman P, Meloen R, Casal JI (2008) Affinity maturation of antibodies assisted by in silico modeling. Proc Natl Acad Sci 105:9029–9034

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Beck A (2011) Biosimilar, biobetter and next generation therapeutic antibodies. MAbs 3:107–110

    Article  PubMed  Google Scholar 

  10. Ben-Horin S, Bank I (2004) The role of very late antigen-1 in immune-mediated inflammation. Clin Immunol 113:119–129. https://doi.org/10.1016/j.clim.2004.06.007

    Article  CAS  PubMed  Google Scholar 

  11. Bernstein FC, Koetzle TF, Williams GJ, Meyer EF, Brice MD, Rodgers JR, Kennard O, Shimanouchi T, Tasumi M (1977) The protein data bank. Eur J Biochem 80(2):319–324. https://doi.org/10.1111/j.1432-1033.1977.tb11885.x. Blackwell Publishing Ltd

    Article  CAS  PubMed  Google Scholar 

  12. Borhani WD, Shaw DE (2012) The future of molecular dynamics simulations in drug discovery. J Comput Aided Mol Des 26:15–26

    Article  CAS  PubMed  Google Scholar 

  13. Bradley P, Misura KM, Baker D (2005) Toward high-resolution de novo structure prediction for small proteins. Science 309:1868–1871

    Article  CAS  PubMed  Google Scholar 

  14. Carter PJ (2006) Potent antibody therapeutics by design. Nat Rev Immunol 6:343–357. http://www.nature.com/nri/journal/v6/n5/suppinfo/nri1837_S1.html

    Article  CAS  PubMed  Google Scholar 

  15. Chaudhury S, Berrondo M, Weitzner BD, Muthu P, Bergman H, Gray JJ (2011) Benchmarking and analysis of protein docking performance in Rosetta v3.2. PLoS One 6:e22477

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Chaudhury S, Gray JJ (2008) Conformer selection and induced fit in flexible backbone protein–protein docking using computational and NMR ensembles. J Mol Biol 381:1068–1087

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Chen R, Weng Z (2002) Docking unbound proteins using shape complementarity, desolvation, and electrostatics. Proteins 47:281–294

    Article  CAS  PubMed  Google Scholar 

  18. Chen WH, Sun PP, Lu Y, Guo WW, Huang YX, Ma ZQ (2011) MimoPro: a more efficient Web-based tool for epitope prediction using phage display libraries. BMC Bioinformatics 12:1–13

    Article  CAS  Google Scholar 

  19. Cheng M, Ahmed M, Xu H, Cheung NKV (2015) Structural design of disialoganglioside GD2 and CD3-bispecific antibodies to redirect T cells for tumor therapy. Int J Cancer 136:476–486

    Article  CAS  PubMed  Google Scholar 

  20. Choi I, Chung AW, Suscovich TJ, Rerks-Ngarm S, Pitisuttithum P, Nitayaphan S, Kaewkungwal J, O’Connell RJ, Francis D, Robb ML, Michael NL, Kim JH, Alter G, Ackerman ME, Bailey-Kellogg C (2015) Machine learning methods enable predictive modeling of antibody feature:function relationships in RV144 vaccinees. PLoS Comput Biol 11:e1004185

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  21. Chong LT, Duan Y, Wang L, Massova I, Kollman PA (1999) Molecular dynamics and free-energy calculations applied to affinity maturation in antibody 48G7. Proc Natl Acad Sci U S A 96:14330–14335

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Clark LA, Boriack-Sjodin PANN, Eldredge J, Fitch C, Friedman B, Hanf KJ, Jarpe M, Liparoto SF, Li Y, Lugovskoy A, Miller S, Rushe M, Sherman W, Simon K, Van Vlijmen H (2006) Affinity enhancement of an in vivo matured therapeutic antibody using structure-based computational design. Protein Sci 15:949–960

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Collura V, Higo J, Garnier J (1993) Modeling of protein loops by simulated annealing. Protein Sci 2:1502–1510

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Colovos C, Yeates TO (1993) Verification of protein structures: patterns of nonbonded atomic interactions. Protein Sci 2:1511–1519

