Skip to main content
Log in

In Silico Study on Retinoid-binding Modes in Human RBP and ApoD Lipocalins

  • Research Paper
  • Published:
Biotechnology and Bioprocess Engineering Aims and scope Submit manuscript

Abstract

Lipocalins are proteins with highly homologous structures but diverse sequences that are potential candidates for scaffold protein engineering with novel ligand-binding functions. Numerous crystal structures of lipocalin-ligand complexes have been identified and used in the study of their binding modes. On the other hand, crystallization studies cannot meet the increasing demand for novel lipocalin-ligand complexes in scaffold engineering, which requires rapid computational analyses of their binding modes in parallel. Human retinol-binding protein (RBP) and apolipoprotein D (apoD) are sequentially very distant proteins, but they show tight binding against retinoids, such as retinol and retinoic acid. In the present study, complexes of the two lipocalins with retinol and retinoic acid were modeled computationally by a molecular docking simulation, and their ligand-binding modes were analyzed at a molecular level. The models identified the crucial residues of lipocalins that interact with the ligands and revealed the similarities and differences in their retinoid-binding modes as well as in the specific interactions of the retinoid species within the same lipocalin. An analysis of the amino acid propensity of the retinoid-binding residues suggested that the evolutionary preference of the residues is restricted to the binding pocket rather than the entire protein. The distribution of charged residues around the terminus of retinoic acid showed a huge difference between RBP and ApoD, which might be a factor for the different binding affinities of lipocalins against retinoic acid. This in silico study is expected to be applied to scaffold protein engineering for novel retinoid-binding lipocalins.

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

Access this article

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

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Akerstrom, B., D. R. Flower, and J. P. Salier (2000) Lipocalins: Unity in diversity. Biochim. Biophysica Acta 1482: 1–8.

    Article  CAS  Google Scholar 

  2. Flower, D. R. (1994) The lipocalin protein family: A role in cell regulation. FEBS Lett. 354: 7–11.

    Article  CAS  Google Scholar 

  3. Flower, D. R. (1996) The lipocalin protein family: Structure and function. Biochem. J. 318: 1–14.

    Article  CAS  Google Scholar 

  4. Flower, D. R., A. C. North, and C. E. Sansom (2000) The lipocalin protein family: Structural and sequence overview. Biochim. Biophys. Acta 1482: 9–24.

    Article  CAS  Google Scholar 

  5. Flower, D. R. (1995) Multiple molecular recognition properties of the lipocalin protein family. J. Mol. Recog 8: 185–195.

    Article  CAS  Google Scholar 

  6. Zhang, Y. -R., Y. Q. Zhao, and J. -F. Huang (2012) Retinoidbinding proteins: Similar protein architectures bind similar ligands via completely different ways. PLOS One 7: e36772.

    Article  CAS  Google Scholar 

  7. Xu, S. and P. Venge (2000) Lipocalins as biochemical markers of disease. Biochim. Biophysic. Acta (BBA) - Protein Structure Mol. Enzymol. 1482: 298–307.

    Article  CAS  Google Scholar 

  8. Bolignano, D., V. Donato, G. Coppolino, S. Campo, A. Buemi, A. Lacquaniti, and M. Buemi Neutrophil Gelatinase Associated lipocalin (NGAL) as a marker of kidney damage. Am. J. Kidney Diseases 52: 595–605.

  9. Rodgers, M. A., J. B. C. Findlay, and P. A. Millner (2010) Lipocalin based biosensors for low mass hydrophobic analytes; development of a novel SAM for polyhistidine tagged proteins. Sens. Actuators B: Chem. 150: 12–18.

    Article  CAS  Google Scholar 

  10. Skerra, A. (2000) Lipocalins as a scaffold. Biochim. Biophysic. Acta 1482: 337–350.

    Article  CAS  Google Scholar 

  11. Richter, A., E. Eggenstein, and A. Skerra (2014) Anticalins: Exploiting a non-Ig scaffold with hypervariable loops for the engineering of binding proteins. FEBS Lett. 588: 213–218.

