Skip to main content

Advertisement

SpringerLink
Log in

Potential acetylcholinesterase inhibitors: molecular docking, molecular dynamics, and in silico prediction

  • Original Paper
  • Published:
Journal of Molecular Modeling Aims and scope Submit manuscript

Abstract

This paper deals with molecular modeling of new therapeutic agents for treating the Alzheimer’s disease. The therapeutic line adopted for this study is the cholinergic hypothesis. To modulate positively the cholinergic function through the inhibition of the acetylcholinesterase, a set of candidates was designed from a natural compound extracted from the cashew nutshell liquid, anacardic acid. In silico screening of this chemical library revealed a ligand that is more promising once it is correlated with an active drug through specific topological and electronic descriptors. The protein–ligand docking showed stable binding modes and the binding free energy computed for the active site of the receptor suggests that our ligand presents a potential biological response.

Representation of the three dimensional structure of the AChE, showing the important binding sites of the Gorge and the conformation of the ligand

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

Access this article

Log in via an institution

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
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15

Similar content being viewed by others

References

  1. Alzheimer A (1906) Über einen eigenartigen schweren Erkrankungsproze β der Hirnrinde. Neurologisches Centralblatt 23:1129–1136

    Google Scholar 

  2. Francis PT, Palmer AM, Snape M, Wilcock GK (1999) The cholinergic hypothesis of Alzheimer’s disease: a review of progress. J Neurol Neurosurg Psychiatry 66:137–147

    Article  CAS  Google Scholar 

  3. Goedert M, Spillantini MGA (2006) Century of Alzheimer’s disease. Science 314:777–781

    Article  CAS  Google Scholar 

  4. Morley JE (2011) Anticholinergic medications and cognition. J Am Med Dir Assoc 12:543–543

    Article  Google Scholar 

  5. Igbal K, Grundke-Igbal I (2000) Alzheimer disease is multifactorial and heterogeneous. Neurobiol Aging 21:901–902

    Article  Google Scholar 

  6. Jellinger KA (2006) Alzheimer 100–highlights in the history of Alzheimer research. J Neural Transm 113:1603–1623

    Article  CAS  Google Scholar 

  7. Castro A, Martinez A (2006) Targeting beta-amyloid pathogenesis through acetylcholinesterase inhibitors. Curr Pharm Des 12:4377–4387

    Article  CAS  Google Scholar 

  8. Karran E, Mercken M, Strooper BD (2011) The amyloid cascade hypothesis for Alzheimer’s disease: an appraisal for the development of therapeutics. Nature Rev Drug Discov 10:698–712

    Article  CAS  Google Scholar 

  9. Alonso AC, Grundke-Igbal I, Igbal K (1996) Alzheimer’s disease hyperphosphorylated tau sequesters normal tau into tangles of filaments and disassembles microtubules. Nat Med 2:783–787

    Article  CAS  Google Scholar 

  10. Andersen JK (2004) Oxidative stress in neurodegeneration: cause or consequence Nat Med 10:S18–25

    Article  Google Scholar 

  11. Dumont M, Beal MF (2011) Neuroprotective strategies involving ROS in Alzheimer disease. Free Rad Biol Med 51:1014–1026

    Article  CAS  Google Scholar 

  12. Cummings JL (2004) Treatment of Alzheimer’s disease: current and future therapeutic approaches. Rev Neurol Dis 1:60–69

    Google Scholar 

  13. Mangialasche F, Solomon A, Winblad B (2010) Alzheimer’s disease: clinical trials and drug development. Lancet Neurol 9:702–716

    Article  CAS  Google Scholar 

  14. Shafferman A, Kronman C, Flashner Y, Leitner M, Grosfeld H, Ordentlich A, Gozes Y, Cohen S, Ariel N, Barak D (1992) Mutagenesis of human acetylcholinesterase. Identif Resid Invol Catalyt Activ Polypep Fold 267:17640–17648

    CAS  Google Scholar 

  15. Dvira H, Silmanb I, Harela M, Rosenberryc TL, Sussman JL (2010) Acetylcholinesterase: from 3D structure to function. Chemico-Biol Interact 187:10–22

    Article  Google Scholar 

  16. Bennion BJ, Essiz SG, Lau EY, Fattebert J-L, Emigh A, Lightstone FC (2015) A wrench in the works of human acetylcholinesterase: soman induced conformational changes revealed by molecular dynamics simulations. PLoS ONE 10:1–31

    Article  Google Scholar 

  17. Phillips JC, Braun R, Wang W, Gumbart J, Tajkhorshid E, Villa E, Chipot C, Skeel RD, Kale L, Schulten K (2005) Scalable molecular dynamics with NAMD. J Comput Chem 26:1781–1802

    Article  CAS  Google Scholar 

  18. Martins JBL, Neves AA, Gargano R, Santos ML, Romeiro LAS (2007) Electronic structure calculations toward new potentially AChE inhibitors. Chem Phys Lett 446:304–308

    Article  Google Scholar 

  19. De Paula AAN, Martins JBL, Santos ML, Nascente LC, Romeiro LAS, Areas TFMA, Vieira KST, Gambo NF, Castro NG, Gargano R (2009) New potential AChE inhibitor candidates. Eur J Med Chem 44:3754–3759

