A race to cure 1 billion people from fatal parasitic diseases

Researchers accelerate search for life-saving treatments for leishmaniasis

“We were about to give up,” says Dr. Benjamin Perry, a drug chemist with the Deathly Disease Initiative (DNDI). When Perry joined the organization seven years ago based in Geneva, Switzerland, his goal was to speed up the discovery of two potentially new therapies: potentially fatal parasitic diseases: Chagas disease and Leishmaniasis. Overall, they have had many successes. However, for one potential leishmaniasis drug in DNDI’s diverse portfolio, progress has largely halted.

“We couldn’t find a way to make changes to improve the drug molecule,” says Perry. “It either lost all its potency as an antiparasitite or it remained the same.”

But things changed when Perry and his collaborators heard about the Deep Mind AI system, Alphafold. Now, using the combination of scientific detective work and AI, researchers paved the way for turning molecules into real-life treatments for catastrophic diseases.

New treatments for leishmaniasis will not come anytime soon. The disease is caused by parasites of the genus Leishmania and spreads through sand bites in Asia, Africa, America and Mediterranean countries.

The most severe form of visceral leishmaniasis causes fever, weight loss, anemia, and enlargement of the spleen and liver. “If you’re not receiving treatment, it’s fatal,” says Dr. Gina Mutoniwattara, senior medical manager at DNDI in Nairobi, Kenya. The most common form of skin leishmaniasis causes skin lesions and leaves the wounds that persistently affect the leaves.

Globally, around 1 billion people are at risk of leishmaniasis, with 50-90,000 new cases of visceral leishmaniasis each year, with the majority being children. Medical care varies from region to region, but most are long and have serious side effects.

In East Africa, first-line treatment for visceral leishmaniasis involves a 17-day course of two separate drugs administered in the hospital, two separate drugs, stibogluconate and paromomycin. “Even for adults, these injections are so painful that you can imagine having to give your child these two injections every day for 17 days,” says Ouattara. This treatment lasted 30 days before important work to develop shorter and more effective combination therapy for DNDI.

Alternative treatments require intravenous infusion. It should be refrigerated and administered under infertility conditions. “The most limiting thing is that all of these treatments have to be given in the hospital,” says Ouattara. It adds to the cost and means that patients and their caregivers missed out on income, school and time with their families. “It really impacts the community.”

Previous efforts by DNDI have already reduced the time spent in hospitals for visceral leishmaniasis patients. But the ultimate goal of an organization is to come up with oral treatments that can be managed in local medical facilities and even at home.

Such a radical improvement may require a whole new drug. If you’re looking for a completely new compound that turns into a treatment, where do you start?

DNDI’s approach to drug discovery in this field of research could be called “old school,” Perry says, but he argues there’s a reason for this. First, researchers will screen thousands of molecules to find promising molecules by attacking the entire disease-causing organism. Then try to fine-tune those molecules to make them more effective. “It’s a little more of a ‘brute force’,” he says. “We usually don’t know how it’s doing.”

This trial and error approach is the best way to find new treatments for patients, says Perry. However, the optimization stage can feel like you’re tripping in the dark. “You’re fine, well, I have this chemical, just make some random changes to it,” and it works from time to time,” says Perry. But with their promising leishmaniasis molecules, they hit a brick wall. “We tried it, but it didn’t work.”

As hope was declining, DNDI sent the molecule to Michael Barrett, a professor at the University of Glasgow, UK. For the past decade, Michael Barrett has been using a technology called metabolomics to understand how drugs work.

“All kinds of chemical processes occur in our bodies, where we cut the molecules into components of the component and then reconstruct them,” Barrett says. “That’s really the basis of life.” Collectively, these chemical reactions constitute our metabolism. Parasites are also metabolism, just like those that cause leishmaniasis.

Metabolic reactions are regulated by biological catalysts known as enzymes. Because many drugs work by interfering with these enzymes, Barrett and his group are looking for changes in the molecules created during the metabolic reaction to understand what the drug is doing.

