Unveiling a New Era in Malaria Therapeutics: A Tailored Molecular Approach Towards the Design of Plasmepsin IX Inhibitors

Abstract

The invasive tactics employed by the malarial parasite renders malaria a global health threat, further impeding the effective treatment of the mosquito borne-parasitic disease. Although there have been countless efforts directed towards the development of effective therapeutics, factors such as emerging strains of drug resistance, enhanced toxicity and poor pharmacokinetic properties of current therapeutics has hampered the drug discovery process resulting in the spread of this parasitic disease. A promising target of the most lethal strain of the Plasmodium species that plays a predicted role in erythrocyte invasion of the virulent malarial parasite is aspartic protease IX commonly referred to Plasmepsin IX. The integration of computer aided-drug design platforms has revolutionized the 21st century and has opened avenues to render a final “knock out” in the elimination and eradication of this parasitic disease Hitherto, this is the first attempt directed towards the design of therapeutics tailored explicitly to Plasmepsin IX. A potent peptidomimetic inhibitor referred to as 49c which is a known inhibitor of Plasmepsin II, has recently exhibited potent inhibitory activity against Plasmepsin IX. In-silico structural and physicochemical inspection of 49c displayed poor pharmacokinetic properties thus paving the way for the development of tailored inhibitors with desirable therapeutic properties against Plasmepsin IX. In this study we implement the pharmacophore model approach in combination with per-residue energy decomposition analysis to serve as a powerful cornerstone, that may assist medicinal experts in the composition of multifunctional therapeutics that may predispose factors such as cross-resistance and toxicity, with enhanced pharmacokinetic properties.

This is a preview of subscription content, access via your institution.

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

References

  1. 1.

    Anslyn EV, Dougherty DA (2006) Modern physical organic chemistry. University Science Books, California

    Google Scholar 

  2. 2.

    Arodola OA, Soliman MES (2016) Molecular dynamics simulations of ligand-induced flap conformational changes in cathepsin-D—a comparative study. J Cell Biochem 117(11):1–15. https://doi.org/10.1002/jcb.25564

    CAS  Article  Google Scholar 

  3. 3.

    Asojo OA, Gulnik SV, Afonina E, Yu B, Ellman JA, Haque TS, Hall BH (2003) Novel Uncomplexed and complexed structures of plasmepsin II, an aspartic protease from Plasmodium falciparum. J Mol Biol 327(1):173–181. https://doi.org/10.1016/S0022-2836(03)00036-6

    CAS  Article  PubMed  Google Scholar 

  4. 4.

    Banerjee R, Liu J, Beatty W, Pelosof L, Klemba M, Goldberg DE (2002) Four plasmepsins are active in the Plasmodium falciparum food vacuole, including a protease with an active-site histidine. Proc Natl Acad Sci USA 99(2):990–995. https://doi.org/10.1073/pnas.022630099

    CAS  Article  PubMed  Google Scholar 

  5. 5.

    Berendsen HJC, Postma JPM, Van Gunsteren WF, Dinola A, Haak JR, Berendsen HJC, Haak JR (1984) Molecular dynamics with coupling to an external bath. J Chem Phys 81(8):3685–3689. https://doi.org/10.1063/1.448118

    Article  Google Scholar 

  6. 6.

    Berry C (2000) New targets for antimalarial therapy: the plasmepsins, malaria parasite aspartic proteinases. Biochem Educ 4412(97):191–194

    Google Scholar 

  7. 7.

    Cai H, Kuang R, Gu J, Wang Y, Texas S, Infectious E, Antonio S (2011) Proteases in malaria parasites—a phylogenomic perspective. Curr Genomics 12(6):1668–1688. https://doi.org/10.1002/jcc.20290

    CAS  Article  Google Scholar 

  8. 8.

    Case DA, Cheatham TE, Darden TOM, Gohlke H, Luo RAY, Merz KM, Woods RJ (2005) The amber biomolecular simulation programs. J Comput Chem 26(16):1668–1688. https://doi.org/10.1002/jcc.20290

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  9. 9.

    Chang CA, Chen W, Gilson MK (2007) Ligand configurational entropy and protein binding. Proc Natl Acad Sci USA 104(5):1534–1539

    CAS  Article  Google Scholar 

  10. 10.

