We have employed our workflow to investigate the impact of the docking protocol on automated SMILES-to-ΔΔG calculations, and show that, in general, open-source docking protocols performed competitively with commercial alternatives. Additional constraints on the ligand during docking procedure may improve correlation of the estimated binding affinities with experiment, however this appears to be strongly dependent on the system. Nevertheless, the vast majority of tested configurations, including all core-or MCS-constrained protocols, successfully produced qualitative agreement with experimental binding affinities, demonstrating the value of our automated approach in early-stage drug discovery applications, where the workflow's ability to enrich a compound series by differentiating the most and least potent binders is critical. In this aspect, we have shown that our workflow can, even in challenging cases, produce results that are qualitatively in agreement with those from expertoptimised poses, whilst in more favourable cases provides quantitative agreement to within chemical accuracy.