A high-throughput virtual screening in Grid for new tubulin-targeted inhibitors of plant fungal pathogens

Abstract

Aim. To select new tubulin-targeted inhibitors of plant fungal pathogens based on results of high-throughput virtual screening in Grid. Methods. Protein and ligand spatial structure modelling (I-Tasser, Grid), design and virtual screening ligands library (UCSF Dock 6, Grid), molecular docking (CCDC Gold), molecular dynamics simulation (Gromacs, Grid). Results. 240 structural models of tubulin molecules (82 α-, 111 β- and 47 γ-tubulin) from 62 species of phytopathogenic fungi were constructed. It was found that imidazole ligands, demonstrate strongest affinity to α- and β-tubulin. It was found that among α-, β- and γ-tubulin, taxol binding site of β-tubulin possess the strongest potential as the fungicidal drugs target. It was selected 50 leader compounds: 23 with affinity for GTP/GDF-exchange site and 27 with affinity for taxol-binding site. Conclusions. It was found, that in phytopathogenic fungi, taxol binding site of β-tubulin are the main fungicid drug target (in compare to other tubulin site or isotype). The highest affinity was predicted for the compounds F0478-0219, F0478-0166 and β-tubulin from Puccinia graminis f. sp. Tritici, as well as for the compound F0478-0385 and β-tubulin from Magnaporthe oryzae.
 Keywords: pathogenic fungi, fungicides, tubulin, virtual screening, Grid.