Computational design of PD-L1 small molecule inhibitors for cancer therapy

A Comparative Molecular Dynamics Study of Food-Derived Compounds as PD-L1 Inhibitors: Insights Across Six Flavonoid Subgroups

In this study, we investigated the inhibitory potential of 60 flavonoids from six distinct subgroups on the programmed cell death ligand 1 (PD-L1) dimer through molecular docking and dynamics simulations. Using AutoDock Vina for docking, the binding poses and affinities were evaluated, revealing an average binding affinity of -8.5 kcal/mol for the flavonoids. Among them, ginkgetin exhibited the highest binding free energy of -46.73 kcal/mol, indicating a strong interaction with PD-L1, while diosmin followed closely, with -44.96 kcal/mol. Molecular dynamics simulations were used to further elucidate the dynamic interactions and stability of the flavonoid-PD-L1 complexes, with the analyses showing minimal root mean square deviation (RMSD) and favorable root mean square fluctuation (RMSF) profiles for several compounds, particularly formononetin, idaein, and neohesperidin. Additionally, contact number and hydrogen bond analyses were performed, which highlighted ginkgetin and diosmin as key flavonoids with significant binding interactions, evidenced by their stable conformations and robust molecular interactions throughout the simulations. Ultimately, a cell-based assay confirmed their ability to inhibit the proliferation of cancer cells. These results, validated through cell-based assays, indicate that the strategy of identifying natural compounds with anticancer activity using computational modeling is highly effective.

Advancements in drug discovery: integrating CADD tools and drug repurposing for PD-1/PD-L1 axis inhibition

Despite significant strides in improving cancer survival rates, the global cancer burden remains substantial, with an anticipated rise in new cases. Immune checkpoints, key regulators of immune responses, play a crucial role in cancer evasion mechanisms. The discovery of immune checkpoint inhibitors (ICIs) targeting PD-1/PD-L1 has revolutionized cancer treatment, with monoclonal antibodies (mAbs) becoming widely prescribed. However, challenges with current mAb ICIs, such as limited oral bioavailability, adverse effects, and high costs, underscore the need to explore alternative small-molecule inhibitors. In this work, we aimed to identify new potential ICI among all FDA-approved drugs. We employed QSAR models to predict PD-1/PD-L1 inhibition, utilizing a diverse dataset of 29 197 molecules sourced from ChEMBL, PubChem, and recent literature. Machine learning techniques, including Random Forest, Support Vector Machine, and Convolutional Neural Network, were employed for benchmarking to assess model performance. Additionally, we undertook a drug repurposing strategy, leveraging the best in silico model for a virtual screening campaign involving 1576 off-patent approved drugs. Only two virtual screening hits were proposed based on the criteria established for this approach, including: (1) QSAR probability of being active against PD-L1; (2) QSAR applicability domain; (3) prediction of the affinity between the PD-L1 and ligands through molecular docking. One of the proposed hits was sonidegib, an anticancer drug, featuring a biphenyl system. Sonidegib was subsequently validated for in vitro PD-1/PD-L1 binding modulation using ELISA and flow cytometry. This integrated approach, which combines computer-aided drug design (CADD) tools, QSAR modelling, drug repurposing, and molecular docking, offers a pioneering strategy to expedite drug discovery for PD-1/PD-L1 axis inhibition. The findings underscore the potential to identify a wider range small molecules to contribute to the ongoing efforts to advancing cancer immunotherapy.

