Computational identification and evaluation of novel PD-L1 inhibitors for cancer immunotherapy

利用计算机技术识别和评估新型PD-L1抑制剂在癌症免疫治疗中的应用

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Abstract

Antibody-based therapies targeting the PD-1/PD-L1 pathway have shown promise in anticancer immunotherapy; however, challenges such as high cost, immunogenicity, and limited penetration highlight the need for small-molecule inhibitors. To find new inhibitors, this study used the ligand found in PD-L1 (PDB ID: 7DY7) as a reference for virtual screening. The co-crystallized HOU inhibitor and selected ligands binding to the PD-L1 active site were assessed using Maestro 12.5 molecular docking and molecular dynamics (MD) simulations. The top ligands were evaluated for pharmacokinetics through ADMET profiling and chemical stability using Density Functional Theory (DFT). With a docking score of - 8.512 kcal/mol, Lig_1 demonstrated the greatest binding, establishing hydrogen bonds with the important residues of PD-L1, generating stable hydrophobic contacts, and π-π stacking with Tyr56. Because Lig_1 has better pharmacokinetic characteristics than CCL, especially its capacity to cross the blood-brain barrier (BBB), it has become a prospective contender. With negligible structural fluctuations, supported by RMSD and Radius of Gyration (Rg) studies, a 100-ns MD simulation further confirmed the steady binding of Lig_1. Lig_1 ensures persistent PD-L1 engagement by maintaining strong hydrophobic contacts and π-π stacking with Tyr56. These results showed the potential of Lig_1 as a new PD-L1 inhibitor by showing that, like CCL, it may cause PD-L1 degradation and interfere with PD-1/PD-L1 signaling. This study offers critical insights into the design of next-generation small-molecule inhibitors, paving the way for more effective cancer immunotherapies.

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