Skip to main content
Springer Nature Link
Log in

Demystifying the pH dependent conformational changes of human heparanase pertaining to structure–function relationships: an in silico approach

  • Published:
Journal of Computer-Aided Molecular Design Aims and scope Submit manuscript

Abstract

Heparanase (HPSE) is an endo-β-d-glucuronidase that has diverse functions in mammals which includes cell survival, cell adhesion and cell migration. HPSE features both enzymatic and non-enzymatic functionalities in a pH dependent manner. Hence, in this study, an extensive molecular dynamics simulation, molecular docking, protein Angular dispersion analysis were performed for apo form and holo forms to understand its conformational changes at varied pH conditions. On comparative conformational analysis of apo and holo forms, it was inferred that the HSPE has undergone pH dependent structural changes, thereby affecting the binding of Heparan sulfate proteoglycan (HSPG). Moreover, HPSE also showed favourable structural changes for optimal binding of HSPG at pH 5.0 and 6.0, as inferred from functional flap displacements within HPSE. Thus, this study provides significant insights on optimal pH for HPSE to exhibit its enzymatic activity. The outcome of this study shall aid in ideal lead generation for targeting HPSE mediated disease conditions.

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

Access this article

Log in via an institution

Subscribe and save

Springer+
from $39.99 /Month
  • Starting from 10 chapters or articles per month
  • Access and download chapters and articles from more than 300k books and 2,500 journals
  • Cancel anytime
View plans

Buy Now

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

Explore related subjects

Discover the latest articles, books and news in related subjects, suggested using machine learning.

References

  1. Bame KJ (2001) Heparanases: endoglycosidases that degrade heparan sulfate proteoglycans. Glycobiology 11(6):91R–98

    Article  CAS  PubMed  Google Scholar 

  2. Li J (2008) Heparin, heparan sulfate and heparanase in cancer: remedy for metastasis? Anticancer Agents Med Chem 8(1):64–76

    Article  PubMed  Google Scholar 

  3. Cassinelli G, Zaffaroni N, Lanzi C (2016) The heparanase/heparan sulfate proteoglycan axis: a potential new therapeutic target in sarcomas. Cancer Lett 382(2):245–254. https://doi.org/10.1016/j.canlet.2016.09.004

    Article  CAS  PubMed  Google Scholar 

  4. Ruan J, Trotter TN, Nan L, Luo R, Javed A, Sanderson RD, Suva LJ, Yang Y (2013) Heparanase inhibits osteoblastogenesis and shifts bone marrow progenitor cell fate in myeloma bone disease. Bone 57(1):10–17. https://doi.org/10.1016/j.bone.2013.07.024

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Sanderson RD, Elkin M, Rapraeger AC, Ilan N, Vlodavsky I (2017) Heparanase regulation of cancer, autophagy and inflammation: new mechanisms and targets for therapy. FEBS J 284(1):42–55. https://doi.org/10.1111/febs.13932

    Article  CAS  PubMed  Google Scholar 

  6. Nikitovic D, Mytilinaiou M, Berdiaki A, Karamanos NK, Tzanakakis GN (2014) Heparan sulfate proteoglycans and heparin regulate melanoma cell functions. Biochim Biophys Acta 1840(8):2471–2481. https://doi.org/10.1016/j.bbagen.2014.01.031

    Article  CAS  PubMed  Google Scholar 

  7. Jin H, Zhou S (2017) The functions of heparanase in human diseases. Mini Rev Med Chem 17(6):541–548. https://doi.org/10.2174/1389557516666161101143643

    Article  CAS  PubMed  Google Scholar 

  8. Fux L, Feibish N, Cohen-Kaplan V, Gingis-Velitski S, Feld S, Geffen C, Vlodavsky I, Ilan N (2009) Structure-function approach identifies a COOH-terminal domain that mediates heparanase signaling. Cancer Res 69(5):1758–1767. https://doi.org/10.1158/0008-5472.CAN-08-1837

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Abboud-Jarrous G, Rangini-Guetta Z, Aingorn H, Atzmon R, Elgavish S, Peretz T, Vlodavsky I (2005) Site-directed mutagenesis, proteolytic cleavage, and activation of human proheparanase. J Biol Chem 280(14):13568–13575. https://doi.org/10.1074/jbc.M413370200

    Article  CAS  PubMed  Google Scholar 

  10. Fairbanks MB, Mildner AM, Leone JW, Cavey GS, Mathews WR, Drong RF, Slightom JL, Bienkowski MJ, Smith CW, Bannow CA, Heinrikson RL (1999) Processing of the human heparanase precursor and evidence that the active enzyme is a heterodimer. J Biol Chem 274(42):29587–29590

