Targeting EGFR degradation by autophagosome degraders.

Several generations of epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors have been developed for the treatment of non-small cell lung cancer (NSCLC) in clinic. However, emerging drug resistance mediated by new EGFR mutations or activations by pass, leads to malignant progression of NSCLC. Proteolysis targeting chimeras (PROTACs) have been utilized to overcome the drug resistance acquired by mutant EGFR, newly potent and selective degraders are still need to be developed for clinical applications. Herein, we developed autophagosome-tethering compounds (ATTECs) in which EGFR can be anchored to microtubule-associated protein-1 light chain-3B (LC3B) on the autophagosome with the assistance of the LC3 ligand GW5074. A series of EGFR-ATTECs have been designed and synthesized. Biological evaluations showed that these compounds could degrade EGFR and exhibited moderate inhibitory effects on certain NSCLC cell lines. The ATTEC 12c potently induced the degradation of EGFR with a DC50 value of 0.98 µM and a Dmax value of 81% in HCC827 cells. Mechanistic exploration revealed that the lysosomal pathway was mainly involved in this degradation. Compound 12c also exhibited promising inhibitory activity, as well as degradation efficiency in vivo. Our study highlights that EGFR-ATTECs could be developed as a new expandable EGFR degradation tool and also reveals a novel potential therapeutic strategy to prevent drug resistance acquired EGFR mutations.

Dissecting the molecular mechanism of cepharanthine against COVID-19, based on a network pharmacology strategy combined with RNA-sequencing analysis, molecular docking, and molecular dynamics simulation.

OBJECTIVES: Recently, it has been reported that cepharanthine (CEP) is highly likely to be an agent against Coronavirus disease 2019 (COVID-19). In the present study, a network pharmacology-based approach combined with RNA-sequencing (RNA-seq), molecular docking, and molecular dynamics (MD) simulation was performed to determine hub targets and potential pharmacological mechanism of CEP against COVID-19. METHODS: Targets of CEP were retrieved from public databases. COVID-19-related targets were acquired from databases and RNA-seq datasets GSE157103 and GSE155249. The potential targets of CEP and COVID-19 were then validated by GSE158050. Hub targets and signaling pathways were acquired through bioinformatics analysis, including protein-protein interaction (PPI) network analysis and enrichment analysis. Subsequently, molecular docking was carried out to predict the combination of CEP with hub targets. Lastly, MD simulation was conducted to further verify the findings. RESULTS: A total of 700 proteins were identified as CEP-COVID-19-related targets. After the validation by GSE158050, 97 validated targets were retained. Enrichment results indicated that CEP acts on COVID-19 through multiple pathways, multiple targets, and overall cooperation. Specifically, PI3K-Akt signaling pathway is the most important pathway. Based on PPI network analysis, 9 central hub genes were obtained (ACE2, STAT1, SRC, PIK3R1, HIF1A, ESR1, ERBB2, CDC42, and BCL2L1). Molecular docking suggested that the combination between CEP and 9 central hub genes is extremely strong. Noteworthy, ACE2, considered the most important gene in CEP against COVID-19, binds to CEP most stably, which was further validated by MD simulation. CONCLUSION: Our study comprehensively illustrated the potential targets and underlying molecular mechanism of CEP against COVID-19, which further provided the theoretical basis for exploring the potential protective mechanism of CEP against COVID-19.