Ligand-based <i>in silico</i> Approach for Identifying Potent Antidotes Against Botulinum Neurotoxin Serotype A, B, E, and F

Introduction: Botulinum neurotoxins are the most poisonous substances reported and listed in category ‘A’ of biowarfare agents. As serotype identification is a time-consuming process and there is no antidote commercially available, the development of inhibitors against serotypes causing human botulism would be beneficial. In the present study, a ligand-based in silico method was applied to identify the “hits” that could have the potential to act as countermeasures against human-intoxicating BoNTs. Methods: For this purpose, a computational approach using Molegro Virtual Docker and Auto- Dock tools was performed, where around thirty-five derivatives were designed and docked into the catalytic domain of BoNT/A, B, E, and F. The designed compounds were also studied for their ADME properties using an online web tool. Results and Discussion: Analysis of the molecular docking data of the complex by Molegro Virtual Docker revealed a high binding affinity between the target and designed ligands, with the MolDock score between -139.85 and -88.24 kcal/mol, whereas the AutoDock score ranged between -11.65 and -5.30 kcal/mol. Three SMNPIs, A11, A18, and A20, exhibited better binding affinities with the target proteins BoNT/A, /B, E, and /F and could be potential pan-active inhibitors. The ADME/T study showed that the designed ligands were less toxic and possessed drug-resemblance properties by considering the Lipinski, Ghose, Veber, and Egan rules, with a bioavailability score of 0.56. Conclusion: Our study provides insight into ‘hits’, which can lead to further progress in experimental studies and the development of new antidotes for botulism.