Virtual Screening Strategy to Identify Retinoic Acid-Related Orphan Receptor γt Modulators

Molecular docking is a key method used in virtual screening (VS) campaigns to identify small-molecule ligands for drug discovery targets. While docking provides a tangible way to understand and predict the protein-ligand complex formation, the docking algorithms are often unable to separate active ligands from inactive molecules in practical VS usage. Here, a novel docking and shape-focused pharmacophore VS protocol is demonstrated for facilitating effective hit discovery using retinoic acid receptor-related orphan receptor gamma t (ROR gamma t) as a case study. ROR gamma t is a prospective target for treating inflammatory diseases such as psoriasis and multiple sclerosis. First, a commercial molecular database was flexibly docked. Second, the alternative docking poses were rescored against the shape/electrostatic potential of negative image-based (NIB) models that mirror the target's binding cavity. The compositions of the NIB models were optimized via iterative trimming and benchmarking using a greedy search-driven algorithm or brute force NIB optimization. Third, a pharmacophore point-based filtering was performed to focus the hit identification on the known ROR gamma t activity hotspots. Fourth, free energy binding affinity evaluation was performed on the remaining molecules. Finally, twenty-eight compounds were selected for in vitro testing and eight compounds were determined to be low mu M range ROR gamma t inhibitors, thereby showing that the introduced VS protocol generated an effective hit rate of similar to 29%.

Automated summary

Molecular docking is a crucial method in virtual screening for identifying small-molecule ligands. However, current docking algorithms struggle to distinguish active ligands from inactive ones. This study introduces a novel docking and shape-focused pharmacophore virtual screening protocol, using retinoic acid receptor-related orphan receptor gamma t (RORγt) as a case study. The results demonstrate that this protocol achieves an effective hit rate of approximately 29%.