There are an enormous amount of chemotype possibilities to be computationally explored for FtsZ docking ligands 66, 67 . Despite using the evolutionary docking to explore libraries on-demand applying fitting criteria, only a small percentage of the chemotype space possibilities has been explored here. Some sense of possible future work was experienced when combining multiple fitness criteria values during the design of PC190723 evolutionary libraries. Much large numbers of possible combinations could be generated than those minimally explored here. The DataWarrior parent-children evolutionary algorithm is powerful, specially when including docking as fitting criteria. Nevertheless, including access to other external docking algorithms or iteration of DW runs with identified leads could further increase the DW evolutionary library penetration into the unknown chemotype/chemical space. Developing new evolutionary software introducing not only consensus docking but also screening for reduced docking to out-target proteins (i.e., human tubulins) as new fitting criteria, would automatize the optimization and selection processes. Also the inclusion of new fitting criteria such as toxicity and ligand efficiency (i.e., several toxicity and LE options) would enrich the evolutionary process automatically screening the widest chemical space possible and generating children with increased accuracies.