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Correia BE, Ban YEA, Holmes MA, Xu H, Ellingson K, Kraft Z, Carrico C, Boni E, Sather DN, Zenobia C, Burke KY, Bradley-Hewitt T, Bruhn-Johannsen JF, Kalyuzhniy O, Baker D, Strong RK, Stamatatos L, Schief WR (2010) Computational design of epitope-scaffolds allows induction of antibodies specific for a poorly immunogenic HIV vaccine epitope. Structure 18:1116–1126. https://doi.org/10.1016/j.str.2010.06.010

    Article  CAS  PubMed  Google Scholar 

  26. Davies DR, Sheriff S, Padlan EA (1988) Antibody-antigen complexes. J Biol Chem 263:10541–10544

    CAS  PubMed  Google Scholar 

  27. Dunbar J, Krawczyk K, Leem J, Baker T, Fuchs A, Georges G, Shi J, Deane CM (2014) SAbDab: the structural antibody database. Nucleic Acids Res 42:1140–1146

    Article  CAS  Google Scholar 

  28. Ecker DM, Jones SD, Levine HL (2015) The therapeutic monoclonal antibody market. MAbs 7:9–14. https://doi.org/10.4161/19420862.2015.989042

    Article  CAS  PubMed  Google Scholar 

  29. Eisenberg D, Lüthy R, Bowie JU (1997) VERIFY3D: assessment of protein models with three-dimensional profiles. Methods Enzymol 277:396–404. https://doi.org/10.1016/S0076-6879(97)77022-8. Academic

  30. El-Manzalawy Y, Honavar V (2010) Recent advances in B-cell epitope prediction methods. Immunome Res 6(Suppl 2):S2. https://doi.org/10.1186/1745-7580-6-S2-S2

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  31. Eswar N, Webb B, Marti-Renom MA, Madhusudhan MS, Eramian D, Shen MY, Pieper U, Sali A (2006) Comparative protein structure modeling using modeller. Curr Protoc Bioinformatics. Editoral board, Baxevanis AD et al. Chapter 5:Unit 5 6. https://doi.org/10.1002/0471250953.bi0506s15

  32. Fan H, Mark AE (2004) Refinement of homology-based protein structures by molecular dynamics simulation techniques. Protein Sci 13:211–220. https://doi.org/10.1110/ps.03381404

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Farimani AB, Aluru NR, Tajkhorshid E, Jakobsson E (2016) Computational approach to designing antibody for Ebola virus. Biophys J 110:537a

    Article  Google Scholar 

  34. Foltz IN, Karow M, Wasserman SM (2013) Evolution and emergence of therapeutic monoclonal antibodies: what cardiologists need to know. Circulation 127:2222–2230. https://doi.org/10.1161/CIRCULATIONAHA.113.002033

    Article  PubMed  Google Scholar 

  35. Gaillard T, Simonson T (2014) Pairwise decomposition of an MMGBSA energy function for computational protein design. J Comput Chem 35:1371–1387

    Article  CAS  PubMed  Google Scholar 

  36. Georgiou G, Ippolito GC, Beausang J, Busse CE, Wardemann H, Quake SR (2014) The promise and challenge of high-throughput sequencing of the antibody repertoire. Nat Biotechnol 32:158–168

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Greer J (1990) Comparative modeling methods: application to the family of the mammalian serine proteases. Proteins 7:317–334. https://doi.org/10.1002/prot.340070404

    Article  CAS  PubMed  Google Scholar 

  38. He B, Chai G, Duan Y, Yan Z, Qiu L, Zhang H, Liu Z, He Q, Han K, Ru B, Guo FB, Ding H, Lin H, Wang X, Rao N, Zhou P, Huang J (2016) BDB: biopanning data bank. Nucleic Acids Res 44:D1127–D1132. https://doi.org/10.1093/nar/gkv1100

    Article  CAS  PubMed  Google Scholar 

  39. Hospital A, Goñi JR, Orozco M, Gelpí JL (2015) Molecular dynamics simulations: advances and applications. Adv Appl Bioinform Chem 8:37–47. https://doi.org/10.2147/AABC.S70333

    PubMed  PubMed Central  Google Scholar 

  40. Hou T, Guo S, Xu X (2002) Predictions of binding of a diverse set of ligands to gelatinase-A by a combination of molecular dynamics and continuum solvent models. J Phys Chem B 106:5527–5535. https://doi.org/10.1021/jp015516z

    Article  CAS  Google Scholar 

  41. Hu ZQ, Li HP, Liu JL, Xue S, Gong AD, Zhang JB, Liao YC (2016) Production of a phage-displayed mouse ScFv antibody against fumonisin B1 and molecular docking analysis of their interactions. Biotechnol Bioprocess Eng 21:134–143