    Article  CAS  Google Scholar 

  12. Schlehuber, S. and A. Skerra (2005) Lipocalins in drug discovery: From natural ligand-binding proteins to “anticalins”. Drug Discovery Today 10: 23–33.

    Article  CAS  Google Scholar 

  13. Blomhoff, R. and H. K. Blomhoff (2006) Overview of retinoid metabolism and function. J. Neurobiol. 66: 606–630.

    Article  CAS  Google Scholar 

  14. Ruiz, M., D. Sanchez, C. Correnti, R. K. Strong, and M. D. Ganfornina (2013) Lipid-binding properties of human ApoD and Lazarillo-related lipocalins: Functional implications for cell differentiation. FEBS J. 280: 3928–3943.

    Article  CAS  Google Scholar 

  15. Breustedt, D. A., D. L. Schonfeld, and A. Skerra (2006) Comparative ligand-binding analysis of ten human lipocalins. Biochimic. Biophysic. Acta 1764: 161–173.

    Article  CAS  Google Scholar 

  16. Cowan, S. W., M. E. Newcomer, and T. A. Jones (1990) Crystallographic refinement of human serum retinol binding protein at 2A resolution. Proteins 8: 44–61.

    Article  CAS  Google Scholar 

  17. Eichinger, A., A. Nasreen, H. J. Kim, and A. Skerra (2007) Structural insight into the dual ligand specificity and mode of high density lipoprotein association of apolipoprotein D. J. Biol. Chem. 282: 31068–31075.

    Article  CAS  Google Scholar 

  18. Morris, G. M., R. Huey, W. Lindstrom, M. F. Sanner, R. K. Belew, D. S. Goodsell, and A. J. Olson (2009) AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J. Computat. Chem. 30: 2785–2791.

    Article  CAS  Google Scholar 

  19. Dassault Systèmes BIOVIA, Discovery Studio Modeling Environment, Release 2017, San Diego. Dassault Systèmes.

    Google Scholar 

  20. Larkin, M. A., G. Blackshields, N. P. Brown, R. Chenna, P. A. McGettigan, H. McWilliam, F. Valentin, I. M. Wallace, A. Wilm, R. Lopez, J. D. Thompson, T. J. Gibson, and D. G. Higgins (2007) Clustal W and Clustal X version 2.0. Bioinformat. 23: 2947–2948.

    Article  CAS  Google Scholar 

  21. Rose, A. S. and P. W. Hildebrand (2015) NGL Viewer: A web application for molecular visualization. Nucleic Acids Res. 43: W576–W579.

    Article  CAS  Google Scholar 

  22. Stothard, P. (2000) The sequence manipulation suite: JavaScript programs for analyzing and formatting protein and DNA sequences. BioTechniq. 28: 1102, 1104.

    CAS  Google Scholar 

  23. The PyMOL Molecular Graphics System, Version 2.0 Schrödinger, LLC.

  24. Warren, G. L., C. W. Andrews, A.-M. Capelli, B. Clarke, J. LaLonde, M. H. Lambert, M. Lindvall, N. Nevins, S. F. Semus, S. Senger, G. Tedesco, I. D. Wall, J. M. Woolven, C. E. Peishoff, and M. S. Head (2006) A critical assessment of docking programs and scoring functions. J. Med. Chem. 49: 5912–5931.

    Article  CAS  Google Scholar 

  25. Zanotti, G., M. Marcello, G. Malpeli, C. Folli, G. Sartori, and R. Berni (1994) Crystallographic studies on complexes between retinoids and plasma retinol-binding protein. J. Biolog. Chem. 269: 29613–29620.

    CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sun-Gu Lee.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Munussami, G., Sokalingam, S., Kim, J.R. et al. In Silico Study on Retinoid-binding Modes in Human RBP and ApoD Lipocalins. Biotechnol Bioproc E 23, 158–167 (2018). https://doi.org/10.1007/s12257-018-0032-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12257-018-0032-z

Keywords

Navigation