SUMMARY. Ivermectin influence on phytopathogenic strains of Fusarium graminearum (F-55644, F-55748) and Fusarium oxysporum f. sp. lycopersici (F-52897, F-55547) was analysed. As the result, it was determined that ivermectin has antifungal effect on the growth of colonies of these strains at high concentrations (2–3 mg/ml). Moreover, the F. oxysporum strains in general were more susceptible to ivermectin than F. graminearum strains. As it is known that ivermectin can cause the microtubules stabilization through binding to β-tubulin, the 3-dimensional model of the interaction of this compound with β-tubulin of F. graminearum was developed to identify of ivermectin induced changes in β-tubulin molecular conformation including the stabilization and spiralization of M-loop. This structural element is important for the establishment of lateral contacts between tubulin subunits of adjacent microtubular protofilaments. As the M-loop stabilization reflects a very important feature of microtubules sta-bilizing agents binding to the taxane site of β-tubulin, it can be supposed, that ivermectin possesses the same effects on Fusarium microtubules. Consequently, the obtained results allow to consider fungal tubulin as a potential target for realization of antifungal activity of ivermectin and its derivatives.
Keywords:
Full text and supplemented materials
Free full text: PDFReferences
Abraham, M.J., Murtola, T., Schulz, R., et al., GROMACS: High performance molecular simulations through multi–level parallelism from laptops to supercomputers, SoftwareX, 2015, vol. 1, pp. 19–25. https://doi.org/10.1016/j.softx.2015.06.001
Ashraf, S., Beech, R.N., Hancock, M.A., and Prichard, R.K., Ivermectin binds to Haemonchus contortus tubulins and promotes stability of microtubules, Int. J. Parasitol., 2015, vol. 45, nos. 9–10, pp. 647–654. https://doi.org/10.1016/j.ijpara.2015.03.010
Balouiri, M., Sadiki, M., and Ibnsouda, S.K., Methods for in vitro evaluating antimicrobial activity: A review, J. Pharm. Anal., 2016, vol. 6, no. 2, pp. 71–79. https://doi.org/10.1016/j.jpha.2015.11.005
Blume, Ya., Yemets, A., Sheremet Ya., et al., Exposure of beta–tubulin regions defined by antibodies on a Arabidopsis thaliana microtubule protofilament model and in the cells, BMC Plant Biol., 2010, vol. 10, p. 29. https://doi.org/10.1186/1471-2229-10-29
Breviario, D., Gianì, S., and Morello, L., Multiple tubulins: evolutionary aspects and biological implications, Plant J., 2013, vol. 75, no. 2, pp. 202–218. https://doi.org/10.1111/tpj.12243
Crump, A., Ivermectin: enigmatic multifaceted ‘wonder’ drug continues to surprise and exceed expectations, J. Antibiot., 2017, vol. 70, no. 5, pp. 495–505. https://doi.org/10.1038/ja.2017.11
Daura, X., Gademann, K., Jaun, B., et al., Peptide folding: when simulation meets experiment, Angew. Chem., Int. Ed., 1999, vol. 38, nos. 1–2, pp. 236–240. https://doi.org/10.1002/(SICI)1521-3773(19990115)38:1/2%3C236::AIDANIE236%3E3.0.CO;2-M
Debs, G.E., Cha, M., Liu, X., et al., Dynamic and asymmetric fluctuations in the microtubule wall captured by high–resolution cryoelectron microscopy, Proc. Natl. Acad. Sci. U. S. A., 2020, vol. 117, no. 29, pp. 16976–16984. https://doi.org/10.1073/pnas.2001546117
Huang, J. and MacKerell, A.D., Jr., CHARMM36 allatom additive protein force field: Validation based on comparison to NMR data, J. Comput. Chem., 2013, vol. 34, no. 25, pp. 2135–2145. https://doi.org/10.1016/j.ijfoodmicro.2017.04.011
Humphrey, W., Dalke, A., and Schulten, K., VMD: Visual molecular dynamics, J. Mol. Graphics, 1996, vol. 14, no. 1, pp. 33–38. https://doi.org/10.1016/0263-7855(96)00018-5
Hunter, B., Benoit, M.P.M.H., Asenjo, A.B., et al., Kinesin-8-specific loop-2 controls the dual activities of the motor domain according to tubulin protofilament shape, Nat. Commun., 2022, vol. 13, no. 1, p. 4198. https://doi.org/10.1038/s41467-022-31794-3
Jones, G., Willett, P., Glen, R.C., et al., Development and validation of a genetic algorithm for flexible docking, J. Mol. Biol., 1997, vol. 267, no. 3, pp. 727–748. https://doi.org/10.1006/jmbi.1996.0897
Jumper, J., Evans, R., Pritzel, A., et al., Highly accurate protein structure prediction with AlphaFold, Nature, 2021, vol. 596, no. 7873, pp. 583–589. https://doi.org/10.1038/s41586-021-03819-2
