Computational and In silico study of novel fungicides against combating root rot, gray mold, fusarium wilt, and...

The exploration of potential candidates for fungicides against four fungal proteins that cause some vital plant diseases, namely Phytophthora capsici, Botrytis cinerea, Fusarium oxysporum f. sp. lycopersici, and Puccinia graminis f. sp. tritici, was conducted using in silico, molecular docking simulations, and molecular dynamic (MD) simulation for selecting the nature of binding affinity with actives sites of proteins. First of all, the DFT was employed to optimize the molecular geometry, and get the prepared optimized ligand. From the DFT data, the chemical descriptors were calculated. Next, two docking tools, such as AutoDock by PyRx and Molecular Docking by Glide from the Schrödinger suite, were used to convey the docking score, and ligand protein interactions against four main proteases, for instance 7VEM, 8H6Q, 8EBB, and 7XDS having name of pathogens: Phytophthora capsici, Botrytis cinerea, Fusarium oxysporum f. sp. lycopersici, and Puccinia graminis f. sp. tritici, respectively. In case of auto dock from PyRx, the fungicides L01, L03, L04, L13, L14, L17, L18, and L19 demonstrated significantly higher affinities for binding to the four fungal pathogens. Surprisingly, it is conveyed that the L03 illustrated the highest binding score against three of 7VEM, 8EBB, and 7XDS proteins and L09 is highest for 8H6Q. However, MD was performed to check the validation and calculation the docking procedure and stability of the protein ligand docked complex accounting of RMSD, RMSF, SASA, Radius of gyration (Rg), Protein secondary structure elements (SSE), Ramachandran plot which confirm that the stability of docked complex is so high, and number of calculating the hydrogen bonds is more than good enough, as a result it is concluded the docking procedure is valid. Finally, Difenoconazole (L03) has been considered as the most promising antifungal drug evaluated from the studies.