Mining of Potential Antifungal Molecules for Control of Fusarium fujikuroi in Rice using in silico and in vitro Analysis

Abstract

A library of 170 fungicidal molecules of different functional moieties were subjected to in-silico assessment of their relative potential to inhibit ten vital targets of the Fusarium fujikuroi, bakanae disease causative pathogen in rice. Targets chosen were tubulin proteins (α-, β- and γ-tubulin) and NRPS31 gene cluster (FFUJ_00005, FFUJ_00006, FFUJ_00007, FFUJ_00008, FFUJ_00010, FFUJ_00011, FFUJ_00013). In-silico findings were validated with the help of in vitro analysis of the molecules to predict the most effective compound(s) relative to carbendazim (positive control). Most effective molecules were selected based on their chemical characteristics and Lipinski’s rule. One each of the natural and synthetic origin molecules was selected for the molecular dynamics and in-vitro analysis. β-Caryophyllene came out as the most potential molecule followed by flusilazole. The extent of inhibition of α-tubulin by these two molecules was significantly higher than by carbendazim. In-vitro bioassay validated the in-silico findings with LC50 values of 3.29, 64.12, and 178.77 μg/mL for β-caryophyllene, flusilazole and carbendazim, respectively. Further, molecular dynamics also revealed the selected molecular complex as highly effective with time when analyzed using Root Mean Square Deviation (RMSD) and Radius of Gyration (Rg).