    Article  CAS  Google Scholar 

  42. Huang J, Honda W (2006) CED: a conformational epitope database. BMC Immunol 7:1–7. https://doi.org/10.1186/1471-2172-7-7

    Article  CAS  Google Scholar 

  43. Huang SY, Zou X (2010) Advances and challenges in protein-ligand docking. Int J Mol Sci 11:3016–3034. https://doi.org/10.3390/ijms11083016

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Huang YX, Bao YL, Guo SY, Wang Y, Zhou CG, Li YX (2008) Pep-3D-Search: a method for B-cell epitope prediction based on mimotope analysis. BMC Bioinformatics 9:538. https://doi.org/10.1186/1471-2105-9-538

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  45. Jauch R, Yeo HC, Kolatkar PR, Clarke ND (2007) Assessment of CASP7 structure predictions for template free targets. Proteins 69:57–67

    Article  CAS  PubMed  Google Scholar 

  46. Jones D (1998) THREADER: protein sequence threading by double dynamic programming. In: Salzberg SL, Searls DB, Simon K (eds) New Compr Biochem 32:285–311. https://doi.org/10.1016/S0167-7306(08)60470-6. Elsevier

  47. Jung J, Mori T, Kobayashi C, Matsunaga Y, Yoda T, Feig M, Sugita Y (2015) GENESIS: a hybrid-parallel and multi-scale molecular dynamics simulator with enhanced sampling algorithms for biomolecular and cellular simulations. Wiley Interdiscip Rev Comput Mol Sci 5:310–323

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Kiyoshi M, Caaveiro JM, Miura E, Nagatoishi S, Nakakido M, Soga S, Shirai H, Kawabata S, Tsumoto K (2014) Affinity improvement of a therapeutic antibody by structure-based computational design: generation of electrostatic interactions in the transition state stabilizes the antibody-antigen complex. PLoS One 9:e87099

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  49. Kollman PA, Massova I, Reyes C, Kuhn B, Huo S, Chong L, Lee M, Lee T, Duan Y, Wang W, Donini O, Cieplak P, Srinivasan J, Case DA, Cheatham TE 3rd (2000) Calculating structures and free energies of complex molecules: combining molecular mechanics and continuum models. Acc Chem Res 33:889–897. doi:ar000033j [pii]

    Article  CAS  PubMed  Google Scholar 

  50. Kortemme T, Kim DE, Baker D (2004) Computational alanine scanning of protein-protein interfaces. Sci STKE 2004:pl2

    Google Scholar 

  51. Kuroda D, Shirai H, Jacobson MP, Nakamura H (2012) Computer-aided antibody design. Protein Eng Des Sel 25:507–522. https://doi.org/10.1093/protein/gzs024

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Kuroda D, Shirai H, Kobori M, Nakamura H (2008) Structural classification of CDR-H3 revisited: a lesson in antibody modeling. Proteins 73:608–620

    Article  CAS  PubMed  Google Scholar 

  53. Laitinen T, Kankare JA, Peräkylä M (2004) Free energy simulations and MM–PBSA analyses on the affinity and specificity of steroid binding to antiestradiol antibody. Proteins 55:34–43

    Article  CAS  PubMed  Google Scholar 

  54. Lazar GA, Dang W, Karki S, Vafa O, Peng JS, Hyun L, Chan C, Chung HS, Eivazi A, Yoder SC, Vielmetter J, Carmichael DF, Hayes RJ, Dahiyat BI (2006) Engineered antibody Fc variants with enhanced effector function. Proc Natl Acad Sci U S A 103:4005–4010. https://doi.org/10.1073/pnas.0508123103

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Lee VS, Tue-ngeun P, Nangola S, Kitidee K, Jitonnom J, Nimmanpipug P, Jiranusornkul S, Tayapiwatana C (2010) Pairwise decomposition of residue interaction energies of single chain Fv with HIV-1 p17 epitope variants. Mol Immunol 47:982–990. doi:S0161-5890(09)00848-7 [pii] 1016/j.molimm.2009.11.021

    Article  CAS  PubMed  Google Scholar 

  56. Lees WD, Stejskal L, Moss DS, Shepherd AJ (2017) Investigating substitutions in antibody–antigen complexes using molecular dynamics: a case study with broad-spectrum, influenza a antibodies. Front Immunol 8. https://doi.org/10.3389/fimmu.2017.00143

