Harnessing Virtual Insights: A Computational Study on the Molecular Characterization of a Drought‐Inducible RNA‐Binding Protein for Enhancing Drought Tolerance in Mungbean ( Vigna radiata L.)

Abstract Abiotic stresses, particularly drought and salinity, significantly impact agricultural crop yields, with mung bean ( Vigna radiata L.) being no exception. This annual green legume, vital to agricultural systems in Asia, is generally resilient to limited water supply; however, severe drought conditions at critical growth stages can drastically diminish both its quality and yield. Drought stress negatively affects various morpho‐physicochemical properties, impeding plant growth and highlighting the need for sustainable approaches to enhance mung bean's drought tolerance through improved farming practices. In this study, we focused on identifying and understanding the molecular mechanisms underlying drought tolerance in mung beans. We retrieved the target gene sequence from the NCBI database, but found no direct sequence similarity, which led to the use of homology modeling. The structure of a known protein (PDB ID: 5T9P) was identified as the most suitable template. Motif prediction using the Motif Search tool highlighted specific motifs relevant to drought stress responses. To investigate potential drought‐tolerance mechanisms, we screened ABA agonists using Density Functional Theory (DFT) analysis. Molecular docking and MD simulations revealed the interactions between these ligands and the modeled protein, shedding light on how they might influence drought tolerance. We performed molecular dynamics (MD) simulations to assess the stability and conformational dynamics of the modeled protein across different time scales. Our findings underscore the potential of ABA agonists to modulate physiological responses and enhance drought resistance. This research offers valuable insights into the conformational dynamics of drought‐related proteins in mung beans, elucidating the molecular underpinnings of drought response mechanisms. By advancing our understanding of these processes, our findings provide novel strategies for improving breeding approaches aimed at enhancing crop resilience against water scarcity and other abiotic stresses. This work promises to mitigate the detrimental effects of drought on mung bean yields and supports sustainable agricultural practices, thereby contributing to global food security.