    Article  CAS  PubMed  Google Scholar 

  11. Levy-Adam F, Miao H, Heinrikson RL, Vlodavsky I, Ilan N (2003) Heterodimer formation is essential for heparanase enzymatic activity. Biochem Biophys Res Commun 308(4):885–891. https://doi.org/10.1016/S0006-291X(03)01478-5

    Article  CAS  PubMed  Google Scholar 

  12. Gandhi NS, Freeman C, Parish CR, Mancera RL (2012) Computational analyses of the catalytic and heparin-binding sites and their interactions with glycosaminoglycans in glycoside hydrolase family 79 endo-β-D-glucuronidase (heparanase). Glycobiology 22(1):35–55. https://doi.org/10.1093/glycob/cwr095

    Article  CAS  PubMed  Google Scholar 

  13. Levy-Adam F, Abboud-Jarrous G, Guerrini M, Beccati D, Vlodavsky I, Ilan N (2005) Identification and characterization of heparin/heparan sulfate binding domains of the endoglycosidase heparanase. J Biol Chem 280(21):20457–20466. https://doi.org/10.1074/jbc.M414546200

    Article  CAS  PubMed  Google Scholar 

  14. Sapay N, Cabannes E, Petitou M, Imberty A (2012) Molecular model of human heparanase with proposed binding mode of a heparan sulfate oligosaccharide and catalytic amino acids. Biopolymers 97(1):21–34. https://doi.org/10.1002/bip.21696

    Article  CAS  PubMed  Google Scholar 

  15. Pala D, Rivara S, Mor M, Milazzo FM, Roscilli G, Pavoni E, Giannini G (2016) Kinetic analysis and molecular modeling of the inhibition mechanism of roneparstat (SST0001) on human heparanase. Glycobiology 26(6):640–654. https://doi.org/10.1093/glycob/cww003

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Wu L, Viola CM, Brzozowski AM, Davies GJ (2015) Structural characterization of human heparanase reveals insights into substrate recognition. Nat Struct Mol Biol 22(12):1016–1022. https://doi.org/10.1038/nsmb.3136

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Vlodavsky I, Ilan N, Naggi A, Casu B (2007) Heparanase: structure, biological functions, and inhibition by heparin-derived mimetics of heparan sulfate. Curr Pharm Des 13(20):2057–2073

    Article  CAS  PubMed  Google Scholar 

  18. Ragazzi M, Ferro DR, Provasoli A (1986) A force-field study of the conformational characteristics of the iduronate ring. J Comput Chem 7(2):105–112. https://doi.org/10.1002/jcc.540070203

    Article  CAS  PubMed  Google Scholar 

  19. Okada Y, Yamada S, Toyoshima M, Dong J, Nakajima M, Sugahara K (2002) Structural recognition by recombinant human heparanase that plays critical roles in tumor metastasis. Hierarchical sulfate groups with different effects and the essential target disulfated trisaccharide sequence. J Biol Chem 277(45):42488–42495. https://doi.org/10.1074/jbc.M206510200

    Article  CAS  PubMed  Google Scholar 

  20. Marchetti D, Liu S, Spohn WC, Carson DD (1997) Heparanase and a synthetic peptide of heparan sulfate-interacting protein recognize common sites on cell surface and extracellular matrix heparan sulfate. J Biol Chem 272(25):15891–15897

    Article  CAS  PubMed  Google Scholar 

  21. Mulloy B, Forster MJ (2000) Conformation and dynamics of heparin and heparan sulfate. Glycobiology 10(11):1147–1156

    Article  CAS  PubMed  Google Scholar 

  22. Verli H (2006) Insights into carbohydrate structure and biological function: 2006/editor, Hugo Verli. Transworld Research Network, Trivandrum

    Google Scholar 

  23. Dreyfuss JL, Regatieri CV, Jarrouge TR, Cavalheiro RP, Sampaio LO, Nader HB (2009) Heparan sulfate proteoglycans: structure, protein interactions and cell signaling. Ann Braz Acad Sci 81(3):409–429

    Article  CAS  Google Scholar 

  24. Shriver Z, Capila I, Venkataraman G, Sasisekharan R (2012) Heparin and heparan sulfate: analyzing structure and microheterogeneity. Handb Exp Pharmacol 207:159–176. https://doi.org/10.1007/978-3-642-23056-1_8

    Article  CAS  Google Scholar 

  25. Lever R, Page CP (2002) Novel drug development opportunities for heparin. Nat Rev Drug Discov 1(2):140–148. https://doi.org/10.1038/nrd724

    Article  CAS  PubMed  Google Scholar 

  26. Sarrazin S, Lamanna WC, Esko JD (2011) Heparan sulfate proteoglycans. Cold Spring Harb Perspect Biol 3(7). https://doi.org/10.1101/cshperspect.a004952