Characterizing tertiary lymphoid structures associated single-cell atlas in breast cancer patients

The tertiary lymphoid structure (TLS) is recognized as a potential prognosis factor for breast cancer and is strongly associated with response to immunotherapy. Inducing TLS neogenesis can enhance the immunogenicity of tumors and improve the efficacy of immunotherapy. However, our understanding of TLS associated region at the single-cell level remains limited. Therefore, we employed high-resolution techniques, including single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST), and a TLS-specific signature to investigate TLS associated regions in breast cancer. We identified eighteen cell types within the TLS associated regions and calculated differential expression genes by comparing TLS associated regions with other areas. Notably, macrophages in the TLS associated regions exhibit lineage transformation, shifting from facilitators of immune activation to supporters of tumor cell growth. In terms of cell-cell communication within the TLS associated regions, KRT86+ CD8+ T cells, HISTIH4C+ cycling CD8+ T cells, IFNG+ CD8+ T cells, and IGKV3-20+ B cells demonstrate strong interactions with other cells. Additionally, we found that APOD+ fibroblast and CCL21+ fibroblast primarily recruit T and B cells through the CXCL12-CXCR4 ligand-receptor signaling pathway. We also validate these findings in four independent breast cancer datasets, which include one cell-level resolution dataset from the 10 × Xenium platform and three spot-level datasets from the 10 × Visium platform.

Discovery of Daclatasvir as a potential PD-L1 inhibitor from drug repurposing

This study employed a drug repositioning strategy to discover novel PD-L1 small molecule inhibitors. 3D-QSAR pharmacophore models were establishedand subsequently validated through various means to select a robust model, Hypo-1, suitable for virtual screening. Hypo1 was used toscreen a library of 7,475 compounds from the Drugbank database, leading to the identification of 283 molecules following molecular docking with PD-L1.19 compounds underwent HTRF assays, with 15 showing varying degrees of inhibition of the PD-1/PD-L1 interaction. Compounds2202,2204,2207, and2208were further confirmed to bind to PD-L1 using SPR experiments. Among them, compound2204(Daclatasvir, KD = 11.4 μM) showeda higher affinity for human PD-L1 than the control compound BMS-1. In the HepG2/Jurkat cell co-culture model, Daclatasvir effectively activated Jurkat cells to kill HepG2 cells. In the mouse H22 hepatocellular tumor model, Daclatasvir significantly inhibited tumor growth (TGI = 53.4 % at a dose of 100 mg/kg). Its anti-tumor effect was more pronounced when combined with Lenvatinib (TGI = 85.1 %). Flow cytometry analysis of splenocytes and tumor cells indicated that Daclatasvir activated the immune system in both models. In summary, Daclatasvir was identified as a novel PD-L1small molecule inhibitor.

Progress in small-molecule inhibitors targeting PD-L1

PD-L1 is a transmembrane protein overexpressed by tumor cells. It binds to PD-1 on the surface of T-cells, suppresses T-cell activity and hinders the immune response against cancer. Clinically, several monoclonal antibodies targeting PD-1/PD-L1 have achieved significant success in cancer immunotherapy. Nevertheless, their disadvantages, such as unchecked immune responses, high cost and long half-life, stimulated pharmacologists to develop small-molecule inhibitors targeting PD-1/PD-L1. After a batch of excellent inhibitors with a biphenyl core structure were firstly reported by BMS, more and more researchers focused on small-molecule inhibitors targeting PD-L1 rather than PD-1. Numerous small-molecule inhibitors were extensively designed and synthesized in the past few years. In this paper, the structural characteristics of PD-L1 and complexes of PD-L1 with its inhibitors are elaborated and small molecule inhibitors developed in the last decade are summarized as well. This paper aims to provide insights into further designing and synthesis of small molecule inhibitors targeting PD-L1.

Immunomodulatory properties of HDAC6 inhibitors in cancer diseases: New chances for sophisticated drug design and treatment optimization

Histone deacetylases (HDACs) are promising targets for the design of anticancer drugs. HDAC6 is of particular interest since it is a cytoplasmic HDAC regulating the acetylation state of cancer-relevant cytoplasmic proteins such as tubulin, Hsp90, p53, and others. HDAC6 also influences the immune system, and the combination of HDAC6 inhibitors with immune therapy showed promising anticancer results. In addition, the design of new HDAC6 inhibitors led to potent anticancer drugs with immunomodulatory activities. This review describes the current state of play, and the recent developments in the research on the interactions of HDAC6 inhibitors with the immune system, and the development of new HDAC6 inhibitors with immunomodulatory activities to improve the therapy options for cancer patients.