  57. Lefèvre F, Rémy MH, Masson JM (1997) Alanine-stretch scanning mutagenesis: a simple and efficient method to probe protein structure and function. Nucleic Acids Res 25:447–448

    Article  PubMed  PubMed Central  Google Scholar 

  58. Levitt M (1992) Accurate modeling of protein conformation by automatic segment matching. J Mol Biol 226:507–533. https://doi.org/10.1016/0022-2836(92)90964-L

    Article  CAS  PubMed  Google Scholar 

  59. Li J, Zhu Z (2010) Research and development of next generation of antibody-based therapeutics. Acta Pharmacol Sin 31:1198–1207. https://doi.org/10.1038/aps.2010.120

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Liang S, Zheng D, Zhang C, Zacharias M (2009) Prediction of antigenic epitopes on protein surfaces by consensus scoring. BMC Bioinform 10:302. https://doi.org/10.1186/1471-2105-10–302

  61. Lippow SM, Wittrup KD, Tidor B (2007) Computational design of antibody-affinity improvement beyond in vivo maturation. Nat Biotechnol 25:1171–1176

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Liu JK (2014) The history of monoclonal antibody development – progress, remaining challenges and future innovations. Ann Med Surg 3:113–116

    Article  Google Scholar 

  63. Marcatili P, Rosi A, Tramontano A (2008) PIGS: automatic prediction of antibody structures. Bioinformatics 24:1953–1954

    Article  CAS  PubMed  Google Scholar 

  64. Margreitter C, Mayrhofer P, Kunert R, Oostenbrink C (2016) Antibody humanization by molecular dynamics simulations—in-silico guided selection of critical backmutations. J Mol Recognit 29:266–275. https://doi.org/10.1002/jmr.2527

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Meng XY, Zhang HX, Mezei M, Cui M (2011) Molecular docking: a powerful approach for structure-based drug discovery. Curr Comput Aided Drug Des 7:146–157

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Messer BM, Roca M, Chu ZT, Vicatos S, Kilshtain AV, Warshel A (2010) Multiscale simulations of protein landscapes: using coarse-grained models as reference potentials to full explicit models. Proteins: Struct Funct Bioinf 78:1212–1227

    Article  CAS  Google Scholar 

  67. Messih MA, Lepore R, Marcatili P, Tramontano A (2014) Improving the accuracy of the structure prediction of the third hypervariable loop of the heavy chains of antibodies. Bioinformatics 30:2733–2740

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Miethe S, Mazuet C, Liu Y, Tierney R, Rasetti-Escargueil C, Avril A, Frenzel A, Thullier P, Pelat T, Urbain R (2016) Development of germline-humanized antibodies neutralizing botulinum neurotoxin A and B. PLoS One 11:e0161446

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  69. Moal IH, Bates PA (2010) SwarmDock and the use of normal modes in protein-protein docking. Int J Mol Sci 11:3623–3648. https://doi.org/10.3390/ijms11103623

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Mohan V, Gibbs AC, Cummings MD, Jaeger EP, DesJarlais RL (2005) Docking: successes and challenges. Curr Pharm Des 11:323–333

    Article  CAS  PubMed  Google Scholar 

  71. Monika G, Punam G, Sarbjot S, Gupta GD (2010) An overview on molecular docking. Int J Drug Dev Res 2:219–231

    Google Scholar 

  72. Moreira IS, Fernandes PA, Ramos MJ (2007) Computational alanine scanning mutagenesis—an improved methodological approach. J Comput Chem 28:644–654

    Article  CAS  PubMed  Google Scholar 

  73. Morris GM, Goodsell DS, Halliday RS, Huey R, Hart WE, Belew RK, Olson AJ (1998) Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function. J Comput Chem 19:1639–1662

    Article  CAS  Google Scholar 

  74. 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 30:2785–2791. https://doi.org/10.1002/jcc.21256

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Nelson AL, Dhimolea E, Reichert JM (2010) Development trends for human monoclonal antibody therapeutics. Nat Rev Drug Discov 9:767–774. https://doi.org/10.1038/nrd3229

    Article  CAS  PubMed  Google Scholar 

  76. North B, Lehmann A, Dunbrack RL (2011) A new clustering of antibody CDR loop conformations. J Mol Biol 406:228–256. https://doi.org/10.1016/j.jmb.2010.10.030

