Ligand B‐Factor Index: A Metric for Prioritizing Protein‐Ligand Complexes in Docking

Docking is a structure‐based cheminformatics tool broadly employed in early drug discovery. Based on the tridimensional structure of the protein target, docking is used to predict the binding interactions between the protein and a ligand, estimate the corresponding binding affinity, or perform virtual screenings (VSs) to identify new active compounds. This study introduces the ligand B‐factor index (LBI), a novel computational metric for prioritizing protein‐ligand complexes for docking. Unlike other metrics, LBI directly compares atomic displacements in the ligand and binding site. LBI is defined as the ratio of the median atomic B‐factor of the binding site to that of the bound ligand. Using the comparative assessment of scoring functions (CASF‐2016) dataset, we evaluated the effectiveness of LBI in guiding the selection of protein‐ligand complexes to enhance docking performance. Our results show a moderate correlation (Spearman ρ ~ 0.48) between LBI and the experimental binding affinities, outperforming several docking scoring functions. Additionally, LBI correlates with improved redocking success (root mean square deviation < 2 Å), underlying the significance of a ligand‐focused metric. While LBI outperforms other metrics such as the protein B‐factor index and resolution, its utility in VS docking remains to be further investigated. LBI is easy to compute, interpretable, applicable in structure‐based cheminformatics, and freely available for calculation at https://chembioinf.ro/tool‐bi‐computing.html .