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Pronota’s Approach to Proteomics

By Malorye Allison
June 13, 2007 | ‘The key reason proteomics hasn’t delivered yet is that everyone is discovering the same 50 proteins over and over again,” says Koen Kas, CSO of Belgium’s Pronota (formerly Peakadilly). Pronota is one company now trying to change that state of affairs. (I’ll be examining the efforts of other second-generation ‘omics companies to change drug and diagnostic discovery and development in future columns.)

Kas and his colleagues are building a protein biomarker discovery platform to find novel markers for blood-based diagnostic tests. As serum is both complex and disproportionately laden with certain proteins, they need tools to pick “needles” from a protein haystack. For this, they’ve brought on some elegant new technology, including special tagging chemistry and towering chromatography columns.

But the core of Pronota’s approach is a focus on sample integrity.

Some basic issues, such as making sure the cohorts studied are well defined, are just as important for proteomics as any other field. But there are unique issues as well, such as how to circumvent the problem of overabundant proteins. Human plasma contains more than 1 million different proteins, yet a mere 22 make up 99% of the total. “The emphasis has always been on depleting samples of those proteins, but that is not enough,” Kas explains.

The real problem, he says, is that proteases degrade the sample from the moment it is taken. “As high abundance proteins degrade, you get a lot more noise,” he says. “This explains why low sensitivity platforms always find small peptides from the same proteins,” such as proteins from the inflammatory cascade. Hence, many proteomic studies are unearthing only artifacts. “Stopping degradation is at least as important as depleting the overabundant proteins,” Kas says.

Pronota’s platform is based on liquid chromatography and mass spectrometry. The company has a couple of unique tools for this. First, there are 9-feet high affinity chromatography columns. “Our extra long columns isolate more peptides and you end up sending a less complex mixture to the mass spec,” Kas says.

Another Pronota proprietary tool is a chemical tagging technique that speeds protein identification and thus allows scientists to spend more time identifying novel proteins. First, an acetyl group is attached to the amino-terminal peptide of each protein, which is then digested and run on reverse-phase chromatography. A chemical is then added that reacts with every amino peptide, except the first acetyl-tagged peptide. The peptides are then run again on the reverse phase column. “The unique peptide sits at the same spot, but all the others have shifted,” Kas says.

Predicting Response
That tagged peptide can now serve as a “signature” of that particular protein in the mixture when it is analyzed via mass spectrometry. “We can thus reduce the complexity of the samples and analysis time and focus only on peptides that are novel.” Kas says this reduces the complexity of the samples 40-fold: Instead of reading 40 peptide signatures for each protein, the scientists are looking for the spectra of just one tagged peptide per protein, providing time to study even more proteins.

Pronota’s scientists argue that these tools are letting them do something that was previously impossible for most groups. “We are making more protein identifications,” Kas says, “and we see proteins in the 10 nanogram per ml range, which is the level of sensitivity you need to find clinically relevant markers.” Kas and his colleagues claim their proteomics data is now as reliable as gene expression data, which is ahead of proteomics in terms of its acceptance for clinical use.

The Pronota platform, which is called Masstermind, has already been tested on samples from various infectious diseases, and was able to predict response (and nonresponse) to treatment. “We have identified proteins that make complete sense as markers in the context of the biology,” he says. That type of proof of concept was particularly important, because there is so much skepticism about proteomics now. “We needed to prove we could find markers from plasma,” Kas says.

The company has raised $18 million in capital and aims to build relationships with pharmaceutical companies in which Pronota will develop companion diagnostics for drugs in development. Pronota will also be developing internal programs.

One area where the company specializes is the study of proteases. Using Pronota’s approach, it should be possible to identify the off-target effects of novel protease inhibitors just by looking for the appearance or disappearance of particular peptides in a blood sample.

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