Race to cure a billion people from deadly parasitic disease

Scientists accelerate search for life-saving treatments for leishmaniasis

“We were about to give up,” says Dr. Benjamin Perry, a medicinal chemist at Drugs for Neglected Diseases Initiative (DNDi)When Perry joined the organization seven years ago, based in Geneva, Switzerland, his goal was to accelerate the discovery of up-to-date treatments for two potentially deadly parasitic diseases, Chagas disease AND LeishmaniasisOverall, they have had many successes. However, with one potential leishmaniasis drug in DNDi’s diverse portfolio, progress has almost come to a standstill.

“We couldn’t find ways to make changes that would improve the drug molecule,” Perry says. “It either lost all its potency as an antiparasitic agent or stayed the same.”

But that all changed when Perry and his colleagues heard about DeepMind’s AI system, AlphaFold. Now, using a combination of scientific detective work and AI, the researchers have charted a path to turning the molecule into a real treatment for a devastating disease.

Novel treatments for leishmaniasis can’t come soon enough. The disease is caused by Leishmania parasites and spreads through the bites of sand flies in countries Asia, Africa, America and the Mediterranean.

Visceral leishmaniasis, the most severe form, causes fever, weight loss, anemia and enlargement of the spleen and liver. “If it’s left untreated, it’s fatal,” says Dr. Gina Muthoni Ouattara, senior medical director at DNDi in Nairobi, Kenya. Cutaneous leishmaniasis, the most common form, causes skin lesions and leaves enduring scarring.

Globally about one billion people are at risk of leishmaniasis and every year it is 50-90,000 new cases of visceral leishmaniasismost in children. While medical treatment varies by region, most are lengthy and associated with significant side effects.

In East Africa, the first-line treatment for visceral leishmaniasis is a 17-day course of two daily injections consisting of two separate drugs, sodium stibogluconate and paromomycinadministered in a hospital setting. “Even for an adult, these injections are very painful, so you can imagine having to give a child these two injections every day for 17 days,” Ouattara says. Before DNDi’s pivotal work to develop a shorter and more effective combination therapy, this treatment lasted 30 days.

Alternative treatments require intravenous infusions that must be refrigerated and administered under sterile conditions. “The biggest limitation is that all of these treatments have to be administered in a hospital setting,” Ouattara says. That increases costs and means patients and their caregivers lose income, school and family time. “It really affects communities.”

Previous DNDi efforts have already reduced the time visceral leishmaniasis patients spend in the hospital. But the organization’s ultimate goal is to develop an oral treatment that could be administered in a community health facility or even at home.

This kind of radical improvement may require entirely up-to-date drugs. If you’re looking for entirely up-to-date compounds that can be developed into drugs, where do you start?

DNDi’s approach to drug discovery in this area of ​​research could be called “old school,” Perry says, though he says there’s a reason for that—it’s often the best way to discover drugs. First, scientists screen thousands of molecules to find those that show promise in attacking the disease-causing organism as a whole. Then they modify those molecules to try to make them more effective. “It’s a little more ‘brute force,’” he says. “We don’t usually know how it does it.”

Perry says this trial-and-error approach is the best way to find up-to-date treatments for patients. But the optimization stage can feel like a struggle in the murky. “You think, ‘OK, I’ve got this chemical, just make some random changes to it,’ and sometimes it works,” Perry says. But with their promising leishmaniasis molecule, they hit a brick wall. “We tried that and it didn’t work.”

As hope dwindled, DNDi sent a particle to Michael Barrettprofessor at the University of Glasgow in the UK who has been using a technique called metabolomics to discover how drugs work.

“There are all kinds of chemical processes going on in our bodies where we break molecules down into their component parts and then rebuild them,” Barrett says. “That’s the basis of life, really.” Together, these chemical reactions make up our metabolism. Parasites, like the one that causes leishmaniasis, also have metabolisms.

Metabolic reactions are regulated by biological catalysts known as enzymes. Many drugs work by interfering with these enzymes, so Barrett and his group look for changes in molecules that are created during metabolic reactions to figure out what the drug does.

