Effect
Researchers are accelerating their search for life-saving treatments for leishmaniasis
“We were ready to give up,” says Dr. Benjamin Perry, a pharmacist 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 new treatments for two potentially fatal parasitic diseases, Chagas disease and leishmaniasis. In general, they achieved many successes. However, for one potential leishmaniasis drug in DNDi’s diverse portfolio, progress had almost stalled.
“We couldn’t find ways to make changes that improved the drug molecule,” says Perry. “Either it lost all its potency as an antiparasitic or it remained the same.”
However, things changed when Perry and his colleagues heard about DeepMind’s AI system, AlphaFold. Now, using a combination of scientific research and artificial intelligence, researchers have opened a path to turn the molecule into a real cure for a devastating disease.
New treatments for leishmaniasis cannot come soon enough. The disease is caused by parasites of the genus Leishmania and is spread through sand fly bites in various 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 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 lasting scars.
Patient with visceral leishmaniasis and HIV co-infection. Credit: University of Gondar
Globally, approx one billion people are at risk of leishmaniasis and every year there are 50-90,000 new cases of visceral leishmaniasis, the majority in children. While medical treatments vary by region, most are time-consuming and have significant side effects.
In East Africa, first-line treatment for visceral leishmaniasis involves a 17-day course of two injections each day of two separate drugs, sodium stivogluconate and paromomycin, is administered at the hospital. “Even for an adult, these injections are very painful, so you can imagine having to give these two injections to a child every day for 17 days,” says Ouattara. Before DNDi’s critical work to develop a shorter and more effective combination therapy, the treatment lasted 30 days.
An alternative treatment requires an intravenous infusion that must be refrigerated and administered under sterile conditions. “The most limiting thing is that all these treatments have to be done in the hospital,” says Ouattara. This increases costs and means patients and their carers miss out on income, school and time with family. “It really affects communities.”
People always ask, “Have we looked at the AlphaFold structure?” It has become common ground.
Michael Barrett, biochemist and parasitologist
DNDi’s previous efforts have already reduced the length of time patients with visceral leishmaniasis spend in hospital. But the organization’s ultimate goal is to come up with an oral treatment that could be administered at a local health facility or even at home.
This kind of radical improvement may require entirely new drugs. If you’re looking for entirely new compounds to turn into therapies, where do you start?
DNDi’s approach to drug discovery in this area of research could be called “old school,” Perry says, though he argues there’s a reason for that — it’s often the best way to discover drugs. First, researchers screen thousands of molecules to find those that hold promise for attacking the disease-causing organism as a whole. They then modify these molecules to try to make them more effective. “It’s a little more ‘brutal,'” he says. “Usually we don’t know how he does it.”
Benjamin Perry and Gina Muthoni Ouattara. Credit: DNDi
This trial-and-error approach is the best way to find new treatments for patients, Perry says. But the optimization stage can feel a bit like stumbling around in the dark. “You’ll say, ‘OK, well, I’ve got this chemical, just make some random changes to it,’ which sometimes works,” Perry says. But with the promising leishmaniasis molecule, they would hit a brick wall. “We had tried it and it didn’t work.”
In hopes of reducing it, DNDi sent the molecule to Michael Barrettprofessor at the University of Glasgow, UK, who for the past decade has been using a technique called metabolomics to reveal how drugs work.
“There are all kinds of chemical processes that happen in our bodies where we break molecules down into their component building blocks and then build them back up,” says Barrett. “That’s the basis of life, really.” Collectively, these chemical reactions make up our metabolism. Parasites, such as the one that causes leishmaniasis, also have a metabolism.
Metabolic reactions are regulated by biological catalysts known as enzymes. Many drugs work by interfering with these enzymes, so Barrett and his team look for changes in the molecules created during metabolic reactions to understand what a drug does.
He put the DNDi molecule into a Leishmania parasite. “Definitely, the metabolism changed,” he says. Barrett and his colleagues saw a large increase in a molecule whose job it is to convert into phospholipids, a type of fat molecule that makes up cell membranes. However, at the same time, the number of phospholipids actually produced was decreasing.
