Exploring FDA-approved small molecules for their potential as PD-1/PD-L1 inhibitors: integrating computational screening with experimental testing.

contextPD-1/PD-L1 axis is a key immune checkpoint in cancer immunotherapy. The interaction between PD-1 (expressed on T-cell) and its ligand PD-L1 (overexpressed on tumor cell) suppresses immune function, promoting cancer progression. Blocking the association between PD-1 and PD-L1 can prevent cancerous cells from evading the immune system, while monoclonal antibodies (mAbs) targeting this pathway demonstrate strong clinical success. However, their immune-related side effects, poor permeability, and high cost limit their usage, emphasizing the need for small-molecule inhibitors (SMIs). Given the limited success of investigational SMIs, drug repurposing offers a promising approach due to its lower cost, known safety, and faster development. This study aims to identify or repurpose existing drugs as PD-1/PD-L1 inhibitors.

methodsA three-tiered docking-based virtual screening (quick, normal, and accurate) was conducted using the lead finder docking algorithm implemented in Flare (Cresset software), with the co-crystallized ligand serving as the reference for score cutoffs. Compounds were shortlisted based on binding orientation, key interactions, and docking energy, yielding six potential candidates. To evaluate binding stability and conformational dynamics, 500 ns molecular dynamics simulations (MDs) were performed for each docked complex (including reference) using Cresset software, and parameters such as RMSD, RMSF, Rg, PCA, and MM/GBSA binding energies were analyzed. Docked complexes were visualized using ICM Molsoft, and data plots were generated by QtGrace. The shortlisted compounds were subsequently validated through an ELISA-based assay to determine their inhibitory potential against PD-1/PD-L1 interaction.