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Bacterial adenosine 5'-diphosphate-ribosylating toxins are encoded by several human pathogens, such as Pseudomonas aeruginosa (exotoxin A (ETA)), Corynebacterium diphtheriae (diphtheria toxin (DT)), and Vibrio cholerae (cholix toxin (CT)). The toxins modify eukaryotic elongation factor 2, an essential human enzyme in protein synthesis, thereby causing cell death. Targeting external virulence factors, such as the above toxins, is a promising alternative for developing new antibiotics, while at the same time avoiding drug resistance. This study aims to establish a reliable computational methodology to find a "silver bullet" able to target all three toxins. Herein, we have undertaken a detailed analysis of the active sites of ETA, DT, and CT, followed by the determination of the most appropriate selection of the size of the docking sphere. Thereafter, we tested two different approaches for normalizing the docking scores and used these to verify the best target (toxin) for each ligand. The results indicate that the methodology is suitable for identifying selective as well as multitoxin inhibitors, further validating the robustness of inverse docking for target-fishing experiments.

Ligand Selectivity between the ADP-Ribosylating Toxins: An Inverse-Docking Study for Multitarget Drug Discovery