Barrett discovered that the enzyme that would have converted the first molecule into phospholipids was the one affected by the drug. Stopping this reaction was how the molecule killed the parasite.
Stella Akiror and John Oseluo download details after checking on a patient. Credit: Lameck Ododo – DNDi
But with one hurdle in the way, Barrett’s team hit another. They wanted to know what their target enzyme looked like, but finding its structure experimentally would be nearly impossible because it was a type of protein that is notoriously difficult to work with in the lab. “It gets embedded in the membrane, and that makes it really hard to fiddle with,” says Barrett.
That could have been the end of the story. Instead, Perry put Barrett in touch with researchers at DeepMind who were working on it AlphaFold, an AI system that predicts the 3D structure of a protein from its amino acid sequence. The AlphaFold team took the amino acid sequence of the target protein and returned with exactly what Barrett and his colleagues needed: a prediction of its three-dimensional structure.
Barrett’s team took that structure, and the structure of the DNDi molecule, and were able to figure out how they fit together—determining, essentially at least, how the drug binds to the protein.
Most of the diseases we work with are endemic in countries where the [scientific] The infrastructure is not necessarily that big.
Benjamin Perry, Medicinal Chemist
Since then, DeepMind, in collaboration with EMBL’s European Bioinformatics Institute, has done a database of millions of protein structures available to researchers. An open source implementation of the AlphaFold system is also available. “Anyone can now just take their protein amino acid sequence, plug it into AlphaFold and get a structure,” says Barrett. “It’s revolutionary.”
“That, to me, is the biggest change that AlphaFold has made in the scientific environment,” says Perry. “People always ask, ‘Have we looked at the AlphaFold structure?’ It’s become common ground.”
Access to protein structure predictions is proving useful to drug discovery researchers in many ways.
There are more than 20 different species of the Leishmania parasite that cause disease in humans, but Barrett’s team is working with just one species, Leishmania mexicana. While much of what they find translates to others, it’s not a given – so they need to cross-check any findings. “Can we take the Leishmania donovani version of this target gene, can we put it through the AlphaFold algorithm very quickly and see, does the donovani version fold the same way as the mexicana version?”
There is also a human version of the Barrett target enzyme identified in the Leishmania parasite. Researchers will need to make sure that only the parasite’s version of the enzyme is attacked by a new drug, to avoid potential side effects for patients – which will be easier if they know what the human version looks like. “We took that structure from AlphaFold as well,” says Perry.
Of course, AlphaFold cannot accurately fold every possible protein. And for those who can, structure alone doesn’t provide everything researchers need for drug discovery. The next step of change would be to develop an artificial intelligence system capable of predicting the connection – taking the structure and the drug and understanding where they fit together.
While there is still a long way to go before the molecule Barrett uncovered becomes a real treatment against leishmaniasis – if it ever gets there – it has proven that AlphaFold can lower a barrier when it comes to investigating new drugs. For researchers looking for new treatments for neglected diseases, where funding is often limited, this could make all the difference.
When drug discovery researchers are in the dark about how to optimize a promising molecule, going beyond quick and easy tweaks means investing much more time and money. When funding is scarce, it’s harder to sell. “We can’t throw kitchen sinks at neglected tropical disease issues because the money isn’t there,” says Barrett.
But a tool like AlphaFold could be accessible to researchers who can’t use expensive equipment to trace the chemistry of their compounds. “Most of the diseases we work with are endemic in countries where the infrastructure isn’t necessarily that great,” says Perry.
If AlphaFold can help reveal how a molecule works against a disease by making visible the structure targeted by the drug – as it did with DNDi’s potential new leishmaniasis drug – it could also light a path to pharmacists like Perry to turn a blind eye. molecule in 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 get rid of this nitrogen, move it around—those kinds of things were off limits for us. ». He says. “Except now, which isn’t.”