Discovery of 4-phenylindolines containing a (5-cyanopyridin-3-yl)methoxy moiety as potent inhibitors of the PD-1/PD-L1 interaction

Meng, Yangyang; Chu, Cuiping; Niu, Xinyu; Cheng, Liuyang; Wu, Di; Liu, Lei; Zhang, Shaopeng; Li, Tianqi; Hou, Yunlei; Liu, Yajing; Qin, Mingze

doi:10.1016/j.bmcl.2022.128647

Cited by 4 publications

(1 citation statement)

References 20 publications

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“…The hit compound was then improved through SAR studies, and a series of resorcinol dibenzyl ethers were synthetized, with compound NP19 ( 22 ) in Figure 5 inhibiting the PD-1/PD-L1 interaction with an IC 50 value of 12.5 nM in Homogeneous Time-Resolved Fluorescence (HTRF) binding assays. Also based on the pharmacophoric model of BMS compounds, and with the use of molecular docking as a corroborative technique [ 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 ], Dai and co-workers [ 74 ] obtained 1-methyl-1H-pyrazolo [4,3-b] pyridine derivatives, with the best compound, D38 ( 23 ) ( Figure 5 ), having an IC 50 value of 9.6 nM. Liu et al [ 75 ] reported benzo[c][1,2,5]oxadiazole derivatives, with molecule L7 ( 24 ) in Figure 5 exhibiting an IC 50 value of 1.8 nM.…”

Section: Computational Methods For Predicting Checkpoint Inhibitorsmentioning

confidence: 99%

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

Sobral

Luz

Almeida

et al. 2023

IJMS

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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.

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Section: Computational Methods For Predicting Checkpoint Inhibitorsmentioning

confidence: 99%

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

Sobral

Luz

Almeida

et al. 2023

IJMS

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Molecular modeling studies of Indoline Scaffold derivatives as PD‐1/PD‐L1 pathway inhibitors by QSAR, molecular docking and molecular dynamics simulation techniques

Tong,

Gao,

Xiao

et al. 2024

ChemistrySelect

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In recent years, blocking the interaction of programmed cell death receptor‐1 (PD‐1) and programmed cell death ligand‐1 (PD‐L1) has been recognized as one of the promising cancer therapies. Due to the many limitations of monoclonal antibodies, the development of small molecule inhibitors targeting PD‐1/PD‐L1 is imminent. This study aims to systematically investigate the interaction mechanisms of novel PD‐1/PD‐L1 inhibitors containing indoline backbone structures using 3D/2D‐QSAR modeling, molecular docking, molecular dynamics (MD) simulation, and ADMET prediction. The performance and predictive ability of the constructed QSAR models were evaluated by internal and external validation techniques. Topomer CoMFA and HQSAR models showed good reliability and predictive capability. By searching for R‐groups in the Topomer search module and combining the existing molecules with high activity contribution values, 24 new compounds with theoretically high activity were obtained, which showed desirable docking scores, appropriate ADMET properties, and good stability. This work not only provides a reliable QSAR model as a valuable screening tool for the development of future drugs targeting PD‐1/PD‐L1, but also makes the newly designed inhibitors expected to be potential PD‐1/PD‐L1 inhibitors that can be used for further synthesis and characterization to obtain novel anti‐cancer drugs targeting PD‐1/PD‐L1.

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Small-molecule modulators of tumor immune microenvironment

Zhang,

Yu,

Liu

et al. 2024

Bioorganic Chemistry

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Discovery of 4-phenylindolines containing a (5-cyanopyridin-3-yl)methoxy moiety as potent inhibitors of the PD-1/PD-L1 interaction

Cited by 4 publications

References 20 publications

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

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

Molecular modeling studies of Indoline Scaffold derivatives as PD‐1/PD‐L1 pathway inhibitors by QSAR, molecular docking and molecular dynamics simulation techniques

Small-molecule modulators of tumor immune microenvironment

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