As we were dissatisfied with the quality and diversity of available covalent structure redocking benchmark sets, we developed a new high-quality set of 95 covalent complexes to assess the performance of our algorithm. The resulting data set includes five reactive amino acid side chains and eight chemical reactions. All input files including 3D-structures and force field (FF) parameters of this benchmark set are publicly available. We compared the results of AC with two state-of-the-art covalent docking algorithms, GOLD and AutoDock4. Our analysis shows that our docking algorithm outperforms the two others, reaching a success rate (RMSD ≤ 2 Å) of 78% in re-docking experiments, versus 36% and 68% for AutoDock4 and GOLD respectively. We also assessed the cross-docking performance of AC on a very challenging set of 76 covalent ligands targeting the SARS-CoV-2 main protease. AC achieved success rates of 58% and 28% in re-docking and cross-docking, respectively, compared to 45% and 17% obtained with GOLD.