Abstract
Alternative drugs are actively searched because of the recent identification of F13L mutations in MonkeyPox Virus (MPXV)-infected patients with resistances to Tecovirimat-treatment. Aiming to help on these searches, computational strategies to generate rather than to screen for new drug-like ligand candidates were explored here. Targeting F13L-mutant representative models, thousands of fitted-children ligands were predicted by i) co-evolutions from the Tecovirimat parent molecule, and ii) F13L-mutant models limited by pooling the most abundant mutations isolated from Tecovirimat-treated patients. Children-fitting F13L-mutant docking-cavities predicted novel scaffolds, nanoMolar affinities, high specificities, absence of known toxicities and conservation of their parent-docking cavities. Despite their limitations, such proved-on-concept similar strategies might be fine-tuned to computational explore for new drugs the most prevalent Tecovirimat-resistance mutants