  27. Peterson SB, Liu J (2013) Multi-faceted substrate specificity of heparanase. Matrix Biol 32(5):223–227. https://doi.org/10.1016/j.matbio.2013.02.006

    Article  CAS  PubMed  Google Scholar 

  28. Rivara S, Milazzo FM, Giannini G (2016) Heparanase: a rainbow pharmacological target associated to multiple pathologies including rare diseases. Future Med Chem 8(6):647–680. https://doi.org/10.4155/fmc-2016-0012

    Article  CAS  PubMed  Google Scholar 

  29. Zetser A, Bashenko Y, Miao H, Vlodavsky I, Ilan N (2003) Heparanase affects adhesive and tumorigenic potential of human glioma cells. Cancer Res 63(22):7733–7741

    CAS  PubMed  Google Scholar 

  30. Hulett MD, Hornby JR, Ohms SJ, Zuegg J, Freeman C, Gready JE, Parish CR (2000) Identification of active-site residues of the pro-metastatic endoglycosidase heparanase. Biochemistry 39(51):15659–15667

    Article  CAS  PubMed  Google Scholar 

  31. Gilat D, Hershkoviz R, Goldkorn I, Cahalon L, Korner G, Vlodavsky I, Lider O (1995) Molecular behavior adapts to context: heparanase functions as an extracellular matrix-degrading enzyme or as a T cell adhesion molecule, depending on the local pH. J Exp Med 181(5):1929–1934

    Article  CAS  PubMed  Google Scholar 

  32. Toyoshima M, Nakajima M (1999) Human heparanase. Purification, characterization, cloning, and expression. J Biol Chem 274(34):24153–24160

    Article  CAS  PubMed  Google Scholar 

  33. Goldshmidt O, Zcharia E, Cohen M, Aingorn H, Cohen I, Nadav L, Katz B, Geiger B, Vlodavsky I (2003) Heparanase mediates cell adhesion independent of its enzymatic activity. FASEB J 17(9):1015–1025. https://doi.org/10.1096/fj.02-0773com

    Article  CAS  PubMed  Google Scholar 

  34. Stringer SE (2006) The role of heparan sulphate proteoglycans in angiogenesis. Biochem Soc Trans 34(Pt 3):451–453. https://doi.org/10.1042/BST0340451

    Article  CAS  PubMed  Google Scholar 

  35. Raman R, Venkataraman G, Ernst S, Sasisekharan V, Sasisekharan R (2003) Structural specificity of heparin binding in the fibroblast growth factor family of proteins. Proc Natl Acad Sci 100(5):2357–2362. https://doi.org/10.1073/pnas.0437842100

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Schlessinger J, Plotnikov AN, Ibrahimi OA, Eliseenkova AV, Yeh BK, Yayon A, Linhardt RJ, Mohammadi M (2000) Crystal structure of a ternary FGF-FGFR-heparin complex reveals a dual role for heparin in FGFR binding and dimerization. Mol Cell 6(3):743–750

    Article  CAS  PubMed  Google Scholar 

  37. Vlodavsky I, Friedmann Y (2001) Molecular properties and involvement of heparanase in cancer metastasis and angiogenesis. J Clin Invest 108(3):341–347. https://doi.org/10.1172/JCI13662

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov IN, Bourne PE (2000) The protein data bank. Nucleic Acids Res 28(1):235–242

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Vadlamudi Y, Muthu K, Kumar S (2016) Structural exploration of acid sphingomyelinase at different physiological pH through molecular dynamics and docking studies. RSC Adv 6(78):74859–74873. https://doi.org/10.1039/C6RA16584B

    Article  CAS  Google Scholar 

  40. Borkotoky S, Kumar Meena C, Bhalerao GM, Murali A (2017) An in-silico glimpse into the pH dependent structural changes of T7 RNA polymerase: a protein with simplicity. Sci Rep 7(1):6290. https://doi.org/10.1038/s41598-017-06586-1

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Abraham MJ, Murtola T, Schulz R, Páll S, Smith JC, Hess B, Lindahl E (2015) GROMACS: high performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX 1–2:19–25. https://doi.org/10.1016/j.softx.2015.06.001

    Article  Google Scholar 

  42. Oostenbrink C, Villa A, Mark AE, van Gunsteren WF (2004) A biomolecular force field based on the free enthalpy of hydration and solvation: the GROMOS force-field parameter sets 53A5 and 53A6. J Comput Chem 25(13):1656–1676. https://doi.org/10.1002/jcc.20090

    Article  CAS  PubMed  Google Scholar 

  43. Gordon JC, Myers JB, Folta T, Shoja V, Heath LS, Onufriev A (2005) H++: a server for estimating pKas and adding missing hydrogens to macromolecules. Nucleic Acids Res 33(Web Server issue):W368–W371. https://doi.org/10.1093/nar/gki464

