Our work on automating the docking process began in 2009 with the introduction of the web-based tool DOCK Blaster . Although it successfully performed retrospective docking on thousands of targets, DOCK Blaster had noteworthy limitations. Notably, it lacked a framework for evaluating results, leaving it difficult to trust the predicted binding modes of resultant models without further assessment. Consequently, it was also unable to optimize the parameters of the DOCK scoring function, which estimates the binding affinity between a candidate molecule pose and the target protein. In effect, DOCK Blaster served merely as a prototype, composed of isolated scripts that made it fragile and difficult to maintain or develop further. In short, although DOCK Blaster demonstrated potential, its shortcomings highlighted the need for a more robust automated pipeline.