    Article  CAS  PubMed  Google Scholar 

  77. Novic M, Anderluh M, Tibaut T, Borisek J, Tomasic T (2016) The comparison of docking search algorithms and scoring functions: an overview and case studies. In: Dastmalchi S, Hamzeh-Mivehroud M, Sokouti B (eds) Methods and algorithms for molecular docking- based drug design and discovery. Medical Information Science Reference, Hershey, pp 99–127

    Chapter  Google Scholar 

  78. Ofek G, Guenaga FJ, Schief WR, Skinner J, Baker D, Wyatt R, Kwong PD (2010) Elicitation of structure-specific antibodies by epitope scaffolds. Proc Natl Acad Sci U S A 107:17880–17887. https://doi.org/10.1073/pnas.1004728107

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. Ołdziej S, Czaplewski C, Liwo A, Chinchio M, Nanias M, Vila JA, Khalili M, Arnautova YA, Jagielska A, Makowski MO, Schafroth HD (2005) Physics-based protein-structure prediction using a hierarchical protocol based on the UNRES force field: assessment in two blind tests. Proc Natl Acad Sci U S A 102:7547–7552

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  80. Pearlman DA, Case DA, Caldwell JW, Ross WS, Cheatham TE, DeBolt S, Ferguson D, Seibel G, Kollman P (1995) AMBER, a package of computer programs for applying molecular mechanics, normal mode analysis, molecular dynamics and free energy calculations to simulate the structural and energetic properties of molecules. Comput Phys Commun 91:1–41

    Article  CAS  Google Scholar 

  81. Pedotti M, Simonelli L, Livoti E, Varani L (2011) Computational docking of antibody-antigen complexes, opportunities and pitfalls illustrated by influenza hemagglutinin. Int J Mol Sci 12:226–251. https://doi.org/10.3390/ijms12010226

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Peters B, Sidney J, Bourne P, Bui HH, Buus S, Doh G, Fleri W, Kronenberg M, Kubo R, Lund O, Nemazee D, Ponomarenko JV, Sathiamurthy M, Schoenberger SP, Stewart S, Surko P, Way S, Wilson S, Sette A (2005) The design and implementation of the immune epitope database and analysis resource. Immunogenetics 57:326–336. https://doi.org/10.1007/s00251-005-0803-5

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Pierce BG, Wiehe K, Hwang H, Kim BH, Vreven T, Weng Z (2014) ZDOCK server: interactive docking prediction of protein-protein complexes and symmetric multimers. Bioinformatics 30:1771–1773. https://doi.org/10.1093/bioinformatics/btu097

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Ponomarenko J, Bui HH, Li W, Fusseder N, Bourne PE, Sette A, Peters B (2008) ElliPro: a new structure-based tool for the prediction of antibody epitopes. BMC Bioinformatics 9:514

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  85. Ramachandran GN, Ramakrishnan C, Sasisekharan V (1963) Stereochemistry of polypeptide chain configurations. J Mol Biol 7:95–99

    Article  CAS  PubMed  Google Scholar 

  86. Rarey M, Kramer B, Lengauer T, Klebe G (1996) A fast flexible docking method using an incremental construction algorithm. J Mol Biol 261:470–489

    Article  CAS  PubMed  Google Scholar 

  87. Ravindranath PA, Forli S, Goodsell DS, Olson AJ, Sanner MF (2015) AutoDockFR: advances in protein-ligand docking with explicitly specified binding site flexibility. PLoS Comput Biol 11:e1004586

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  88. Rubinstein ND, Mayrose I, Martz E, Pupko T (2009) Epitopia: a web-server for predicting B-cell epitopes. BMC Mioinform 10: 87. https://doi.org/10.1186/1471-2105-10-287

  89. Šali A, Blundell T (1993) Comparative protein modelling by satisfaction of spatial restraints. J Mol Biol 234:779–815. https://doi.org/10.1006/jmbi.1993.1626

    Article  PubMed  Google Scholar 

  90. Schrödinger (2016) Prime, version 4.5. Schrödinger, LLC, New York

    Google Scholar 

  91. Sevy AM, Meiler J (2014) Antibodies: computer-aided prediction of structure and design of function. Microbiol Spectr 2:1–14

    Article  CAS  Google Scholar 

  92. Shirai H, Kidera A, Nakamura H (1999) H3-rules: identification of CDR-H3 structures in antibodies. FEBS Lett 455:188–197

