C-027

Molecular design of small-molecule inhibitors targeting programmed cell death-1 (PD-1)/programmed cell death ligand-1 (PD-L1) pathway has been recognized as an active research area by the clinical success of cancer immunotherapy. In recent years, using machine learning (ML) methods to accelerate drug design have been confirmed. However, the black box character of ML methods makes model interpretation and ligands optimization obscured. Herein, five explainable ML models were constructed by integrating five ML models with the SHAP method, where these ML models were pretrained with >4000 molecules and their R² ranged from 0.835 to 0.86 on test set. Subsequently, the explainable ML models were employed to identify the relationship between fragments and bio-activity of a small molecule inhibitor BMS-1166, leading to the modification of BMS-1166 into 60 novel compounds. After consensus docking and ADMET test, 3 small molecules (C27, C52 and C54) with better docking scores and lower toxicity than BMS-1166 were screened out further. Finally, the improved binding affinity of C27, C52 to the PD-L1 dimer was validated by the MD simulation. Overall, this work proposed an efficient protocol on the basis of explainable ML models for designing small-molecule inhibitors targeting PD-1/PD-L1 pathway in a rational way.

Programmed death-ligand 1 (PD-L1) has emerged as a promising therapeutic target for various cancers due to its crucial role in promoting tumor immune evasion. Here, we report a novel class of chroman-like small-molecule PD-L1 inhibitors exhibiting significant activity in inhibiting the PD-1/PD-L1 interaction. Employing a "ring-close" strategy for conformational restriction, we have achieved compound C27, which demonstrates superior PD-1/PD-L1 inhibitory activity compared to the positive control. Molecular dynamics simulation and binding free energy calculation predict that (R)-C27 with inhibitory activity surpassed (S)-C27. The experimental results from bioassay and X-ray structural analysis corroborate these findings. All these results collectively indicate that (R)-C27 is a promising lead compound deserving further exploration.