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In silico prediction of a new lead compound targeting enolase of trypanosomatids through structure-based virtual screening and molecular dynamic studies


Enolase is one of the key glycolytic metalloenzyme in many organisms, and it is a potential therapeutic target including trypanosomatids. Sequence and structural analysis of enolase of Trypanosoma bruzi (TbENO), Trypanosoma cruzi (TcENO) and Leishmania donovani (LdENO) revealed conserved sequence pattern and structural features. Hence identification of an inhibitor against enolase of one trypanosomatid organism may have similar effects on enolase of homologous organisms belonging to same family. In the process to identify potent inhibitor compounds against TbENO by in silico methods, compounds containing the substructures of substrate, i.e. phosphoenolpyruvate (PEP) and the well-known inhibitors, fluoro-2-phosphono-acetohydroxamate (FPAH) and phosphono-acetohydroxamate (PAH), were collected. Virtual screening and induced fit docking studies were carried out to explore compounds that have better binding affinity than PEP and FPAH. PPPi was found to be the top hit exhibiting significant binding affinity towards enolase. Glide energy values of two other compounds represented by PubChem ID: 511392 and 101803456 was in good agreement with PEP and PAH. TbENO-PPPi complex was subjected to molecular orbital analysis and molecular dynamic studies by considering its remarkable binding affinity as it could be a potent inhibitor of enolase. Despite being an endogenous compound, based on the results of this study, we highlight PPPi to be a lead compound, and its structure can be treated as a model for further chemical modifications to obtain more potent antagonists.

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  1. 1.

    Podlipaev S (2001) The more insect trypanosomatids under study-the more diverse Trypanosomatidae appears. Int J Parasitol 31:648–652.

  2. 2.

    Nussbaum K, Honek J, Cadmus C, Efferth T (2010) Trypanosomatid parasites causing neglected diseases. Curr Med Chem 17:1594–1617.

  3. 3.

    Singh N, Kumar M, Singh RK (2012) Leishmaniasis : current status of available drugs and new potential drug targets. Asian Pac J Trop Med 5:485–497.

  4. 4.

    Lebioda L, Stec B (1991) Mechanism of Enolase: the crystal structure of Enolase-Mg2+-2-Phosphoglycerate/Phosphoenolpyruvate complex at 2.2-Å resolution. Biochemistry 30:2817–2822.

  5. 5.

    Schulz EC, Tietzel M, Tovy A et al (2011) Structure analysis of Entamoeba histolytica enolase. Acta Crystallogr Sect D Biol Crystallogr D67:619–627.

  6. 6.

    Wu Y, Wang C, Lin S et al (2015) Octameric structure of Staphylococcus aureus enolase in complex with phosphoenolpyruvate. Acta Crystallogr Sect D Biol Crystallogr 71:2457–2470.

  7. 7.

    Ehinger S, Schubert WD, Bergmann S et al (2004) Plasmin(ogen)-binding α-Enolase from Streptococcus pneumoniae: crystal structure and evaluation of plasmin(ogen)-binding sites. J Mol Biol 343:997–1005.

  8. 8.

    Kang HJ, Jung SK, Kim SJ, Chung SJ (2008) Structure of human α-enolase (hENO1), a multifunctional glycolytic enzyme. Acta Crystallogr Sect D Biol Crystallogr D64:651–657.

  9. 9.

    Cork AJ, Ericsson DJ, Law RHP et al (2015) Stability of the octameric structure affects plasminogen-binding capacity of streptococcal enolase. PLoS One 10:1–18.

  10. 10.

    Vanegas G, Quiñones W, Carrasco-López C et al (2007) Enolase as a plasminogen binding protein in Leishmania mexicana. Parasitol Res 101:1511–1516.

  11. 11.

    Almeida L, Vanegas G, Calcagno M et al (2004) Plasminogen interaction with Trypanosoma cruzi. Mem Inst Oswaldo Cruz 99:63–67.

  12. 12.

    Antúnez K, Anido M, Arredondo D et al (2011) Paenibacillus larvae enolase as a virulence factor in honeybee larvae infection. Vet Microbiol 147:83–89.

  13. 13.

    Capello M, Ferri-Borgogno S, Cappello P, Novelli F (2011) α-Enolase: a promising therapeutic and diagnostic tumor target. FEBS J 278:1064–1074.

  14. 14.

    Weng Y, Chen F, Liu Y et al (2016) Pseudomonas aeruginosa enolase influences bacterial tolerance to oxidative stresses and virulence. Front Microbiol 7:1–12.

  15. 15.