    Article  CAS  PubMed  Google Scholar 

  93. Shirai H, Nakajima N, Higo J, Kidera A, Nakamura H (1998) Conformational sampling of CDR-H3 in antibodies by multicanonical molecular dynamics simulation. J Mol Biol 278:481–496

    Article  CAS  PubMed  Google Scholar 

  94. Sircar A, Kim ET, Gray JJ (2009) RosettaAntibody: antibody variable region homology modeling server. Nucleic Acids Res 37:W474–W479

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  95. Sivasubramanian A, Sircar A, Chaudhury S, Gray JJ (2009) Toward high-resolution homology modeling of antibody Fv regions and application to antibody–antigen docking. Proteins 74:497–514

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. Soria-Guerra RE, Nieto-Gomez R, Govea-Alonso DO, Rosales-Mendoza S (2015) An overview of bioinformatics tools for epitope prediction: implications on vaccine development. J Biomed Inform 53:405–414

    Article  PubMed  Google Scholar 

  97. Sormanni P, Aprile FA, Vendruscolo M (2015) Rational design of antibodies targeting specific epitopes within intrinsically disordered proteins. Proc Natl Acad Sci 112:9902–9907

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Sousa SF, Fernandes PA, Ramos MJ (2006) Protein–ligand docking: current status and future challenges. Proteins 65:15–26

    Article  CAS  PubMed  Google Scholar 

  99. Sun J, Wu D, Xu T, Wang X, Xu X, Tao L (2009) SEPPA: a computational server for spatial epitope prediction of protein antigens. Nucleic Acids Res 37:W612–W616. https://doi.org/10.1093/nar/gkp417

  100. Sun P, Ju H, Liu Z, Ning Q, Zhang J, Zhao X, Huang Y, Ma Z, Li Y (2013) Bioinformatics resources and tools for conformational B-cell epitope prediction. Comput Math Methods Med 2013:943636

    PubMed  PubMed Central  Google Scholar 

  101. Sweredoski MJ, Baldi P (2008) PEPITO: improved discontinuous B-cell epitope prediction using multiple distance thresholds and half sphere exposure. Bioinformatics 24:1459–1460. https://doi.org/10.1093/bioinformatics/btn199

  102. Teplyakov A, Gilliland GL (2014) Canonical structures of short CDR-L3 in antibodies. Proteins 82:1668–1673. https://doi.org/10.1002/prot.24559

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  103. Tiller KE, Tessier PM (2015) Advances in antibody design. Annu Rev Biomed Eng 17:191–216

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  104. Tonegawa S (1983) Somatic generation of antibody diversity. Nature 302:575–581

    Article  CAS  PubMed  Google Scholar 

  105. Tramontano A (2006) The role of molecular modelling in biomedical research. FEBS Lett 580:2928–2934

    Article  CAS  PubMed  Google Scholar 

  106. Tronrud DE (1992) Conjugate-direction minimization: an improved method for the refinement of macromolecules. Acta Crystsllogr A 48:912–916

    Article  Google Scholar 

  107. Tronrud DE (2004) Introduction to macromolecular refinement. Acta Crystsllogr D Biol Crystallogr 60:2156–2168

    Article  CAS  Google Scholar 

  108. Trott O, Olson AJ (2009) AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem 31:455–461. https://doi.org/10.1002/jcc.21334

    Google Scholar 

  109. Tue-ngeun P, Kodchakorn K, Nimmanpipug P, Lawan N, Nangola S, Tayapiwatana C, Rahman NA, Zain SM, Lee VS (2013) Improved SCFV ANTI-HIV-1 P17 binding affinity guided from the theoretical calculation of pairwise decomposition energies and Computational Alanine Scanning. Biomed Res Int 2013:1–12

    Article  CAS  Google Scholar 

  110. Vakser IA (2014) Protein-protein docking: from interaction to interactome. Biophys J 107:1785–1793

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  111. Valuev VP, Afonnikov DA, Ponomarenko MP, Milanesi L, Kolchanov NA (2002) ASPD (Artificially Selected Proteins/Peptides Database): a database of proteins and peptides evolved in vitro. Nucleic Acids Res 30:200–202

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  112. Vita R, Overton JA, Greenbaum JA, Ponomarenko J, Clark JD, Cantrell JR, Wheeler DK, Gabbard JL, Hix D, Sette A (2015) The immune epitope database (IEDB) 3.0. Nucleic Acids Res 43:D405–D412