    Coombs GH, Goldberg DE, Klemba M, Berry C, Kay J, Mottram JC, Mottram JC (2001) Aspartic proteases of Plasmodium falciparum and other parasitic protozoa as drug targets. Trends Parasitol 17(11):532–537

    CAS  Article  Google Scholar 

  11. 11.

    Cowman AF, Berry D, Baum J (2012) The cellular and molecular basis for malaria parasite invasion of the human red blood cell. J Cell Biol 198(6):961–971. https://doi.org/10.1083/jcb.201206112

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  12. 12.

    Crunkhorn S (2017) Blocking malaria parasite invasion and egress. Nat Rev Drug Discov 17(1):17. https://doi.org/10.1038/nrd.2017.253

    CAS  Article  PubMed  Google Scholar 

  13. 13.

    Motiejunas D, Wade RC (2007) Computer-assited drug design. In: Taylor JB, Triggle DJ (eds) Comprehensive medicinal chemistry II, 2nd edn. Elsevier, New York

    Google Scholar 

  14. 14.

    Daina A, Michielin O, Zoete V (2017) SwissADME: a free web tool to evaluate pharmacokinetics, drug- likeness and medicinal chemistry friendliness of small molecules. Sci Rep 7(1):1–13. https://doi.org/10.1038/srep42717

    Article  Google Scholar 

  15. 15.

    Dash C, Kulkarni A, Dunn B, Rao M (2003) Aspartic peptidase inhibitors: implications in drug development aspartic peptidase inhibitors: implications in drug development. Crit Rev Biochem Mol Biol 38(2):89–119. https://doi.org/10.1080/713609213

    CAS  Article  PubMed  Google Scholar 

  16. 16.

    Davidchack RL, Handel R, Tretyakov MV, Davidchack RL, Handel R, Tretyakov MV (2009) Langevin thermostat for rigid body dynamics Langevin thermostat for rigid body dynamics. J Chem Phys 130(23):234101. https://doi.org/10.1063/1.3149788

    CAS  Article  PubMed  Google Scholar 

  17. 17.

    Deu E (2017) Proteases as antimalarial targets: strategies for genetic, chemical, and therapeutic validation. FEBS J 284(16):2604–2628. https://doi.org/10.1111/febs.14130

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  18. 18.

    Du X, Li Y, Xia Y, Ai S, Liang J, Sang P, Ji X (2016) Insights into protein–ligand interactions: mechanisms, models, and methods. Int J Mol Sci 17(2):1–34. https://doi.org/10.3390/ijms17020144

    CAS  Article  Google Scholar 

  19. 19.

    Erik J (2010) Electrostatics in proteins and protein-ligand complexes. Future Med Chem 2(4):1–41

    Google Scholar 

  20. 20.

    Ersmark K, Samuelsson B, Hallberg A (2006) Plasmepsins as potential targets for new antimalarial therapy. Med Res Rev 26(5):626–666. https://doi.org/10.1002/med.20082

    CAS  Article  PubMed  Google Scholar 

  21. 21.

    Favourite NC, Ramesh M, Mahmoud ESS (2016) Per-residue energy decomposition pharmacophore model to enhance virtual screening in drug discovery: a study for identification of reverse transcriptase inhibitors as potential anti-HIV agents. Drug Des Dev Ther 10:1365–1377

    Google Scholar 

  22. 22.

    Ferreira De Freitas R, Schapira M (2017) A systematic analysis of atomic protein-ligand interactions in the PDB. MedChemComm 8(10):1970–1981. https://doi.org/10.1039/c7md00381a

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  23. 23.

    Galindo-murillo R, Robertson JC, Zgarbova M, Jir S, Otyepka M, Jurec P, Cheatham TE (2016) Assessing the current state of amber force field modifications for DNA. J Chem Theory Comput 12(8):4114–4127. https://doi.org/10.1021/acs.jctc.6b00186

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  24. 24.

    Haldar K, Bhattacharjee S, Safeukui I (2018) Drug resistance in Plasmodium. Nat Rev Microbiol 16(3):156–170. https://doi.org/10.1038/nrmicro.2017.161

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  25. 25.