    Article  CAS  Google Scholar 

  20. Kiametis AS, Martins JBL, Romeiro LAS, Gargano R (2013) Acetylcholinesterase inhibitors: modeling potential candidates. Int J Quantum Chem 113:1461–1466

    Article  CAS  Google Scholar 

  21. Nascimento ECM, Martins JBL (2011) Electronic structure and PCA analysis of covalent and non-covalent acetylcholinesterase inhibitors. J Mol Model 17:1371–1379

    Article  CAS  Google Scholar 

  22. Nascimento ECM, Martins JBL, Gargano R, Santos ML (2008) Theoretical study of classical acetylcholinesterase inhibitors. Chem Phys Lett 458:285–289

    Article  CAS  Google Scholar 

  23. Samochochi M, Hoffle A, Fehrenbacher A, Jostock R, Ludwig J, Christner C, Radina M, Zerlim M, Ullmer C, Pereira E, Lubbert H, Albuquerque E (2003) Galantamine is an allosterically potentiating ligand of neuronal nicotinic but not of muscarinic acetylcholine receptors. J Pharmacol Exp Ther 305:1024–1036

    Article  Google Scholar 

  24. Cheung J, Rudolph M, Burshteyn F, Cassidy M, Gary E, Love J, Height J, Franklin M (2012) Structures of human acetylcholinesterase in complex with pharmacologically important ligands. J Med Chem 55:10282–10288

    Article  CAS  Google Scholar 

  25. Raevsky OA (2004) Physicochemical descriptors in property-based drug design. Mini Rev Med Chem 4:1041–1052

    Article  CAS  Google Scholar 

  26. Sakkiah S, Lee KW (2012) Pharmacophore-based virtual screening and density functional theory approach to identifying novel butyrylcholinesterase inhibitors. Acta Pharmacol Sin 33:964–978

    Article  CAS  Google Scholar 

  27. Frisch MJ, Trucks GW, Schlegel HB, Scuseria GE, Robb MA, Cheeseman JR, Montgomery JA Jr, Vreven T, Kudin KN, Burant JC, Millam JM, Iyengar SS, Tomasi J, Barone V, Mennucci B, Cossi M, Scalmani G, Rega N, Petersson GA, Nakatsuji H, Hada M, Ehara M, Toyota K, Fukuda R, Hasegawa J, Ishida M, Nakajima T, Honda Y, Kitao O, Nakai H, Klene M, Li X, Knox JE, Hratchian HP, Cross JB, Adamo C, Jaramillo J, Gomperts R, Stratmann RE, Yazyev O, Austin AJ, Cammi R, Pomelli C, Ochterski JW, Ayala PY, Morokuma K, Voth GA, Salvador P, Dannenberg JJ, Zakrzewski VG, Dapprich S, Daniels AD, Strain MC, Farkas O, Malick DK, Rabuck AD, Raghavachari K, Foresman JB, Ortiz JV, Cui Q, Baboul AG, Clifford S, Cioslowski J, Stefanov BB, Liu G, Liashenko A, Piskorz P, Komaromi I, Martin RL, Fox D J, Keith T, Al-Laham MA, Peng CY, Nanayakkara A, Challacombe M, Gill PMW, Johnson B, Chen W, Wong MW, Gonzalez C, Pople JA (2009). Gaussian09, Inc., Wallingford, CT, USA, Gaussian, Inc., Wallingford, CT

  28. HyperChem Computational Chemistry (1996). Hypercube Inc., New York

  29. Trott O, Olson AJ (2010) AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization and multithreading. J Comput Chem 31:455–461

    CAS  Google Scholar 

  30. Smart OS, Neduvelil JG, Wang X, Wallace BA, Sansom MSP (1996) HOLE: A program for the analysis of the pore dimensions of ion channel structural models. J Mol Graph 14:354–360

    Article  CAS  Google Scholar 

Download references

Acknowledgments

The authors gratefully acknowledge the financial support from the Brazilian Research Councils CAPES, CNPq, FINATEC, FAPDF, and the computational support of LBTC-UnB.

Author information

Authors and Affiliations

  1. Institute of Biology, University of Brasilia, Brasilia, Brazil

    Alessandra S. Kiametis

  2. Institute of Physics, University of Brasilia, Brasilia, Brazil

    Mônica A. Silva & Ricardo Gargano

  3. Departament of Tropical Medicine, University of Brasilia, Brasilia, Brazil

    Luiz A. S. Romeiro

  4. Institute of Chemistry, University of Brasilia, Brasilia, Brazil

    João B. L. Martins

Authors
  1. Alessandra S. Kiametis
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mônica A. Silva
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Luiz A. S. Romeiro
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. João B. L. Martins
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ricardo Gargano
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mônica A. Silva.

Additional information

This paper belongs to Topical Collection VI Symposium on Electronic Structure and Molecular Dynamics – VI SeedMol

Electronic supplementary material

Below is the link to the electronic supplementary material.

(PDF 61.9 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kiametis, A.S., Silva, M.A., Romeiro, L.A.S. et al. Potential acetylcholinesterase inhibitors: molecular docking, molecular dynamics, and in silico prediction. J Mol Model 23, 67 (2017). https://doi.org/10.1007/s00894-017-3228-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s00894-017-3228-9

Keywords

Search

Navigation