Molecular docking in pesticide resistance research: Applications, advances, limitations, and experimental validation

Pesticide resistance has emerged as a primary constraint on sustainable agriculture, reducing crop yields and directly menacing threatening global food security. Molecular docking, a key technique in computer-aided molecular design, offers significant advantages for addressing this challenge, including computational efficiency and capacity for high-throughput screening. These advancements have facilitated the increasingly diverse application of molecular docking in research on pesticide resistance. It can be used to aid in the analysis of resistance mechanisms and accelerate the discovery and screening of new pesticides. As a result, it has established itself as an effective tool for analyzing resistance mechanisms and supporting new pesticide development. It is worth noting that the deep integration of molecular docking with artificial intelligence has provided new insights into the mechanisms of pesticide resistance, facilitated the efficient discovery and rational design of novel pesticides, and further expanded the scope of its application in pesticide optimization and development. However, due to limitations in scoring functions, protein flexibility, and computational models, the results obtained from molecular docking are computational predictions and typically require comprehensive evaluation in conjunction with experimental data. Accordingly, this review provides a systematic analysis molecular docking in pesticide resistance research, including its core principles, specific applications, integration with artificial intelligence, limitations, and the necessity of experimental validation.