World Scientific
  • Search
  •   
Skip main navigation

Cookies Notification

We use cookies on this site to enhance your user experience. By continuing to browse the site, you consent to the use of our cookies. Learn More
×

System Upgrade on Tue, May 28th, 2024 at 2am (EDT)

Existing users will be able to log into the site and access content. However, E-commerce and registration of new users may not be available for up to 12 hours.
For online purchase, please visit us again. Contact us at [email protected] for any enquiries.

A novel Arg H52/Tyr H33 conservative motif in antibodies: A correlation between sequence of antibodies and antigen binding

    https://doi.org/10.1142/S0219720016500190Cited by:0 (Source: Crossref)

    Antibodies are the family of proteins, which are responsible for antigen recognition. The computational modeling of interaction between an antigen and an antibody is very important when crystallographic structure is unavailable. In this research, we have discovered the correlation between the amino acid sequence of antibody and its specific binding characteristics on the example of the novel conservative binding motif, which consists of four residues: Arg H52, Tyr H33, Thr H59, and Glu H61. These residues are specifically oriented in the binding site and interact with each other in a specific manner. The residues of the binding motif are involved in interaction strictly with negatively charged groups of antigens, and form a binding complex. Mechanism of interaction and characteristics of the complex were also discovered. The results of this research can be used to increase the accuracy of computational antibody–antigen interaction modeling and for post-modeling quality control of the modeled structures.

    References

    • 1. C Chothia and AM Lesk, Canonical structures for the hypervariable regions of immunoglobulins, J Mol Biol 196 (4) (1987) 901–917. Crossref, MedlineGoogle Scholar
    • 2. J Dunbar et al., SAbDab: The structural antibody database, Nucl Acids Res 42 (2014) 1140–1146. CrossrefGoogle Scholar
    • 3. HM Berman et al., The protein data bank, Nucl Acids Res 28 (2000) 235–242. Crossref, MedlineGoogle Scholar
    • 4. WL DeLano, The PyMOL Molecular Graphics System, DeLano Scientific, San Carlos, CA, USA, 2002. Google Scholar
    • 5. MC Ramirez-Benitez et al., VIR.II: A new interface with the antibody sequences in the Kabat database, BioSystems 61 (2001) 125–131. Crossref, MedlineGoogle Scholar
    • 6. F Sievers, Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega, Mol Syst Biol 7 (2011) 539. Crossref, MedlineGoogle Scholar
    • 7. AM Waterhouse et al., Jalview Version 2—A multiple sequence alignment editor and analysis workbench, Bioinformatics 25 (2009) 1189–1191. Crossref, MedlineGoogle Scholar
    • 8. V Arzhanik et al., Interaction of antibodies with aromatic ligands: The role of π-stacking, J Bioinform Comput Biol 8 (2010) 471–483. LinkGoogle Scholar
    • 9. B Hess et al., GROMACS 4: Algorithms for highly efficient, load-balanced, and scalable molecular simulation, J Chem Theor Comput 4 (2008) 435–447. Crossref, MedlineGoogle Scholar
    • 10. Y Duan et al., A point-charge force field for molecular mechanics simulations of proteins based on condensed-phase quantum mechanical calculations, J Comput Chem 24 (2003) 1999–2012. Crossref, MedlineGoogle Scholar
    • 11. G Bussi et al., Canonical sampling through velocity rescaling, J Chem Phys 126 (2007) 1–6. CrossrefGoogle Scholar
    • 12. HJC Berendsen et al., Molecular dynamics with coupling to an external bath, J Chem Phys 81 (1984) 3684–3690. CrossrefGoogle Scholar
    • 13. T Darden et al., Particle mesh Ewald: An N log(N) method for Ewald sums in large systems, J Chem Phys 98 (1993) 10089–10092. CrossrefGoogle Scholar
    • 14. WL Jorgensen et al., Comparison of simple potential functions for simulating liquid water, J Chem Phys 79 (1983) 926–935. CrossrefGoogle Scholar
    • 15. A Shishkina et al., Conjugates of amino acids and peptides with 5-o-mycaminosyltylonolide and their interaction with the ribosomal exit tunnel, Bioconjug Chem 24 (2013) 1861–1869. Crossref, MedlineGoogle Scholar
    • 16. V Sadovnichy et al., “Lomonosov”: Supercomputing at Moscow State University, Contemporary High Performance Computing: From Petascale toward Exascale, Chapman & Hall/CRC Computational Science (CRC Press, Boca Raton, USA, 2013), pp. 283–307. Google Scholar
    • 17. CL Brooks et al., Exploration of specificity in germline monoclonal antibody recognition of a range of natural and synthetic epitopes, J Mol Biol 377 (2008) 450–468. Crossref, MedlineGoogle Scholar
    • 18. D Nikoloudis et al., A complete, multi-level conformational clustering of antibody complementarity-determining regions, PeerJ 2 (2014) e456. Crossref, MedlineGoogle Scholar
    • 19. B Golinelli-Pimpaneau et al., Structural basis for D-amino acid transamination by the pyridoxal 5’-phosphate-dependent catalytic antibody 15A9, J Biol Chem 281 (2006) 23969–23977. Crossref, MedlineGoogle Scholar
    • 20. LC Hsieh-Wilson et al., Insights into antibody catalysis: Structure of an oxygenation catalyst at 1.9-A resolution, Proc Natl Acad Sci USA 93 (1996) 5363–5367. Crossref, MedlineGoogle Scholar
    • 21. S Mian et al., Structure, function and properties of antibody binding sites, J Mol Biol 217 (1991) 133–151. Crossref, MedlineGoogle Scholar
    • 22. Chen et al., Enhancement and destruction of antibody function by somatic mutation: Unequal occurrence is controlled by V gene combinatorial associations, EMBO J 14 (1995) 2784–2794. Crossref, MedlineGoogle Scholar
    • 23. J Novotny et al., On the attribution of binding energy in antigen-antibody complexes McPC 603, D1.3, and HyHEL-5, Biochemistry 28 (1989) 4735–4749. Crossref, MedlineGoogle Scholar
    • 24. B Mouratou and J Stetefeld, Identification of functionally important residues in the pyridoxal-5c-phosphate-dependent catalytic antibody 15A9, Biochemistry 43 (2004) 6612–6619. Crossref, MedlineGoogle Scholar
    • 25. R Sathyapriya and V Saraswathi, Short hydrogen bonds in proteins, FEBS J 272 (2005) 1819–1832. Crossref, MedlineGoogle Scholar
    • 26. N Sinha, SJ Smith-Gill et al., Differences in electrostatic properties at antibody–antigen binding sites: Implications for specificity and cross-reactivity, Biophys J 83 (2002) 2946–2968. Crossref, MedlineGoogle Scholar
    • 27. SK Burley and GA Petsko, Weakly polar interactions in proteins, Adv Protein Chem 39 (1988) 125–186. Crossref, MedlineGoogle Scholar
    • 28. DJ Barlow and JM Thornton, Ion-pairs in proteins, J Mol Biol 168 (1983) 867–885. Crossref, MedlineGoogle Scholar
    • 29. KR Abhinandan and ACR Martin, Analysis and improvements to Kabat and structurally correct numbering of antibody variable domains, Mol Immunol 45 (2008) 3832–3839. Crossref, MedlineGoogle Scholar