ArticleAmerican journal of cancer research2022
Structural insights into EphA4 unconventional activation from prediction of the EphA4 and its complex with ribonuclease 1.
Article in American journal of cancer research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 4 citations in OpenAlex.
- AlphaPPIweb: an integration platform for protein-protein interaction prediction and evaluation.American journal of cancer research · 2025Article
- RNASE4 promotes malignant progression and chemoresistance in hypoxic glioblastoma via activation of AXL/AKT and NF-κB/cIAPs signaling pathways.American journal of cancer research · 2024Article
- Ribonuclease 1 Enhances Antitumor Immunity against Breast Cancer by Boosting T cell Activation.International journal of biological sciences · 2023Article
- Development of triazole-based PKC-inhibitors to overcome resistance to EGFR inhibitors in EGFR-mutant lung cancers.American journal of cancer research · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
It has been shown that several ribonuclease (RNase) A superfamily proteins serve as ligands of receptor tyrosine kinases (RTKs), representing a new concept for ligand/receptor interaction. Moreover, recent studies indicate high clinical values for this type of ligand/RTK interactions. However, there is no structural report for this new family of ligand/receptor. In an attempt to understand how RNase and RTK may interact, we focused on the RNase1/ephrin type-A receptor 4 (EphA4) complex and predicted their structure by using the state-of-the-art machine learning method, AlphaFold and its derivative method, AF2Complex. In this model, electrostatic force plays an essential role for the specific ligand/receptor interaction. We found the R39 of RNase1 is the key residue for EphA4-binding and activation. Mutation on this residue causes disruption of an essential basic patch, resulting in weaker ligand-receptor association and leading to the loss of activation. By comparing the surface charge distribution of the RNase A superfamily, we found the positively charged residues on the RNase1 surface is more accessible for EphA4 forming salt bridges than other RNases. Furthermore, RNase1 binds to the ligand-binding domain (LBD) of EphA4, which is responsible for the traditional ligand ephrin-binding. Our model reveals the location of RNase1 on EphA4 partially overlaps with that of ephrin-A5, a traditional ligand of EphA4, suggesting steric hindrance as the basis by which the ephrin-A5 precludes interactions of RNase1 with EphA4. Together, our discovery of RNase1/EphA4 interface provides a potential treatment strategy by blocking the RNase1-EphA4 axis.
Indexed as
Identifiers
36381327PMC9641407W4309245096What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.