Cystic Fibrosis Goes 3-D

3 D cystic fibrosis models used to develop new treatments

(RxWiki News) Movies are not the only thing getting the 3-D treatment. Researchers are using 3-D models of cystic fibrosis to discover new targets for treatment.

3-D models of a disease can allow researchers to examine the structure of the disease and identify potential targets for treatment.

Researchers can use the models to see if the molecules used for treatment attach to the particular target.  From there, the treatment could be tested further either in animal models or human tissue in the laboratory.

"Ask your doctor about cystic fibrosis screenings."

The research was led by Bruce Donald, PhD, from Duke University. Researchers focused on a way to block a protein-to-protein process that occurs in cystic fibrosis. To test if this treatment could be used to reduce cystic fibrosis symptoms, researchers developed 3-D models of cystic fibrosis.

Cystic Fibrosis is caused by a mutation in the protein, cystic fibrosis transmembrane conductance regulator (CFTR). The mutation causes the CFTR to improperly fold and can affect normal cell function. There are no treatments for the mutation and one of the problems involved with treating the symptoms is due to how fast the body recycles CFTR.

For recycling, a protein, CAL, attaches to CFTR which is then removed. The mutated CFTR sends out a signal that causes the recycling process to occur faster than usual. Researchers believed that if they could stop or slow down this process, it would help reduce cystic fibrosis symptoms.

Having CFTR remain inside the cell helps maintain part of the balance between salt and water transfer in the cell. The researchers looked at thousands of possible molecules that could bind with CAL and prevent it from attaching to CFTR and ranked them based on how well they attached to the protein.

The researchers developed 11 of the highest ranked computer-generated molecules. These molecules proved to be effective and had a stronger attachment to the CAL protein than the CAL protein had to CFTR. The computer-generated molecules were more efficient in how they attached to CAL.

When testing on human tissue in the lab, the highest ranked computer-generated molecule increased CFTR activity in the cell by 12 percent. Future tests can determine how much of an impact the increased CFTR activity has in reducing cystic fibrosis symptoms.

Researchers believe that this computer-generated molecule could be combined with an already known molecule that corrects the improper folding of CFTR and improves CFTR activity by 15 percent. Combining the two molecules could improve CFTR activity by 27 percent and could improve cystic fibrosis symptoms.

Funding was provided by the National Institutes of Health.

The study was published in the April edition of Public Library of Science Computational Biology.

Review Date: 
April 16, 2012