Structure-based virtual screening for new lead compounds targeted Plasmodium α-tubulin

  • O. V. Rayevsky Institute of Food Biotechnology and Genomics, National Academy of Sciences of Ukraine
  • O. M. Demchyk Institute of Food Biotechnology and Genomics, National Academy of Sciences of Ukraine
  • P. A. Karpov Institute of Food Biotechnology and Genomics, National Academy of Sciences of Ukraine
  • S. P. Ozheredov
  • S. I. Spivak Institute of Food Biotechnology and Genomics, National Academy of Sciences of Ukraine
  • A. I. Yemets Institute of Food Biotechnology and Genomics, National Academy of Sciences of Ukraine
  • Ya. B. Blume


Aim. Search for new dinitroaniline and phosphorothioamide compounds, capable of selective binding with Plasmodium α-tubulin, affecting its mitotic apparatus. Methods. Structural biology methods of computational prediction of protein-ligand interaction: molecular docking, molecular dynamics and pharmacophore analysis. Selection of compounds based on pharmacophore characteristics and virtual screening results. Results. The protocol and required structural conditions for target (α-tubulin of P. falciparum) preparation and correct modeling of the ligand-protein interaction (docking and virtual screening) were developed. The generalized pharmacophore model of ligand-protein interaction and key functional groups of ligands responsible for specific binding were identified. Conclusions. Based on results of virtual screening, 22 commercial compounds were selected. Identified compounds proposed as potential inhibitors of Plasmodium mitotic machinery and the base of new antimalarial drugs.

Keywords: malaria, Plasmodium, intermolecular interaction, dinitroaniline derived, phosphorothioamidate derived.


Karpov P.A., Demchuk O.M., Ozheredov S.P., Spivak S.I., Yemets A.I., Blume Ya.B. Conservation of dinitroaniline/phosphorothioamidate site of α-tubulin in Plasmodium species distributed in India. Factors of the Experimental Evolution of Organisms. 2019. Vol. 24. P. 327–332. doi: 10.7124/FEEO.v24.1124.

Blume Ya.B., Rayevsky A.V., Yemets A.I., Demchuk O.M., Karpov P.A., Ozheredov S.P., Spivak S.I. P152 Alanine scanning of dinitroaniline/phosphorothioamidate binding site on α-tubulin of Plasmodium species. Cell Bio. 2020 Virtual-an Online ASCB|EMBO Meeting. Retrieved from:

Bell A. Microtubule inhibitors as potential antimalarial agents. Parasitol. Today. 1998. Vol. 14. P. 234–240.

Fennell B.J., Naughton J.A., Dempsey E., Bell A. Cellular and molecular actions of dinitroaniline and phosphorothioamidate herbicides on Plasmodium falciparum: tubulin as a specific antimalarial target. Mol. Biochem. Parasitol. 2006. Vol. 145 (2). P. 226–238.

Blume Ya.B., Nyporko A.Yu., Yemets A.I., Baird W.V. Structural modeling of the interaction of plant α-tubulin with dinitroaniline and phosphoroamidate herbicides. Cell Biol. Int. 2003. Vol. 27 (3). P. 171–174.

Yemets A.I., Blume Y.B. Antimitotic drugs for microprotoplast-mediated chromosome transfer in plant genomics, cell engineering and breeding. In: Blume Y.B., Baird W.V., Yemets A.I., Breviario D. (eds) The Plant Cytoskeleton: a Key Tool for Agro-Biotechnology. Springer, Dordrecht. 2008. P. 419–434.

Lyons-Abbott S., Sackett D.L., Wloga D., Gaertig J., Morgan R.E., Werbovetz K.A., Morrissette N.S. α-Tubulin mutations alter oryzalin affinity and microtubule assembly properties to confer dinitroaniline resistance. Eukaryot Cell. 2010. Vol. 9 (12). P. 1825–1834. doi: 10.1128/EC.00140-10.

Morgan R.E., Ahn S., Nzimiro S., Fotie J., Phelps M.A., Cotrill J., Yakovich A.J., Sackett D.L., Dalton J.T., Werbovetz K.A. Inhibitors of tubulin assembly identified through screening a compound library. Chem. Biol. Drug Design. 2008. Vol. 72 (6). P. 513-524.

Corral M.G., Leroux J., Stubbs K.A., Mylne J.S. Herbicidal properties of antimalarial drugs. Sci. Repts. 2017. Vol. 7. P. 45871. doi: 10.1038/srep45871.

Dhooghe E., Van L.K., Eeckhaut T., Leus L., Van H.J. Mitotic chromosome doubling of plant tissues in vitro. Plant Cell Tiss. Org. Cult. 2011. Vol. 104. P. 359–373.

Kutzner C, Páll S, Fechner M, Esztermann A, de Groot BL, Grubmüller H. More bang for your buck: Improved use of GPU nodes for GROMACS 2018. J Comput Chem. 2019. Vol. 40 (27). P. 2418–2431. doi: 10.1002/jcc.26011.

Machado M.R., Barrera E.E., Klein F., Sóñora M., Silva S., Pantano S. The SIRAH 2.0 force field: altius, fortius, citius. J. Chem. Theor. Comput. 2019. Vol. 15 (4). P. 2719–2733. doi: 10.1021/acs.jctc.9b00006.

Liebeschuetz J.W., Cole J.C., Korb O. Pose prediction and virtual screening performance of GOLD scoring functions in a standardized test. J. Comput. Aided Mol. Des. 2012. Vol. 26 (6). P. 737–748. doi: 10.1007/s10822-012-9551-4.

López-López E., Naveja J.J., Medina-Franco J.L. DataWarrior: an evaluation of the open-source drug discovery tool. Expert Opin. Drug Discov. 2019. Vol. 14 (4). P. 335–341. doi: 10.1080/17460441.2019.1581170.

Allen W.J., Balius T.E., Mukherjee S., Brozell S.R., Moustakas D.T., Lang P.T., Case D.A., Kuntz I.D., Rizzo R.C. DOCK 6: Impact of new features and current docking performance. J. Comput. Chem. 2015. Vol. 36 (15). P. 1132–1156. doi: 10.1002/jcc.23905.