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Seeking a goldilocks molecule

Speed read
  • Peptides are short chains of amino acids sized ‘just right’ for interacting with human cells
  • Molecular modeling plus AI accelerates search for peptides to target COVID-19 infection
  • Peptide treatments may have fewer side effects and be easier and cheaper to produce than traditional drugs

You may have seen peptides advertised as the secret to increased athletic performance or younger-looking skin. But these naturally occurring molecules may hold the key to more significant medical breakthroughs, including treatments for COVID-19.

<strong>Uniquely customizable.</strong> Peptides have proven effective for enhancing athletic performance and younger-looking skin. But these naturally occurring molecules may also hold the solution to many medical problems. Like proteins, peptides are composed of amino acids. But unlike proteins, peptides are smaller and easier to break down. They are just the right size for interacting with the human body. Peptides are big enough to bind to cellular targets but small enough to penetrate the skin or intestines and enter the bloodstream.

But beyond collagen treatments for anti-aging and creatine for enhancing athletic performance, peptides’ unique abilities and customizability remain largely unexplored. Dr. Nora Khaldi, a bioinformatician and the founder of Irish biotech company Nuritas, believes that peptides hold the solution to many medical problems—we just haven’t found them yet. 

An ambitious investigation

One new area where peptides may prove valuable is in managing the novel coronavirus. Dr. Hansel Gomez Martinez, a data scientist and bioinformatician at Nuritas, is leading a search for a network of peptides to target COVID-19 infection.

<strong>Finding the right one.</strong> Dr Gomez is seeking peptides with an affinity for binding with the proteins on the surface of the SARS-CoV-2 virus. His team will also target the proteins in the human host cell that are involved in the COVID-19 life cycle. Courtesy David Orr. Nuritas combines artificial intelligence and big data techniques to discover peptides that can be used in new drugs. The company claims it can find relevant peptides 10 times faster and with 500 times more accuracy than traditional drug discovery methods. So far, it has developed several bioactive ingredients that are effective against inflammation, diabetes, and multi-drug resistant pathogens.

Gomez’s team is seeking peptides that demonstrate antiviral activity against SARS-CoV-2, the virus that causes COVID-19. Their research will focus on evaluating drugs already in the market or in advanced clinical trials because these have already been assessed for safe use in humans.

Molecular modeling techniques will help Gomez discover which peptides have an affinity for binding with the proteins of SARS-CoV-2. A secondary target will be proteins in the human host cells that are involved in the COVID-19 life cycle.

That all adds up to a lot of proteins. Modeling all of the proteins in the virus and the interacting partners in the host cells is “a vast dimension of target space,” says Gomez. Each of those targets must then be paired with any number of possible peptide drugs.

“This is a very ambitious investigation,” says Gomez. “The number of combinations of target proteins and candidate peptide drugs will be very high—in the hundreds of thousands.”

To tackle this challenge, Gomez was granted 40,000,000 core hours on Piz Daint, the fastest supercomputer in Europe. Hosted at the Swiss National Supercomputing Centre, access to Piz Daint is provided by the Partnership for Advanced Computing in Europe (PRACE) under a special “fast-track” program to supply computing resources for research that will mitigate the impact of the COVID-19 pandemic.  

<strong>Ambitious investigation.</strong> Pairing all of the proteins in the virus and partners in the host cell with possible peptide drugs will result in hundreds of thousands of interactions to model. Piz Daint, the fastest supercomputer in Europe will handle the calculations thanks to a special fast-track grant from PRACE.  “For every pair of target and peptide drug we will need to model the binding complex using computational tools in high-throughput experiments,” Gomez says. “Then, we will perform accurate binding energy estimations with the best pair candidates. Finally, we will combine this modeling strategy with the development of anti-viral predictors using state-of-the-art AI techniques to rank all peptides under consideration. This just isn’t feasible without supercomputers.”

To begin the research, Gomez will consider the full proteome of the SARS-CoV-2 virus, formed by 29 proteins. As for the host cells, he will initially consider 332 high-confidence targets, including 66 druggable human proteins, as reported in recent research. However, his team will continue to search for more and include as many targets as possible during their study. 

However, not all genetic sequences or other relevant clinical information about potential peptide drugs is readily available. AI methods will provide automatic information extraction and data curation expertise to find the missing information about potential peptide drugs.

Gomez will also use Nuritas’s AI platform to look for peptides that show an anti-inflammatory effect that could boost overall efficiency against COVID-19. 

“We are confident in our discovery capabilities,” says Gomez. “In the last 5 years, Nuritas has made significant progress in identifying bioactive peptides for several phenotypic areas—including ones relevant to COVID-19, such as anti-inflammation.”

Another advantage of peptide drugs is that they may present fewer off-target side effects than more traditional drug treatments. Because peptide therapeutics are typically less complex, an effective peptide treatment may be easier and cheaper to produce—a definite plus in our current situation where billions of people worldwide may require treatment. 

“We are already talking to external collaborators specializing in virology to test the antiviral efficacy of the candidate drugs we are hoping to find,” says Gomez.

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