Structure-based virtual screening of bioherbicide candidates for weeds in sugarcane plantation using in silico approaches

Abstract

Weeds in sugarcane have negatively affected the sugar yield rate. Several approaches have been carried out to overcome the weeds, including the usage of diuron as synthetic herbicide. However, the long-term usage of diuron is known to have a negative effect leads to the production of 3,4- Dichloroaniline responsible for soil leach and bioaccumulation. Therefore, this study aimed to find a potential natural herbicide. By mimicking the diuron's mode of action which inhibits the process of photosynthesis through blocking the Photosystem II protein D1 (psbA) of the weeds, fourteen compounds as potential candidate bioherbicides were virtually docked by PyRx v0.9.5 software to the specific site. Three important species of the weeds were chosen including Eleusine indica, Praxelis clematidea, and Momordica charantia. The binding affinity score was further calculated and ranked to screen the top six compounds as bioherbicide candidates. Interaction of each complex and the biological activity prediction were then performed by Discovery Studio software and PASS server, respectively. Aurachin P, Aurachin A, and Cyanobacterin were placed in the top ranked compounds with high binding affinity score around -6 to -9 kcal mol-1 toward the psbA. The amino acid interaction involved in the complex shows 50-90% similar to the control, psbA and diuron complex. Besides, the biological activity prediction of Aurachin P, Aurachin A, and Cyanobacterin exhibits the terms related to the inhibition of photosynthesis process via enzymatic pathway. Thus, the active compounds might have inhibition action in the photosynthesis process and control the weeds in sugarcane.