Fluorescent probes in living cells can reveal the underlying biology of cancer, which could lead to the discovery of better anticancer drugs.

© Pixabay

Detecting illegal assemblies in cancer cells

31 Dec 2019

A*STAR scientists have developed a method to measure crucial protein-protein interactions in cancer cells, with implications for drug design and discovery.

The second leading cause of death globally, cancer is a disease characterized by uncontrolled cell division. To develop new and better treatments for cancer, researchers are delving deep into the signaling pathways that drive rogue behavior in cancer cells.

At the crossroads of several of these signaling pathways sits a protein complex called eIF4F, which controls whether a cell divides or not. Because the eIF4F complex requires three sub-components—eIF4A, eIF4E and eIF4G—coming together to work, scientists have considered targeting the assembly process of eIF4F to treat cancer. For that to happen, scientists need a clear method to monitor the interactions among the sub-components of eIF4F.

“Conventional approaches to study eIF4E:eIF4G interaction are experimentally demanding, tedious and can only be done in dead cells,” said Christopher Brown, a Principal Investigator at the p53 Laboratory, A*STAR. “Our method, the NanoLuc-based protein fragment complementation assay or protein-protein interaction assay, can be performed in live cells with high throughput.”

Put simply, when eIF4E and eIF4G interact in living cancer cells, luminescent or fluorescent signals are generated. If a compound successfully prevents eIF4E from complexing with eIF4G, the luminescent or fluorescent signal is lost, granting the researchers the ability to identify upstream or downstream factors that perturb eIF4E:eIF4G interaction.

Using this assay, the researchers validated that eIF4F complex assembly is regulated by another protein named 4EBP1. Meanwhile, 4EBP1 is controlled by two upstream signaling pathways named RAS/ERK and PI3K/AKT/mTOR.

When the researchers used small molecule drugs to inhibit the RAS/ERK and PI3K/AKT/mTOR pathways concurrently in cancer cells, eIF4F complex assembly was blocked, and the cells were less resistant to treatment.

“Using our technique to monitor eIF4E:eIF4G interaction in living cells, we aim to drive the discovery of new modalities against ‘difficult drug targets’ within cells, such as the eIF4F complex and KRAS,” said Brown. Additionally, his team is developing methods to probe the interfaces between proteins and other biomolecules such as DNA, which will allow druggable sites in proteins to be identified.

“More importantly, we are developing target-agnostic assays to measure the permeability of macrocyclic compounds directly. We hope that this type of assay will allow us to understand the parameters required for the uptake of macrocyclic compounds into cells,” Brown added. The findings from this ongoing study may have implications for cancer drug design, by screening for anticancer drugs that show optimal uptake into tumors.

The A*STAR-affiliated researchers contributing to this research are from the p53 Laboratory.

Want to stay up to date with breakthroughs from A*STAR? Follow us on Twitter and LinkedIn!


Frosi, Y., Usher, R., Lian, D. T. G., Lane, D. P., Brown, C. J. Monitoring flux in signaling pathways through measurements of 4EBP1-mediated eIF4F complex assembly. BMC Biology 17, 40 (2019) | article

About the Researcher

Christopher Brown

Research Scientist

p53 Laboratory
Christopher Brown obtained his PhD degree from the University of Edinburgh, UK, where he worked on structural biochemistry. He is currently a Co-Principal Investigator on A*STAR’s Peptide Engineering Program and a Research Scientist at the p53 Laboratory, A*STAR. His main research interests are in using biophysical and crystallographic techniques to understand small molecule-protein and peptide-protein interactions. He uses this information to develop drug-like small molecules, peptidomimetics and mini-proteins which can then be used to perturb and dissect cellular function.

This article was made for A*STAR Research by Wildtype Media Group