Strategic lead compound design and development utilizing computer‐aided drug discovery (CADD) to address herbicide‐resistant Phalaris minor in wheat fields

Abstract Wheat ( Triticum aestivum ) is a vital cereal crop and a staple food source worldwide. However, wheat grain productivity has significantly declined as a consequence of infestations by Phalaris minor . Traditional weed control methods have proven inadequate owing to the physiological similarities between P. minor and wheat during early growth stages. Consequently, farmers have turned to herbicides, targeting acetyl‐CoA carboxylase (ACCase), acetolactate synthase (ALS) and photosystem II (PSII). Isoproturon targeting PSII was introduced in mid‐1970s, to manage P. minor infestations. Despite their effectiveness, the repetitive use of these herbicides has led to the development of herbicide‐resistant P. minor biotypes, posing a significant challenge to wheat productivity. To address this issue, there is a pressing need for innovative weed management strategies and the discovery of novel herbicide molecules. The integration of computer‐aided drug discovery (CADD) techniques has emerged as a promising approach in herbicide research, that facilitates the identification of herbicide targets and enables the screening of large chemical libraries for potential herbicide‐like molecules. By employing techniques such as homology modelling, molecular docking, molecular dynamics simulation and pharmacophore modelling, CADD has become a rapid and cost‐effective medium to accelerate the herbicide discovery process significantly. This approach not only reduces the dependency on traditional experimental methods, but also enhances the precision and efficacy of herbicide development. This article underscores the critical role of bioinformatics and CADD in developing next‐generation herbicides, offering new hope for sustainable weed management and improved wheat cultivation practices. © 2024 Society of Chemical Industry.