    Irwin JJ, Shoichet BK (2006) ZINC- A free database of commercially available compounds for virtual screening. J Chem Inf Model 45(1):177–182

    Article  Google Scholar 

  26. 26.

    Kaalia R, Kumar A, Srinivasan A, Ghosh I (2011) An ab initio method for designing multi-target specific pharmacophores using complementary interaction field of aspartic proteases. Mol Inform 34(6–7):380–393. https://doi.org/10.1002/minf.201400157

    CAS  Article  Google Scholar 

  27. 27.

    Karubiu W, Bhakat S, Mcgillewie L, Soliman MES (2015) Molecular BioSystems Flap dynamics of plasmepsin proteases: insight dynamics. Mol BioSyst 11(4):1061–1066. https://doi.org/10.1039/C4MB00631C

    CAS  Article  PubMed  Google Scholar 

  28. 28.

    Kelley LA, Mezulis S, Yates CM, Wass MN, Sternberg MJE (2015) The Phyre2 web portal for protein modeling, prediction and analysis. Nat Protoc 10(6):845–858. https://doi.org/10.1038/nprot.2015-053

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  29. 29.

    Lionta E, Spyrou G, Vassilatis DK, Cournia Z (2014) Structure-based virtual screening for drug discovery: principles, applications and recent advances. Curr Top Med Chem 14(16):1923–1938. https://doi.org/10.2174/1568026614666140929124445

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  30. 30.

    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 64:4–7. https://doi.org/10.1016/j.addr.2012.09.019

    Article  Google Scholar 

  31. 31.

    Liu J, Gluzman IY, Drew ME, Goldberg DE (2005) The role of Plasmodium falciparum food vacuole plasmepsins. J Biol Chem 280(2):1432–1437. https://doi.org/10.1074/jbc.M409740200

    CAS  Article  PubMed  Google Scholar 

  32. 32.

    Mao Y (2011) Dynamical basis for drug resistance of HIV-1 protease. BMC Struct Biol 11(31):1–9

    Google Scholar 

  33. 33.

    Martin YC, Park A (2005) A bioavailability score. J Med Chem 48:3164–3170. https://doi.org/10.1021/jm0492002

    CAS  Article  Google Scholar 

  34. 34.

    Mcgillewie L, Ramesh M, Soliman ME (2017) Sequence, structural analysis and metrics to define the unique dynamic features of the flap regions among aspartic proteases. Protein J 12:5–9. https://doi.org/10.1007/s10930-017-9735-9

    CAS  Article  Google Scholar 

  35. 35.

    Mcgillewie L, Soliman ME (2015) Flap flexibility amongst I, II, III, IV, and V: sequence, structural, and molecular dynamic analyses. PROTEINS: Structure. Funct Genet 11:1693–1705. https://doi.org/10.1002/prot.24855

    CAS  Article  Google Scholar 

  36. 36.

    Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ (2010) AutoDock4 and AutoDockTools4: automated docking with selective receptor flexibility. J Comput Chem 30(16):2785–2791. https://doi.org/10.1002/jcc.21256.AutoDock4

    Article  Google Scholar 

  37. 37.

    Moura PA, Dame JB, Fidock DA (2009) Role of Plasmodium falciparum digestive vacuole plasmepsins in the specificity and antimalarial mode of action of cysteine and aspartic protease inhibitors. Antimicrob Agents Chemother 53(12):4968–4978. https://doi.org/10.1128/AAC.00882-09

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  38. 38.

    Nair DN, Singh V, Angira D, Thiruvenkatam V (2016) Proteomics & bioinformatics structural investigation and in-silico characterization of plasmepsins from Plasmodium falciparum. J Proteom Bioinform 9(7):181–195. https://doi.org/10.4172/jpb.1000405

    CAS  Article  Google Scholar 

  39. 39.

    Nasamu AS, Glushakova S, Russo I, Vaupel B, Oksman A, Kim AS, Goldberg DE (2017) Plasmepsins IX and X are essential and druggable mediators of malaria parasite egress and invasion. Science 522(358):518–522

    Article  Google Scholar 

  40. 40.

