Generation rather than screening, were employed in this work to search for new anti-KcsA ligand candidates using the DataWarrior Build Evolutionary Library (DW-BEL) algorithms . Starting from defined parent molecules and their preliminarily identified docking cavity, DW-BEL co-evolution generated tens of thousands raw children and thousands of highly specific cavityfitting children molecules selected by their docking affinities. Despite the particular toxicity and/or steric difficulties found when targeting the known KcsA central cavity and/or lipid surfaces, respectively, the random generation of children molecules was very successful. By restricting their molecular weight, hydrophobicity and toxicity risks and quantitating their affinities by the most accurate AutoDockVina (ADV) program , thousands of low toxicity, high specificity and sub-nanoMolar computational children predictions were identified. Further co-evolutions and deeper preference criteria could be applied, for instance by designing other parent molecules and/or by increasing computer memories since the vast chemical space limits have not yet been reached. In the absence of any experimental confirmatory data, all these predicted docking-cavities and new ligand candidates remain hypothetical.