Screening Tool Identifies Aggregation-Resistant Proteins

Producing antibody therapies at a large scale can be difficult. Stresses encountered during manufacturing can disrupt the structure of proteins leading to aggregation and loss of activity. That could be changing as scientists at the University of Leeds and AstraZeneca have developed a technique that allows fragments of antibodies to be screened for susceptibility to aggregation much earlier in the drug discovery process. The approach is described today in Nature Communications.

When it comes to developing an antibody drug, scientists are not restricted to a single protein sequence. Fortunately, there is often an array of similar antibodies with the same ability of locking or binding tightly onto a disease-causing agent. That gives researchers a range of proteins to screen, to determine which are more likely to progress through the development process.

First, target proteins are cloned into the center of an enzyme that breaks down antibiotics in E.coli. This enables the scientists to directly link antibiotic resistance of the bacteria to how aggregation-prone the antibody fragment is. A simple readout gives an indication of whether the target protein will survive the manufacturing process. If the antibody proteins are susceptible to stress, they will unfold or clump together, become inactive, and the antibiotic will kill the bacteria. But if the protein chain is more stable, the bacteria thrives and will display antimicrobial resistance and will grow in the presence of the antibiotic. The scientists harvest the bacteria that have survived and identify the cloned protein sequence. That indicates which protein sequences to take forward in the development pipeline. The whole cycle takes about a month and increases the chances of success.

Second, scientists use the idea of natural selection where mutations or changes take place in the proteins, sometimes making them more stable. Directed evolution could generate better performing sequences that, at the current time, cannot even be imagined, let alone designed and manufactured. Like Darwin's natural selection, evolutionary pressure in this case is applied by the antibiotic and selects for the survival of bacteria that produce the protein variants that do not aggregate.

The protein sequences hosted in the bacterial cells that have shown resistance are harvested and their genes sequenced and scored, to select the best performing sequences. After a quick check to ensure that the new antibody sequences still retain their excellent binding capability for the original disease-causing target, they can be taken forward for further development.

"[In this approach], we are letting evolutionary selection change the sequence of the proteins for us and that might make some of them more useful as drug therapies. Importantly for industry, nature does the hard-work, obviating the need for so called rational engineering which is time- and resource-intensive, co-author Sheena Radford explained.

"As we do this, we will be putting the sequence information we gather into a database. As the database gets bigger, it may well be possible with artificial intelligence and machine learning to be able to identify the patterns in protein sequences that tell us that a protein can be scaled up for pharmaceutical production without needing any experiments. That is our next challenge and one we are tackling right now."