Stopping malaria in its tracks

Developing a Better Malaria Vaccine Using AI Could Save Hundreds of Thousands of Lives Every Year

When biochemist Matthew Higgins founded his research group in 2006, he had malaria in his sights. The mosquito-borne disease is second only to tuberculosis in its devastating global impact. In 2020, malaria is estimated to have killed around 627,000 people, mostly children under the age of five, and nearly half the world’s population is affected, although Africa is by far the worst hit. Symptoms of the infection can start with fever and headache, making it straightforward to miss or misdiagnose and therefore leave untreated.

Preventing malaria is therefore a priority, which is why Higgins, a professor of molecular parasitology at the University of Oxford, is working tirelessly with his team to understand how the malaria parasite interacts with human host proteins. Their aim is to operate these insights to design improved therapies, including a vaccine that is far more effective than those currently available.

When a person is bitten by an infected female mosquito, one of five types of malaria parasite can enter the bloodstream. These single-celled parasites are usually transferred to the liver, where they mature and reproduce, releasing more into the bloodstream. Symptoms such as fever, chills, fatigue and nausea may not appear until 10 days to four weeks after the onset of infection, but the speed of diagnosis is crucial. Of the five species of parasites that cause malaria in humans, two are particularly threatening. For example, a Plasmodium falciparum infection can, if left untreated, suddenly progress to severe illness and death within a day.

A key challenge for Higgins is the changing nature of malaria parasites. Their ability to constantly change their appearance, as well as the appearance of the host’s cells (red blood cells), allows them to evade the human immune system. “When it comes to drug discovery or vaccine discovery, it’s hard to define it and decide what to pursue,” he says. The possibility of a fully effective vaccine – the only way to stop malaria – seemed distant.

The urgency of the race to develop an effective vaccine is underscored by the number of teams working toward this goal. Currently, RTS,S, commonly known by the brand name Mosquirix, is the only approved vaccine. It was designed with children in mind and was scheduled for release in October 2021. Its arrival was a “huge advance” and “very good news,” says Higgins. Because RTS,S only works on the first stage of infection, during which the malaria parasite enters the liver, its effectiveness is only about 30%. “30% is a big number. This means saving many lives,” he says. “But it’s far from the 100% we expected.”

Recently, another team from the University of Oxford, the Jenner Institute, announced promising results from another similar vaccine. Its effectiveness, which includes three doses followed by a booster one year later, is 77%. However, like Mosquirix, this vaccine captures the first phase of the malaria parasite’s life cycle, before the liver.

Meanwhile, Higgins—with his Oxford colleagues Simon Draper and Sumi Biswas—is developing vaccine immunogens for a multi-stage vaccine that can act simultaneously at each stage of the infection cycle. Beyond the parasite’s initial entry into human liver cells, the lab’s ultimate goal is a vaccine that can target not only the invasion of blood cells that follows infection, but also the final reproductive stage of the parasite’s life cycle, which involves the fusion of male and female gametes. Addressing this stage is vital because infected humans could otherwise transmit the parasite to previously uninfected mosquitoes if they are bitten again, continuing the cycle.

Progress has been hard-fought and tardy. To illustrate, consider the COVID-19 virus. This type of coronavirus has just one spike protein on its surface that a vaccine must target. Malaria parasites, on the other hand, have hundreds, even thousands, of surface proteins, according to Higgins. And it’s a slippery shapeshifter.

Most importantly, developing a vaccine containing a key infection-disrupting ingredient requires knowledge of the molecular structure of one gamete surface protein – Pfs48/45 – necessary for parasite development in the mosquito midgut. This is where Higgins and his team were derailed. Over the years, attempts have been made to decipher the shape of the protein, with narrow success. Even using the two best experimental techniques available for identifying the protein’s structure – X-ray crystallography and cryo-electron microscopy – the researchers were able to obtain only blurry, low-resolution images. As a result, their structural models of Pfs48/45 were necessarily imperfect and incomplete.

And that was until AlphaFold came along.

“We struggled with this problem for years, trying to get the detail we needed,” Higgins says. “Then we added AlphaFold to the mix. And when we combined our model with the predicted structure of Alphafold, we could suddenly see how the whole system worked.” Higgins recalls an exhilarating moment when his Ph.D. Kuang-Ting Ko – “who tried various methods to improve the experimental images” – rushed into the office with the news.

“That was a huge relief,” Higgins says, and a turning point for the project. The combination of painstaking experimental work and AI prediction quickly produced a piercing picture of Pfs48/45. “AlphaFold’s key information allowed us to decide which protein fragments we wanted to put into the vaccine and how we wanted to organize those proteins,” Higgins says. “AlphaFold allowed us to take our project to the next level, from basic science to preclinical and clinical development.”

AlphaFold isn’t without its flaws, of course. Higgins noted that while the AI ​​system did a good job of predicting how each module in the protein would take on its structure, there were times when its 3D visualizations were slightly off. For the most correct and reliable results, AlphaFold is best used in conjunction with more time-honored tools, such as cryo-electron microscopy, he says. “I’m sure AlphaFold’s predictions will continue to improve. But for now, combining experimental knowledge with AlphaFold’s models is the optimal approach because it allows us to piece everything together. We use that approach in many of our projects.”

Higgins’ collaborator, Professor Sumi Biswas, will lead a human clinical trial of Pfs48/45 in early 2023. Now that the structure of Pfs48/45 is known, it will enable Biswas’ and Higgins’ groups to work together to understand the immune response generated in these vaccination trials and to design improved vaccines. As they work to develop a vaccine that is effective at every stage of the malaria life cycle, Higgins is also making progress in understanding another target: a enormous protein elaborate that is key to the stage of malaria where the parasites infect red blood cells, causing the onset of disease symptoms. Using a combination of AlphaFold and cryo-EM, the team is working stiff to understand how this elaborate fits together.

Looking further into the future, Higgins envisions AlphaFold as a critical technology for creating novel, useful proteins from scratch, a process known as de novo protein design. “The future of AlphaFold may not be predicting molecules that already exist in cells, but rather predicting the structures of molecules that people are designing for specific applications, like vaccines,” he says. “If we can design proteins and then use AlphaFold to predict whether they’re going to fold the way we need them to, that’s very powerful.”