To computationally explore drug-like anti-gpGVHSV, large numbers of high-affinity 3D-conformers docking to gpGVHSV need to be generated. For that, the fastest java-based DataWarrior Build Evolutionary Library (DWBEL) 2-5 algorithms were employed. To start DWBEL co-evolutions, 2 optimal inputs were required: i) a 2D-molecular parent (to randomly generate large numbers of raw-children) and ii) a docked gpGVHSV-parent complex target cavity (to evaluate DWBEL-3Dconformers). Once optimized the 2 inputs, co-evoluted generations originated tens of thousands of raw-children. Each raw-children was then evaluated for fitness to the target cavity (and other user-defined criteria), to select best-fitted children DWBEL-conformers. Iterations yielded hundreds of unique DWBEL-conformers with increased affinities , for independent AutoDockVina (ADV) docking , to generate additional ADV-conformers to confirm increased affinities and targeted cavities.