Scientists have harnessed a computational approach usually used in oil exploration to search for cures for rare genetic diseases such cystic fibrosis. By using the method to analyse the spatial relationships between different variants of a protein, instead of the relationships between test wells across an oil field, the researchers can obtain valuable information on how disease affects a protein’s underlying shape and how drugs can restore that shape to normal.
The new method, detailed in the journal Structure, runs with just a few gene sequences collected from people with disease. Then, it determines how the structure of each corresponding variant protein is associated with its function, and how this functional structure can affect pathology and be repaired by therapeutics. To test the techniques, the researchers showed why existing drugs for cystic fibrosis fall short of curing the disease.
“This is an important step forward for treating rare diseases,” said senior author William Balch, PhD, professor of Molecular Medicine at Scripps Research. “The fact that we can get so much information from a few gene sequences is really unprecedented.”
Studies on inherited diseases often rely on the precise three-dimensional shape of a protein affected by disease. But genetic diseases can be caused by thousands of gene variants, some of which destabilise or change the protein shape in ways that make isolating the protein for further investigation much more difficult than usual.
Prof Balch, with Scripps Research senior staff scientist Chao Wang and staff scientist Frédéric Anglés, instead wanted to use natural variation to their advantage. So the group developed a method called variation-capture (VarC) mapping to analyse the natural array of gene sequences which exist in the human population and determine the mechanism by which they each changed a protein’s structure to cause disease.
Among other statistical tools, Prof Balch’s group integrated the methods that oil companies use to draw inferences about the location of an oil reservoir using only a small number of test wells. With only a few gene sequences, this let the researchers determine the most likely structural mechanisms driving function for each variant leading to disease, as well as model how drugs impacted those structural functions.
In the case of cystic fibrosis, disease is caused by genetic variants in the cystic fibrosis transmembrane conductance regulator (CFTR), leading to a buildup of mucus in the lungs. More than 2000 variants of the CFTR gene have been identified, and many of these variants were known to have very different effects on the CFTR protein, but it has been difficult to compare and contrast these variants to guide how patients with different variants should be treated differently in the clinic.
“When you want to treat patients, you really have to appreciate that different therapeutics might target different variants in completely different ways, and that’s why our approach that looks at many different variants all at once is so powerful,” explained Wang. “Our approach not only reveals how these variants contribute to each patient’s biology, but also connects them in a way that each variant can inform how to manage the others.”
The researchers input about 60 genetic variants found in the cystic fibrosis population into their VarC program. The analysis captured how each amino acid residue talks to every other residue to generate function, and revealed that most of the cystic fibrosis patients had the same net effect on the protein: an unstable inner core.
When the program modelled how existing cystic fibrosis drugs impacted the structures, the researchers discovered that, despite the drugs’ effect on CFTR structure, none of them effectively stabilised the protein’s hidden inner core. This was like how the location of an oil reservoir in a complex landscape can be revealed by test wells.
Now that the researchers better understand the structural deficiencies in CFTR in cystic fibrosis patients, they say that the job of developing an effective drug to fix it is much easier. Potential compounds can be modelled in advance of lab experiments for their effect on the inner core of the CFTR protein.
“In most drug discovery, you throw thousands of compounds at a protein and see which ones change it, often without fully understanding the mechanism,” said Prof Balch. “To fix a thing, you must first understand the problem.”
Already, his team is applying the method to other rare genetic diseases, as well as pursuing new drugs to treat cystic fibrosis.
Source: Scripps Research Institute