    Kühnel K, Luisi BF (2001) Crystal structure of the Escherichia coli RNA degradosome component enolase. J Mol Biol 313:583–592.

  16. 16.

    Verlinde CLMJ, Hannaert V, Blonski C et al (2001) Glycolysis as a target for the design of new anti-trypanosome drugs. Drug Resist Updat 4:50–65.

  17. 17.

    Hannaert V, Albert MA, Rigden DJ et al (2003) Kinetic characterization, structure modelling studies and crystallization of Trypanosoma brucei enolase. Eur J Biochem 270:3205–3213.

  18. 18.

    Engel JC, Franke de Cazzulo BM, Stoppani AOM et al (1987) Aerobic glucose fermentation by Trypanosoma cruzi axenic culture amastigote-like forms during growth and differentiation to epimastigotes. Mol Biochem Parasitol 26:1–10.

  19. 19.

    Albert MA, Haanstra JR, Hannaert V et al (2005) Experimental and in silico analyses of glycolytic flux control in bloodstream form Trypanosoma brucei. J Biol Chem 280:28306–28315.

  20. 20.

    Naderer T, Ellis MA, Sernee MF et al (2006) Virulence of Leishmania major in macrophages and mice requires the gluconeogenic enzyme fructose-1,6-bisphosphatase. Proc Natl Acad Sci 103:5502–5507.

  21. 21.

    Maldonado J, Marina C, Puig J et al (2006) A study of cutaneous lesions caused by Leishmania mexicana in plasminogen-deficient mice. Exp Mol Pathol 80:289–294.

  22. 22.

    Cimasoni G (1972) The inhibition of Enolase by fluoride in vitro. Caries Res 6:93–102.

  23. 23.

    Qin J, Chai G, Brewer JM et al (2006) Fluoride inhibition of Enolase: crystal structure and thermodynamics. Biochemistry 45:793–800.

  24. 24.

    Anderson VE, Weiss PM, Cleland WW (1984) Reaction intermediate analogues for Enolase. Biochemistry 23:2779–2786.

  25. 25.

    de AS Navarro MV, Gomes Dias SM, Mello LV et al (2007) Structural flexibility in Trypanosoma brucei enolase revealed by X-ray crystallography and molecular dynamics. FEBS J 274:5077–5089.

  26. 26.

    Leonard PG, Satani N, Maxwell D et al (2016) SF2312 is a natural phosphonate inhibitor of Enolase Paul. Nat Chem Biol 12:1053–1058.

  27. 27.

    Muller et al (2018) Enolase inhibitors and methods of treatment therewith. Global Patent Index - EP 3268376 A1

  28. 28.

    Avilán L, Gualdrón-López M, Quiñones W et al (2011) Enolase: a key player in the metabolism and a probable virulence factor of trypanosomatid parasites - perspectives for its use as a therapeutic target. Enzyme Res 2011.

  29. 29.

    Cáceres AJ, Portillo R, Acosta H et al (2003) Molecular and biochemical characterization of hexokinase from Trypanosoma cruzi. Mol Biochem Parasitol 126:251–262.

  30. 30.

    Sievers F, Wilm A, Dineen D et al (2011) Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal omega. Mol Syst Biol 7.

  31. 31.

    Robert X, Gouet P (2014) Deciphering key features in protein structures with the new ENDscript server. Nucleic Acids Res 42:320–324.

  32. 32.

    Protein Preparation Wizard [Schrödinger Suite 2017–2] Schrödinger, LLC, NewYork, NY, 2017

  33. 33.

    Jorgensen WL, Tirado-rives J (1988) The OPLS potential functions for proteins. Energy minimizations for crystals of cyclic peptides and Crambin. J Am Chem Soc 110:1657–1666.

  34. 34.

    Da Silva Giotto MT, Hannaert V, Vertommen D et al (2003) The crystal structure of Trypanosoma brucei enolase: visualisation of the inhibitory metal binding site III and potential as target for selective, irreversible inhibition. J Mol Biol 331:653–665.

  35. 35.

    SiteMap [Schrödinger Suite 2017–2] Schrödinger, LLC, New York, NY, 2017

  36. 36.

    LigPrep [Schrödinger Suite 2017–2] Schrödinger, LLC, New York, NY, 2017

  37. 37.

    Lipinski CA, Lombardo F, Dominy BW, Feeney PJ (2001) Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev 46:3–26.

  38. 38.

    Epik [Schrödinger Suite 2017–2] Schrödinger, LLC, New York, NY, 2017

  39. 39.