    Article  CAS  PubMed  Google Scholar 

  113. Volpe JM, Cowell LG, Kepler TB (2006) SoDA: implementation of a 3D alignment algorithm for inference of antigen receptor recombinations. Bioinformatics 22:438–444

    Article  CAS  PubMed  Google Scholar 

  114. Vyas VK, Ukawala RD, Ghate M, Chintha C (2012) Homology modeling a fast tool for drug discovery: current perspectives. Indian J Pharm Sci 74:1–17. https://doi.org/10.4103/0250-474X.102537

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  115. Wang C, Schueler-Furman O, Baker D (2005) Improved side-chain modeling for protein–protein docking. Protein Sci 14:1328–1339

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  116. Willis JR, Sapparapu G, Murrell S, Julien JP, Singh V, King HG, Xia Y, Pickens JA, LaBranche CC, Slaughter JC, Montefiori DC, Wilson IA, Meiler J, Crowe JEJ (2015) Redesigned HIV antibodies exhibit enhanced neutralizing potency and breadth. J Clin Invest 125:2523–2531. https://doi.org/10.1172/JCI80693

    Article  PubMed  PubMed Central  Google Scholar 

  117. Winter G, Griffiths AD, Hawkins RE, Hoogenboom HR (1994) Making antibodies by phage display technology. Annu Rev Immunol 12:433–455. https://doi.org/10.1146/annurev.iy.12.040194.002245

    Article  CAS  PubMed  Google Scholar 

  118. Xu J, Jiao F, Yu L (2008) Protein structure prediction using threading. Methods Mol Biol 413:91–121

    CAS  PubMed  Google Scholar 

  119. Yang J, Yan R, Roy A, Xu D, Poisson J, Zhang Y (2015) The I-TASSER suite: protein structure and function prediction. Nat Methods 12:7–8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  120. Zhao Y, Sanner MF (2007) FLIPDock: docking flexible ligands into flexible receptors. Proteins 68:726–737

    Article  CAS  PubMed  Google Scholar 

  121. Zhexin X (2006) Advances in homology protein structure modeling. Curr Protein Pept Sci 7:217–227. https://doi.org/10.2174/138920306777452312

    Article  Google Scholar 

  122. Zhu K, Day T (2013) Ab initio structure prediction of the antibody hypervariable H3 loop. Proteins 81:1081–1089. https://doi.org/10.1002/prot.24240

    Article  CAS  PubMed  Google Scholar 

  123. Zhu K, Day T, Warshaviak D, Murrett C, Friesner R, Pearlman D (2014) Antibody structure determination using a combination of homology modeling, energy-based refinement, and loop prediction. Proteins 82:1646–1655. https://doi.org/10.1002/prot.24551

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgement

This work is supported by Fundamental Research Grant Scheme (FRGS; 203/CIPPM/6711439) and Higher Institution Centre of Excellence Grant (HICoE; 311/CIPPM/44001005) from Malaysia Ministry of Education. The authors would also like to acknowledge the fellowships provided by National Science Fellowship from Malaysian Ministry of Science, Technology and Innovation for YV Lee, MyBrain15 (MyMaster) scholarship from Ministry of Higher Education for JX Soong and Graduate Assistant scheme from Universiti Sains Malaysia for CT Law.

Author information

Authors and Affiliations

  1. Institute for Research in Molecular Medicine, Universiti Sains Malaysia, Minden, Penang, Malaysia

    Yee Siew Choong, Yie Vern Lee, Jia Xin Soong, Cheh Tat Law & Yee Ying Lim

Authors
  1. Yee Siew Choong
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yie Vern Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jia Xin Soong
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Cheh Tat Law
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yee Ying Lim
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yee Siew Choong .

Editor information

Editors and Affiliations

  1. Institute for Research in Molecular Medicine, Universiti Sains Malaysia, Penang, Malaysia

    Theam Soon Lim

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG, part of Springer Nature

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Choong, Y.S., Lee, Y.V., Soong, J.X., Law, C.T., Lim, Y.Y. (2017). Computer-Aided Antibody Design: An Overview. In: Lim, T. (eds) Recombinant Antibodies for Infectious Diseases. Advances in Experimental Medicine and Biology, vol 1053. Springer, Cham. https://doi.org/10.1007/978-3-319-72077-7_11

Download citation

Publish with us

Policies and ethics

Search

Navigation