    National Library of Medicine (US) (1988) National Center for Biotechnology Information (NCBI)

  41. 41.

    Nigussie D, Beyene T, Shah NA, Belew S (2015) Malaria control & elimination new targets in malaria parasite chemotherapy: a review. Malar Control Elimin. https://doi.org/10.4172/2470-6965/1000S1-007

    Article  Google Scholar 

  42. 42.

    Parr CL, Tanaka T, Xiao H, Yada RY (2008) The catalytic significance of the proposed active site residues in Plasmodium falciparum histoaspartic protease. FEBS J 275(8):1698–1707. https://doi.org/10.1111/j.1742-4658.2008.06325.x

    CAS  Article  PubMed  Google Scholar 

  43. 43.

    Petrenko R (2010) Molecular dynamics. In: Encyclopedia of life sciences. Wiley, Chichester, pp 1–13. https://doi.org/10.1002/9780470015902.a0003048.pub2

  44. 44.

    Pino P, Caldelari R, Mukherjee B, Vahokoski J, Klages N, Maco B, Soldati-favre D (2017) A multistage antimalarial targets the plasmepsins IX and X essential for invasion and egress. Science 528(358):522–528

    Article  Google Scholar 

  45. 45.

    Rosenthal PJ (1998) Proteases of malaria parasites: new targets for chemotherapy. Emerg Infect Dis 4(1):49–57

    CAS  Article  Google Scholar 

  46. 46.

    Saddala MS, Adi PJ (2018) Discovery of small molecules through pharmacophore modeling, docking and molecular dynamics simulation against Plasmodium vivax. Heliyon 4(5):e00612. https://doi.org/10.1016/j.heliyon.2018.e00612

    Article  PubMed  PubMed Central  Google Scholar 

  47. 47.

    Tamar S (2002) Molecular modeling and simulation: an interdisciplinary guide, 2nd edn. Springer, New York

    Google Scholar 

  48. 48.

    Wang J, Hou T, Li Y, Wang W (2012) Assessing the performance of the MM/PBSA and MM/GBSA medthods: the accuracy of binding free energy calculations based on molecular dynamics simulations. J Chem Inf Model 51(1):69–82. https://doi.org/10.1021/ci100275a.Assessing

    Article  Google Scholar 

  49. 49.

    Wang J, Wolf RM, Caldwell JW, Kollman PA, Case DA (2004) Development and testing of a general amber force field. J Comput Chem 25:1157–1174

    CAS  Article  Google Scholar 

  50. 50.

    World Health Organization (2016) Global technical strategy for malaria 2016–2030. http://apps.who.int/iris/bitstream/handle/10665/176712/9789241564991_eng.pdf?sequence=1

  51. 51.

    World Health Organization (2017) World malaria report 2017. Geneva. http://www.who.int/malaria/publications/world-malaria-report-2017/report/en/

  52. 52.

    Wright DW, Hall BA, Kenway OA, Jha S, Coveney PV (2014) Computing clinically relevant binding free energies of HIV-1 protease inhibitors. J Chem Theroy Comput 10(3):1228–1241

    CAS  Article  Google Scholar 

  53. 53.

    Ylilauri M, Pentikäinen OT (2013) MMGBSA as a tool to understand the binding affinities of filamin-peptide interactions. J Chem Inf Model 53(10):2626–2633. https://doi.org/10.1021/ci4002475

    CAS  Article  PubMed  Google Scholar 

Download references

Acknowledgements

The authors acknowledge the National Research Foundation for their financial support and the Centre for High Performance Computing (http://www.chpc.ac.za) for their computational resources.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Mahmoud E. S. Soliman.

Ethics declarations

Conflict of interest

There are no conflicts to declare.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 2495 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Munsamy, G., Soliman, M.E.S. Unveiling a New Era in Malaria Therapeutics: A Tailored Molecular Approach Towards the Design of Plasmepsin IX Inhibitors. Protein J 38, 616–627 (2019). https://doi.org/10.1007/s10930-019-09871-2

Download citation

Keywords

  • Plasmodium falciparum
  • Plasmepsin IX
  • Twisting motion
  • Pharmacophore