    Glide [Schrödinger Suite 2017–2] Schrödinger, LLC, New York, NY, 2017

  40. 40.

    Induced Fit Docking [Schrödinger Suite 2017–2] Schrödinger, LLC, New York, NY, 2017

  41. 41.

    Yang Z, Lasker K, Schneidman-duhovny D et al (2012) UCSF chimera, MODELLER, and IMP : an integrated modeling system. J Struct Biol J 179:269–278.

  42. 42.

    Melo F, Sánchez R, Sali A (2002) Statistical potentials for fold assessment. Protein Sci 11:430–448.

  43. 43.

    Pieper U, Webb BM, Barkan DT et al (2011) ModBase, a database of annotated comparative protein structure models, and associated resources. Nucleic Acids Res 39:465–474.

  44. 44.

    Laskowski AR (1993) PROCHECK: a program to check the stereochemical quality of protein structures 26:283–291.

  45. 45.

    Arnold K, Bordoli L, Kopp J, Schwede T (2006) The SWISS-MODEL workspace: a web-based environment for protein structure homology modelling. Bioinformatics 22:195–201.

  46. 46.

    Wiederstein M, Sippl MJ (2007) ProSA-web : interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Res 35:407–410.

  47. 47.

    Jaguar [Schrödinger Suite 2017–2] Schrödinger, LLC, New York, NY, 2017

  48. 48.

    Becke AD (2014) A new mixing of Hartree–Fock and local density-functional theories. J Chem Phys 98:1372–1377.

  49. 49.

    Lindahl E, Hess B (2001) GROMACS 3.0 : a package for molecular simulation and trajectory analysis. J Mol Model 7:306–317.

  50. 50.

    Van Der Spoel D, Lindahl E, Hess B, Groenhof G (2005) GROMACS: fast, flexible, and free. J Comput Chem 26:1701–1718.

  51. 51.

    Jo S, Kim T, Iyer VG, Im W (2008) Software news and updates CHARMM-GUI : a web-based graphical user Interface for CHARMM. J Comput Chem 29:1859–1865.

  52. 52.

    Lee J, Cheng X, Swails JM et al (2016) CHARMM-GUI input generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM simulations using the CHARMM36 additive force field. J Chem Theory Comput 12:405–413.

  53. 53.

    Vanommeslaeghe K, Hatcher E, Acharya C et al (2010) CHARMM general force field (CGenFF): a force field for drug-like molecules compatible with the CHARMM all-atom additive biological force fields. J Comput Chem 31:671–690.

  54. 54.

    Floden AM, Watt JA, Brissette CA (2011) Borrelia burgdorferi Enolase is a surface-exposed plasminogen binding protein. PLoS One 6:1–9.

  55. 55.

    Hsiao K, Shih N, Fang H et al (2013) Surface α-Enolase promotes extracellular matrix degradation and tumor metastasis and represents a new therapeutic target. PLoS One 8:1–15.

  56. 56.

    Fujii A, Yoneda M, Ito T et al (2005) Autoantibodies against the amino terminal of α-enolase are a useful diagnostic marker of Hashimoto’s encephalopathy. J Neuroimmunol 162:130–136.

  57. 57.

    Saranya M, Ayyappan S, Nithya R et al (2018) Molecular structure, NBO and HOMO-LUMO analysis of quercetin on single layer graphene by density functional theory. Dig J Nanomater Biostruct 13:97–105

  58. 58.

    Pearson RG (1986) Absolute electronegativity and hardness correlated with molecular orbital theory. Proc Natl Acad Sci U S A 83:8440–8441

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KP gratefully acknowledges the Department of Biotechnology (DBT), Government of India for the financial support in the form of grants (No.BT/273/NE/TBP/2011) under North Eastern Region Twinning Programme. KP thanks DST-FIST, Government of India for computing facility sanctioned to the department (No: SR/FST/LSII-037/2014 (C) dt.29.03.2016). VMV thanks DBT for the fellowship. Dr. BSL acknowledges the financial support of the DBT – BUILDER (BT/PR12153/INF/22/200/2014) programme for the computational resources and the HPC computing facility at Anna University.

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Correspondence to Karthe Ponnuraj.

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Vidhya, V.M., Lakshmi, B.S. & Ponnuraj, K. In silico prediction of a new lead compound targeting enolase of trypanosomatids through structure-based virtual screening and molecular dynamic studies. J Mol Model 26, 23 (2020).

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  • Enolase
  • Trypanosomatids
  • Virtual screening
  • Enolase inhibitor
  • PPPi
  • Molecular dynamic simulation