Inside PD-1/PD-L1,2 with their inhibitors

This review summarizes current knowledge in the development of immune checkpoint inhibitors, including antibodies and small molecules.

Novel PD-L1-Targeted Phenyl-Pyrazolone Derivatives with Antioxidant Properties

Orally-active anticancer small molecules targeting the PD-1/PD-L1 immune checkpoint are actively searched. Phenyl-pyrazolone derivatives with a high affinity for PD-L1 have been designed and characterized. In addition, the phenyl-pyrazolone unit acts as a scavenger of oxygen free radicals, providing antioxidant effects. The mechanism is known for the drug edaravone (1) which is also an aldehyde-reactive molecule. The present study reports the synthesis and functional characterization of new molecules (2-5) with an improved anti-PD-L1 activity. The leading fluorinated molecule 5 emerges as a potent checkpoint inhibitor, avidly binding to PD-L1, inducing its dimerization, blocking PD-1/PD-L1 signaling mediated by phosphatase SHP-2 and reactivating the proliferation of CTLL-2 cells in the presence of PD-L1. In parallel, the compound maintains a significant antioxidant activity, characterized using electron paramagnetic resonance (EPR)-based free radical scavenging assays with the probes DPPH and DMPO. The aldehyde reactivity of the molecules was investigated using 4-hydroxynonenal (4-HNE), which is a major lipid peroxidation product. The formation of drug-HNE adducts, monitored by high resolution mass spectrometry (HRMS), was clearly identified and compared for each compound. The study leads to the selection of compound 5 and the dichlorophenyl-pyrazolone unit as a scaffold for the design of small molecule PD-L1 inhibitors endowed with antioxidant properties.

Computational Approaches Drive Developments in Immune-Oncology Therapies for PD-1/PD-L1 Immune Checkpoint Inhibitors

Computational approaches in immune-oncology therapies focus on using data-driven methods to identify potential immune targets and develop novel drug candidates. In particular, the search for PD-1/PD-L1 immune checkpoint inhibitors (ICIs) has enlivened the field, leveraging the use of cheminformatics and bioinformatics tools to analyze large datasets of molecules, gene expression and protein-protein interactions. Up to now, there is still an unmet clinical need for improved ICIs and reliable predictive biomarkers. In this review, we highlight the computational methodologies applied to discovering and developing PD-1/PD-L1 ICIs for improved cancer immunotherapies with a greater focus in the last five years. The use of computer-aided drug design structure- and ligand-based virtual screening processes, molecular docking, homology modeling and molecular dynamics simulations methodologies essential for successful drug discovery campaigns focusing on antibodies, peptides or small-molecule ICIs are addressed. A list of recent databases and web tools used in the context of cancer and immunotherapy has been compilated and made available, namely regarding a general scope, cancer and immunology. In summary, computational approaches have become valuable tools for discovering and developing ICIs. Despite significant progress, there is still a need for improved ICIs and biomarkers, and recent databases and web tools have been compiled to aid in this pursuit.

Structure-Based Screening Reveals a Ligand That Stabilizes the [2Fe-2S] Clusters of Human mitoNEET and Reduces Ovarian Cancer Cell Proliferation

Human NEET proteins play an important role in a variety of diseases, including cancer. Using the recently published X-ray structure of the human mNT-M1 complex, we screened a commercial chemical compound library and identified a new human mitoNEET (mNT) binding ligand (NTS-01). Biochemical investigations revealed that NTS-01 specifically binds to the human mNT protein and stabilizes its [2Fe-2S] clusters under oxidative conditions in vitro. Treatment of ovarian cancer cells with NTS-01 induces ovarian cancer (SKOV-3) mitochondrial fragmentation (fission) and reduces ovarian cancer cell proliferation in a 2D single-layer cell culture, as well as in a 3D-spheroids culture. The NTS-01 molecule represents therefore a new lead compound for further drug design studies attempting to develop efficient treatment against ovarian cancer.