AutoFlex-Dock: New Molecular Docking Workshop Supports Deciphering Protein–Ligand Interactions

Understanding protein–ligand interactions (PLIs) is deeply related to the area of structural bioinformatics and drug discovery, as it is crucial for elucidating the underlying molecular mechanisms. In general, molecular docking is used to predict the PLIs; however, its accuracy is mainly regulated by ligand flexibility. Here, we propose the number of torsion bond (NTB)-based strategy to improve the prediction accuracy of PLIs. The results showed that this strategy achieved a sampling success rate of 62.8% at a root-mean-square deviation (RMSD) threshold of 1.0 Å, approximately 8 to 21% higher than the single search algorithm in AutoDock. Then, the AutoFlex-Dock (https://chemyang.ccnu.edu.cn/ccb/server/AutoFlex-Dock/), a user-friendly and multifunctional server, was developed by integrating the NTB-based strategy, binding free energy calculation, and multiple binding poses analysis based on the AutoDock program. The AutoFlex-Dock server is a convenient tool to explore PLIs and relevant molecular mechanisms.