He puts the dndi molecule on the leishmania parasite. “Of course, my metabolism has changed,” he says. Barrett and his colleagues saw a major increase in one molecule, which is transforming into a phospholipid, a kind of fatty molecule that makes up the cell membrane. However, at the same time, the number of phospholipids actually produced had decreased.

Barrett realized that the enzyme that would have transformed the original molecule into a phospholipid was one that was influenced by the drug. Discontinuing this reaction was how the molecules were killing parasites.

However, because he had one obstacle, Barrett’s group hit another obstacle. They wanted to know what the target enzyme looks like, but finding its structure experimentally is nearly impossible as it is a type of protein that is difficult to work in the lab. “It’s embedded in the membrane, which really makes it difficult to tinker with,” Barrett says.

That could have been the end of the story. Instead, Perry contacted Barrett with researchers at Deepmind who was working on Alphafold, an AI system that predicts the 3D structure of proteins from amino acid sequences. The AlphaFold team adopted the amino acid sequence of the target protein, reverting back exactly what Barrett and his colleagues needed: predictions of 3D structure.

Barrett’s group adopted its structure and the structure of the molecules of dndi, allowing us to understand how they fit together – at the very least, fixing how the drug binds to the protein.

Since then, DeepMind has worked with EMBL’s European Institute of Bioinformatics to create a database of millions of protein structures available to researchers. An open source implementation of the AlphaFold system is also available. “Everyone can ingest a protein amino acid sequence and connect it to an alphafold to bring out the structure,” says Barrett. “It’s innovative.”

“This is the biggest change that Alphafold has made to the scientific environment for me,” Perry says. “People always ask themselves, ‘Did we see the structure of the alphafold?” has become a general term. ”

Access to protein structure predictions has proven useful in many ways for drug discovery researchers.

There are over 20 species of Leishmania parasites that cause human disease, but the Barrett group works with a single species, Leishmania Mexicina. Much of what they find is translated to others, but it is not given. Therefore, they should cross-check the findings. “I can get a Leishmania Donovani version of that target gene. Can I place it in the Alphafold algorithm very quickly and fold the Donovani version in the same way as the Mexicana version?”

There is also a human version of the target enzyme valet identified in Leishmania parasites. Researchers should ensure that only versions of the parasite enzymes are under attack from the new drug to avoid potential side effects in patients. This is easy if you know what a human version looks like. “We got that structure from Alphafold too,” Perry says.

Of course, Alphafold cannot accurately fold all possible proteins. And for those who can do that, structure alone doesn’t provide everything a drug discovery researcher needs. The next step change is to develop an AI system that can predict docking – taking the structure and drugs and knowing where they fit together.

Although there is still a long way to go before the molecules that have been elucidated become a real treatment for leishmaniasis — if it gets there, Alphafold has demonstrated that it can lower the barriers when it comes to researching new drugs. Funding is often tough, so this can make all the difference for researchers hunting new treatments for neglected illnesses.

When drug discovery researchers are in the dark about how to optimize promising molecules, moving beyond quick and easy adjustments can invest more time and money. If you’re short on funds, that’s a more difficult selling. “We can’t throw a kitchen sink into a neglected tropical disease problem because the money isn’t there,” Barrett says.

However, tools like Alphafold may be accessible to researchers who cannot identify the chemistry of a compound using expensive equipment. “Most of the illnesses we work in are endemic in countries where the infrastructure isn’t necessarily so great,” says Perry.

If Alphafold helps to understand how molecules work on disease by making the structures the drug targeted, as did with DNDI’s potential new leishmaniasis drugs, drug chemists like Perry could light the way that transform dead-end molecules into real-life treatments. “We can’t see this flashy way our molecules interact with our structure, and here we need another carbon or remove that nitrogen and move this. “Now, it’s not.”