The results further define pharmacological molecular comprehensions for paralog-dependent engagement of m6A in RNA by the aromatic cage for the selective modulation of YTHDF functions.
Abstract
Recognition of N6-methyl-adenosine (m6A) in the RNA sequences by the YT521-B homology domain-containing protein family paralogs 1–3 (YTHDF1–3) is a dominant layer of myriad cellular regulation. Dysregulated YTHDF paralog expression and activities have been reported in cancer, including glioblastoma multiforme (GBM) in which YTHDF2 has been identified as a druggable dependency. Guided by structure-based in silico screening, we identified structurally related small-molecule compound families of promising YTHDF inhibitor compounds. Following in vitro screening, two hits, DT11 and DT15, emerged and were further examined. We identified DT11 as a YTHDF2-selective inhibitor of the YTH domain using proximity-based bead assays, microscale thermophoresis, molecular dynamics, and nuclear magnetic resonance spectroscopy. DT11 demonstrated 10–100-fold YTHDF2-selectivity (IC50: YTHDF2 16.6 μM; YTHDF1 185 μM; YTHDF3 1300 μM) in inhibiting m6A-RNA binding, whereas the pan-inhibitor DT15 effectively inhibited all the paralogs (IC50: YTHDF2 12.6 μM; YTHDF1 18.8 μM; YTHDF3 31 μM). In LN229 glioblastoma cells, DT11 reduced cell viability and showed relevant additive efficacy with the gold standard Temozolomide. DT15 blocked GBM cell invasion and scratch wound closure. Similar effects were observed after inhibition of the m6A writer METTL3 activity by STM2457. No such effects were observed with DT11. A minutely modified DT11 derivative, DT11-1, showed 10-fold increases in YTHDF2-selective m6A binding and LN229 cell viability inhibitory potencies. All the compounds produced high GBM preference over primary neurons and HEK293 cells in their effects. Our results further define pharmacological molecular comprehensions for paralog-dependent engagement of m6A in RNA by the aromatic cage for the selective modulation of YTHDF functions.
Findings validate the diphenylpyrazine scaffold as a promising chemotype for Skp2–Cks1 inhibition and identify C3 as a strong lead for further optimization.
Emadeldin M. Kamel, A. A. Allam, H. Rudayni et al.· Journal of Computer-Aided Mo...· 0 citations
BRD4, a member of the bromodomain and extra-terminal (BET) family of epigenetic readers, plays a central role in transcriptional regulation and is implicated in a wide spectrum of diseases. Although BRD4 inhibitors targeting both bromodomains have advanced into clinical studies, their development and therapeutic use ar...
Sriram Prakash Baskaran, Yashini Vidhya Subramani, S. Bairy et al.· ACS Omega· 0 citations
Triple-negative breast cancer (TNBC) lacks effective targeted therapies, and YTHDF proteins are frequently overexpressed in this malignancy, which correlates with adverse prognosis. Through high-throughput drug screening, we identify ellagic acid (EA) as a compound that binds to YTHDF proteins and disrupts their intera...
Dual-specificity tyrosine phosphorylation-regulated kinase 1A (DYRK1A) has been implicated in the pathogenesis of Alzheimer's disease (AD) by regulating tau hyperphosphorylation and neuroinflammatory pathways, suggesting DYRK1A as an important therapeutic target. Herein, we report the rational design, synthesis and eva...
Sabiha Khan, Sumaiya Khan, Shafa Khan et al.· RSC Advances· 0 citations
HFS764 disrupts the HIF-1α–p300 interface and suppresses hypoxia-driven signaling in ccRCC, supporting the use of transcriptional complex inhibition as a promising therapeutic strategy.
Mesfer Al Shahrani· Discover medicine· 0 citations
Findings identify SBS-873 as a first-in-class dual inhibitor targeting both p110α and GDH1, offering a promising therapeutic strategy that simultaneously disrupts proliferative signaling, metabolic adaptation, and metastatic potential in TNBC.
A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.