He put the DNDi molecule on Leishmania parasites. “Of course, the metabolism changed,” he says. Barrett and his colleagues saw a gigantic escalate in one molecule that is meant to be turned into phospholipids, a type of fat molecule that makes up cell membranes. But at the same time, the number of phospholipids actually being made went down.

Barrett discovered that the enzyme that would turn the first molecule into phospholipids was the one the drug affected. Interrupting that reaction was how the molecule killed the parasite.

But after overcoming one obstacle, Barrett’s group ran into another. They wanted to know what their target enzyme looked like, but figuring out its structure experimentally would be nearly impossible because it was a type of protein that’s notoriously arduous to work with in the lab. “It gets embedded in the membrane, which makes it really hard to play with,” Barrett says.

That could have been the end of the story. Instead, Perry put Barrett in touch with researchers at DeepMind who were working on Alpha-Compositionan AI system that predicts the three-dimensional structure of a protein based on its amino acid sequence. The AlphaFold team took the amino acid sequence of a target protein and came back with exactly what Barrett and his colleagues needed: a prediction of its three-dimensional structure.

Barrett’s group took that structure and the structure of the DNDi molecule and was able to figure out how they fit together—at least virtually figuring out how the drug binds to the protein.

Since then, DeepMind, in collaboration with the European Bioinformatics Institute EMBL, has developed a database containing millions of protein structures available to researchers. The open-source implementation of the AlphaFold system is also available“Anyone can now just take their protein’s amino acid sequence, plug it into AlphaFold, and get the structure,” says Barrett. “It’s revolutionary.”

“That’s the biggest change that AlphaFold has made in the scientific community, to me,” Perry says. “People are always asking, ‘Have we looked at the structure of AlphaFold?’ That’s become common parlance.”

Access to protein structure predictions is proving useful to drug discovery researchers in several ways.

There are more than 20 different species of Leishmania parasites that cause disease in humans, but Barrett’s group is working with just one species, Leishmania mexicana. Although much of what they find translates to others, it’s not certain—so they have to check all their findings. “We can get the Leishmania donovani version of this target gene, and we can run it through the AlphaFold algorithm very quickly, and see if the donovani version folds the same way as the mexicana version?”

There is also a human version of the Barrett target enzyme identified in the Leishmania parasite. Scientists will need to make sure that only the parasite version of the enzyme is attacked by the up-to-date drug to avoid potential side effects in patients – which will be easier if they know what the human version looks like. “We also got this structure from AlphaFold,” Perry says.

Of course, AlphaFold can’t accurately fold every possible protein. And for those it can, the structure alone doesn’t provide everything drug discovery researchers need. The next step would be to develop an AI system that could predict docking—taking a structure and a drug and figuring out where they fit together.

Although the molecule Barrett discovered has a long way to go before it becomes a real treatment for leishmaniasis—if it ever does—AlphaFold has shown that it can lower the barrier to testing up-to-date drugs. For researchers hunting for up-to-date drugs for neglected diseases, where funding is often constrained, that could have huge implications.

When drug discovery researchers don’t know how to optimize a promising molecule, moving beyond quick and effortless fixes means investing much more time and money. When funding is tight, it’s a harder sell. “We can’t throw the kitchen sink at neglected tropical diseases because there’s no money,” Barrett says.

But a tool like AlphaFold could be accessible to researchers who can’t employ exorbitant equipment to determine the chemistry of their compounds. “Most of the diseases we work with are endemic in countries where the infrastructure isn’t necessarily as good,” Perry says.

If AlphaFold can facilitate reveal how a molecule works in a disease by revealing the structure that a drug is targeting—as it did with the potential up-to-date leishmaniasis drug DNDi—it could also lithe a path for medicinal chemists like Perry to turn a dead end into a real treatment. “We couldn’t look at this fancy way our molecule interacts with the structure and say we just need another carbon here, or we can get rid of this nitrogen, move this—those kinds of things were out of reach for us,” he says. “But they’re out of reach now.”