Design of Biphenyl‐Type Programmed Cell Death‐Ligand 1 Inhibitors Using 3D‐QSAR, Molecular Docking, and Molecular Dynamics Simulation

Blocking the interaction between programmed cell death‐1 (PD‐1) and programmed cell death‐ligand 1 (PD‐L1) is a crucial immunotherapeutic strategy for cancer. Currently, all inhibitors available on the market that target PD‐1/PD‐L1 are monoclonal antibodies, with no small molecule drugs yet accessible. This study focused on PD‐L1 and conducted three‐dimensional quantitative structure‐activity relationship (3D‐QSAR) research on 39 PD‐L1 inhibitors using Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA). The CoMFA (q2=0.593, r2=0.991) and CoMSIA (q2=0.542, r2=0.971) models were successfully established. Based on these models, a series of structurally novel and potentially active PD‐L1 inhibitors (37 a–37 e) were designed. Among these compounds, 37 c exhibited superior performance, with CoMFA predicting a pIC50 value of 9.204 and CoMSIA predicting a pIC50 value of 8.597. Further molecular docking and molecular dynamics simulations revealed that compound 37 c establishes hydrophobic interactions with BTyr56 and BVal68 of PD‐L1, engages in hydrogen bonds with AAsp122, ALys124, and BTyr123, and forms electrostatic interactions with ALys124 and AMet115. The design of this biphenyl series of inhibitors offers additional options for the development of small molecule inhibitors targeting PD‐L1, with 37 c expected to be a promising inhibitor of PD‐L1. This study examines the pivotal role of the PD‐1/PD‐L1 immune checkpoint interaction in tumor immunotherapy. Due to the absence of mature small molecule inhibitors in the market, exploring novel PD‐L1 small molecule inhibitors is imperative. Utilizing asymmetric biphenyl compounds developed by BMS Corporation, we assembled 39 small molecule compounds with analogous biphenyl scaffolds from the literature. By employing QSAR methods, these compounds were randomly divided into training and test sets, facilitating the successful construction of CoMFA and CoMSIA models, and thereby laying the groundwork for further research. Extracting insights from the spatial fields depicted in the three‐dimensional contour maps, including the electrostatic field, hydrophobic field, and hydrogen bond donor field, the most active molecule, 37, was selected from the training set. Its specific positions were modified, and functional groups were added to enhance its activity. Based on this, a series of structurally novel and potentially active small molecule compounds (37 a–37 e) were de