Karlsson, I., Friberg, H., Kolseth, A.K., et al., Agricultural factors affecting Fusarium communities in wheat kernels, Int. J. Food Microbiol., 2017, vol. 252, pp. 53–60. https://doi.org/10.1073/pnas.2001546117
Karpov, P.A., Brytsun, V.M., Rayevsky, A.V., et al., High-throughput screening of new antimitotic compounds based on CSLabGrid virtual organization, Sci. Innovat., 2015, vol. 11, no. 1, pp. 85–93. https://doi.org/10.15407/scin11.01.092
Korb, O., Stützle, T., and Exner, T.E., Empirical scoring functions for advanced protein–ligand docking with PLANTS, J. Chem. Inf. Model., 2009, vol. 49, no. 1, pp. 84–96. https://doi.org/10.1021/ci800298z
Kustovskiy, Y.O., Buziashvili, A.Y., and Yemets, A.I., Research of ivermectin influence on Fusarium graminearum and F. oxysporum, in Faktory eksperimental’noi evolutsii organizmov (Factors in the Experimental Evolution of Organisms), 2022, vol. 30, pp. 91–95. https://doi.org/10.7124/feeo.v30.1467
Löscher, W., Is the antiparasitic drug ivermectin a suitable candidate for the treatment of epilepsy?, Epilepsia., 2023, vol. 64, no. 3, pp. 553–566. https://doi.org/10.1111/epi.17511
Lykholat, Y.V., Rabokon, A.M., Blume, R.Ya., et al., Characterization of β–tubulin genes in Prunus persica and Prunus dulcis for fingerprinting of their interspecific hybrids, Cytol. Genet., 2022, vol. 56, no. 6, pp. 481–493. https://doi.org/10.3103/S009545272206007X
Martin, R.J., Robertson, A.P., and Choudhary, S., Ivermectin: an anthelmintic, an insecticide, and much more, Trends Parasitol., 2021, vol. 37, no. 1, pp. 48–64. https://doi.org/10.1016/j.pt.2020.10.005
Mittal, N. and Mittal, R., Repurposing old molecules for new indications: Defining pillars of success from lessons in the past, Eur. J. Pharmacol., 2021, vol. 912, p. 174569. https://doi.org/10.1016/j.ejphar.2021.174569
Momany, M. and Talbot, N.J., Septins focus cellular growth for host infection by pathogenic fungi, Front. Cell Dev. Biol., 2017, vol. 5, p. 33. https://doi.org/10.3389/fcell.2017.00033
Mooij, W.T. and Verdonk, M.L., General and targeted statistical potentials for protein–ligand interactions, Proteins, 2005, vol. 61, no. 2, pp. 272–287. https://doi.org/10.1002/prot.20588
Mühlethaler, T., Gioia, D., Prota, A.E., et al., Comprehensive analysis of binding sites in tubulin, Angew. Chem., Int. Ed., 2021, vol. 60, no. 24, pp. 13331–13342. https://doi.org/10.1002/anie.202100273
Sampaio, A.M., Araújo, Sd.S., Rubiales, D., and Vaz Patto, M.C., Fusarium wilt management in legume crops, Agronomy, 2020, vol. 10, no. 8, p. 1073. https://doi.org/10.3390/agronomy10081073
Schneider, N., Lange, G., Hindle, S., et al., A consistent description of HYdrogen bond and DEhydration energies in protein–ligand complexes: methods behind the HYDE scoring function, J. Comput.-Aided Mol. Des., 2013, vol. 27, no. 1, pp. 15–29. https://doi.org/10.1007/s10822-012-9626-2
Volkamer, A., Griewel, A., Grombacher, T., and Rarey, M., Analyzing the topology of active sites: on the prediction of pockets and subpockets, J. Chem. Inf. Model., 2010, vol. 50, no. 11, pp. 2041–2052. https://doi.org/10.1021/ci100241y
Volkamer, A., Kuhn, D., Rippmann, F., and Rarey, M., DoGSiteScorer: a web server for automatic binding site prediction, analysis and druggability assessment, Bioinformatics, 2012, vol. 28, no.15, pp. 2074–2075. https://doi.org/10.1093/bioinformatics/bts310
Westphal, K.R., Heidelbach, S., Zeuner, E.J., et al., The effects of different potato dextrose agar media on secondary metabolite production in Fusarium, Int. J. Food Microbiol., 2021, vol. 347, p. 109171. https://doi.org/10.1016/j.ijfoodmicro.2021.109171
Xiao, Q., Xue, T., Shuai, W., et al., High-resolution X-ray structure of three microtubule-stabilizing agents in complex with tubulin provide a rationale for drug design, Biochem. Biophys. Res. Commun., 2021, vol. 534, pp. 330–336. https://doi.org/10.1016/j.bbrc.2020.11.082
Zoete, V., Cuendet, M.A., Grosdidier, A., and Michielin, O., SwissParam: A fast force field generation tool for small organic molecules, J. Comput. Chem., 2011, vol. 32, no. 11, pp. 2359–2368. https://doi.org/10.1002/jcc.21816