Crop management through the use of herbicides is an integral part of modern high-yield farming. The identification of resistant mutated strains of normal plants amongst a background of weeds is important to the usage of herbicides, their development, and resistance. In this work a computational study of a point mutation of Proline-197-Serine of the Soybean AHAS enzyme explains the latter’s S197 resistance to the commonly used Chlorsulfuron. Just as a small molecular change to a therapeutic can alter drastically the binding and efficacy of a drug, a small substitution of one amino acid in a target can alter the binding and efficacy of an herbicide through conformation and binding changes of the bound inhibitor, e.g., eliminating a dominant bound herbicide conformation and de-localization generally of the binding. The computational approach here using large scale sampling and distributions from protein-ligand docking and AlphaFold generated protein structures is easily scaled to scan over the mutation possibilities of protein binding sites, similar to screening compounds for potential hits in therapeutic design.
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