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Berendsen HJC, Postma JPM, van Gunsteren WF, DiNola A, Haak JR (1984) Molecular dynamics with coupling to an external bath. J Chem Phys 81(8):3684–3690. https://doi.org/10.1063/1.448118

    Article  CAS  Google Scholar 

  45. Hess B, Bekker H, Berendsen HJC, Fraaije JG (1997) LINCS: a linear constraint solver for molecular simulations. J Comput Chem 18(12):1463–1472. https://doi.org/10.1002/(SICI)1096-987X(199709)18:12%3C1463:AID-JCC4%3E3.0.CO;2-H

    Article  CAS  Google Scholar 

  46. Papaleo E, Mereghetti P, Fantucci P, Grandori R, Gioia L de (2009) Free-energy landscape, principal component analysis, and structural clustering to identify representative conformations from molecular dynamics simulations: the myoglobin case. J Mol Graph Model 27(8):889–899. https://doi.org/10.1016/j.jmgm.2009.01.006

    Article  CAS  PubMed  Google Scholar 

  47. Maisuradze GG, Liwo A, Scheraga HA (2009) Principal component analysis for protein folding dynamics. J Mol Biol 385(1):312–329. https://doi.org/10.1016/j.jmb.2008.10.018

    Article  CAS  PubMed  Google Scholar 

  48. Amadei A, Linssen AB, Berendsen HJ (1993) Essential dynamics of proteins. Proteins 17(4):412–425. https://doi.org/10.1002/prot.340170408

    Article  CAS  PubMed  Google Scholar 

  49. Bakan A, Meireles LM, Bahar I (2011) ProDy: protein dynamics inferred from theory and experiments. Bioinformatics 27(11):1575–1577. https://doi.org/10.1093/bioinformatics/btr168

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Humphrey W, Dalke A, Schulten K (1996) VMD: visual molecular dynamics. J Mol Graph 14(1):33–38

    Article  CAS  PubMed  Google Scholar 

  51. Caliandro R, Rossetti G, Carloni P (2012) Local fluctuations and conformational transitions in proteins. J Chem Theory Comput 8(11):4775–4785. https://doi.org/10.1021/ct300610y

    Article  CAS  PubMed  Google Scholar 

  52. Teilum K, Olsen JG, Kragelund BB (2011) Protein stability, flexibility and function. Biochim Biophys Acta 1814(8):969–976. https://doi.org/10.1016/j.bbapap.2010.11.005

    Article  CAS  PubMed  Google Scholar 

  53. Camejo G, Hurt-Camejo E, Wiklund O, Bondjers G (1998) Association of apo B lipoproteins with arterial proteoglycans: pathological significance and molecular basis. Atherosclerosis 139(2):205–222

    Article  CAS  PubMed  Google Scholar 

  54. Molecular Operating Environment (MOE),(2013.08). 1010 Sherbooke St. West, Suite #910, Montreal, QC, Canada, H3A 2R7: Chemical Computing Group Inc., 2013 (2018)

  55. Vilar S, Cozza G, Moro S (2008) Medicinal chemistry and the molecular operating environment (MOE): application of QSAR and molecular docking to drug discovery. CTMC 8(18):1555–1572. https://doi.org/10.2174/156802608786786624

    Article  CAS  Google Scholar 

Download references

Acknowledgements

This study was possible due to hardware support provided by SCOPE International and software license procured under DST-SERB YSS scheme [File No. YSS/2014/000282]. We also acknowledge Mr. Samdani. A, Senior Research Fellow, Centre for Bioinformatics, Vision Research Foundation for his support in some of the technical aspects.

Author information

Authors and Affiliations

  1. Centre for Bioinformatics, Kamalnayan Bajaj Institute for Research in Vision and Ophthalmology, Vision Research Foundation, Sankara Nethralaya, Chennai, Tamilnadu, 600 006, India

    Hemavathy Nagarajan & Umashankar Vetrivel

Authors
  1. Hemavathy Nagarajan
    View author publications

    Search author on:PubMed Google Scholar

  2. Umashankar Vetrivel
    View author publications

    Search author on:PubMed Google Scholar

Corresponding author

Correspondence to Umashankar Vetrivel.

Ethics declarations

Conflict of interest

Authors declare no conflict of interest.

Ethical approval

This is purely a computational work and does not involve any animal studies.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 16032 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Nagarajan, H., Vetrivel, U. Demystifying the pH dependent conformational changes of human heparanase pertaining to structure–function relationships: an in silico approach. J Comput Aided Mol Des 32, 821–840 (2018). https://doi.org/10.1007/s10822-018-0131-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10822-018-0131-0

Keywords