Researchers have shown how small structural changes in a key breast cancer receptor are directly linked to regulating molecules and can produce predictable effects in curbing or accelerating cancer growth.

This predictive statistical approach moves science on step closer to the development of more effective structure-based drug design to treat the disease.

The long term goal is for researchers to be able to predict proliferative or anti-proliferative activity of receptor molecule complexes by identifying structural changes that lead to specific outcomes. In many cases, researchers are able to identify structural features that could help guide more effective drug development.

In order to identify the root or estrogen receptor cell signaling that drive breast cancer cell proliferation, researchers synthesized more than 240 estrogen receptor binding molecules that led the cancer to proliferate. Researchers used a structural analysis to determine the basis for receptor activity.

A variety or drugs target signaling proteins like the estrogen receptor.

The new research suggests that certain structural changes might be made to the binding pocket to eliminate this negative side effect. Certain drugs can have different effects in different tissues because of structural changes often not discernable using traditional methods. This new approach reveals some mechanisms associated with tissue specificity and several predictive structural features.

In order to further test these signaling models, the team solves the atomic structure of some 76 different estrogen receptor-ligand complexes to better understand these responses.

Researchers are able to predict some of these effects be measuring the distance between two specific carbon atoms of the estrogen receptor.

This is the first time researchers have been able to use these atomic structures to identify how very small changes from the ligands have different outcomes, leading them towards the goal of predicting which ligands are going to make the most effective treatments for breast cancer.

Here's the source article.


Gerry Oginski
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