Unlocking Benzosampangine's Potential: A Computational Approach to Investigating, Its Role as a PD-L1 Inhibitor in Tumor Immune Evasion via Molecular Docking, Dynamic Simulation, and ADMET Profiling

Abstract

The interaction between programmed cell death protein 1 (PD-1) and its ligand PD-L1 plays a crucial role in tumor immune evasion, presenting a critical target for cancer immunotherapy. Despite being effective, current monoclonal antibodies present some drawbacks such as high costs, toxicity, and resistance development. Therefore, the development of small-molecule inhibitors is necessary, especially those derived from natural sources. In this study, benzosampangine is predicted as a promising PD-L1 inhibitor, with potential applications in cancer immunotherapy. Utilizing the high-resolution crystal structure of human PD-L1 (PDB ID: 5O45), we screened 511 natural compounds, identifying benzosampangine as a top candidate with exceptional inhibitory properties. Molecular docking predicted that benzosampangine exhibits a strong binding affinity for PD-L1 (-9.4 kcal/mol) compared with established controls such as CA-170 (-6.5 kcal/mol), BMS-202 (-8.6 kcal/mol), and pyrvinium (-8.9 kcal/mol). The compound's predicted binding efficacy is highlighted by robust interactions with key amino acids (ILE54, TYR56, GLN66, MET115, ILE116, SER117, ALA121, ASP122) within the active site, notably forming 3 Pi-sulfur interactions with MET115-an interaction absents in control inhibitors. In addition, ADMET profiling suggests that over the control molecules, benzosampangine has several key advantages, including favorable solubility, permeability, metabolic stability, and low toxicity, while adhering to Lipinski's rule of five. Molecular dynamic simulations predict the stability of the benzosampangine-PD-L1 complex, reinforcing its potential to sustain inhibition of the PD-1/PD-L1 pathway. MMGBSA analysis calculated a binding free energy (ΔGbind) of -39.39 kcal/mol for the benzosampangine-PD-L1 complex, with significant contributions from Coulombic, lipophilic, and Van der Waals interactions, validating the predicted docking results. This study investigates in silico benzosampangine, predicting its better molecular interactions and pharmacokinetic profile compared with several already known PD-L1 inhibitors.

Keywords: PD-1/PD-L1 inhibitors; benzosampangine; cancer; in silico study; molecular docking; molecular dynamic; small molecules.

Figure 1.

Mechanism of PD1/PD-L1 blockade. The CD8⁺ T cell activates on recognizing the tumor antigen presented on MHC class I and releases IFN-γ to bind to IFN-γ receptor, and consequently induces the expression of PDL1 on tumor cells. PDL1 conjugates the elevated PD1 on T cell surface, triggering inhibitory effect of PD1/PD-L1 axis. Anti-PD1 or anti-PDL1 antibody blocks the interaction of PD1 and PD-L1, and abolishes the inhibition of CD8⁺ T cell thus enhancing the antitumor activity.

Figure 2.

The predicted binding pocket of PD-L1. Key residues represented in blue in the binding pocket and the surfaces of the binding pocket in PD-L1 are presented in gray.

Figure 3.

2D interaction of benzosampangine with the active site of PD-L1.

Figure 4.

Root mean square deviation (RMSD) of the protein PD-L1 alone (blue) and in complex with and benzosampangine (red) as a function of simulation time.

Figure 5.

Root mean square fluctuation (RMSF) analysis of PD-L1 in complex with benzosampangine. The vertical green lines represent the amino acid residue of RPFC making contact with ligand.

Figure 6.

The stability of PD-L1’s secondary structure over 100 ns of MD simulation in complex with benzosampangine.

Figure 7.

The protein-ligand interactions: (a) hydrogen bonds—green, hydrophobic—white purple, ionic—pink, water bridges—blue).

Figure 8.

Binding pose and atomic-level interactions of control molecules CA-170 (B), BMS-202 (C), and pyrvinium (D) and benzosampangine (A).

Figure 9.

Root mean square deviation (RMSD) of the protein PD-L1 alone (blue) and in complex with and CA-170 (red) as a function of simulation time.

Figure 10.

Root mean square fluctuation (RMSF) analysis of PD-L1 in complex with CA-170.