To generate thousands of new F-docking candidates, the java-based DataWarrior Build Evolutionary Library (DWBEL) 2-5 fast algorithms were employed. Provided with a drug parent and its crystallographic 3D binding cavity , DWBEL co-evolutions randomly add/insert atom/bond variations into the parent molecule to generate tens of thousands of raw-children. Those children best-fitting the F cavity were then automatically selected . The DWBEL predicted affinities and cavities were then confirmed by consensus with those form the highly accurate AutoDockVina (ADV) docking program . Thousands of children targeting F with low toxicities, high specificities and lower than sub-nanoMolar affinities were predicted. Hundreds of top-children also docked to inhibitor resistant F mutant cavities.