Antibiotics and antifungals have dramatically reduced deaths from microbial infections since the First World War but their value is increasingly being negated by rising drug resistance. However, new strategies are being developed that aim to target infection, while also avoiding routes that commonly trigger antimicrobial drug resistance.
One such strategy comes from researchers at the Keck School of Medicine at the University of Southern California. They have devised a new type of drug based on an existing natural molecule known as a theta-defensin, as described in a recent Scientific Reports paper. Old world monkeys produce these cyclic peptides naturally, but great apes such as gorillas, bonobos, chimpanzees, and humans do not.
“Old world monkeys that make these natural molecules at extraordinary high quantities every day are incredibly resistant to experimental sepsis. They are in the order of 10,000-fold more resistant to endotoxin [which contributes to sepsis] than humans,” Michael Selsted, professor of pathology at Keck and co-lead author of the study, told Clinical OMICs.
Selsted is also co-founder and CSO of Oryn Therapeutics, a biotech set up to develop these molecules and take them to the clinic. He said the discovery in old world monkeys is what set the company on this path 20 years ago.
The recent study tested an engineered theta-defensin designed to be even better at targeting infections than the natural molecules found in monkeys.
“Traditional antibiotics, which are currently used in the clinic, directly interact with the bacteria they directly kill or inhibit their growth. But the problem with that is bacteria have an immense ability to rapidly adapt and evolve,” explained Justin Schaal, assistant professor and colleague of Selsted’s at Keck, as well as first author on the recent study.
Theta-defensins take a different approach, interacting directly with the host and only indirectly with the microbe, they clear infections by stimulating the host immune system to attack the pathogens causing them.
Schaal’s engineered theta-defensin showed good results in a preclinical, animal study against Klebsiella infections. It is specially designed to target hard-to-treat gram-negative bacteria, but there are others researchers and companies working in this area. For example, biotech Atox Bio is working to develop similar immune modulators, but instead focuses on serious gram-positive bacterial infections.
An advantage of the theta-defensins are that they are small and stable and don’t trigger a large immune reaction. “The expectation is that this class of molecules will not generate an anti-drug antibody response which would neutralize it and make it useless,” explained Selsted.
They could also be used to target a range of pathogenic microbes, something not possible with standard antibiotics. Oryn’s research team is already working on developing antifungal drugs based on this approach.
“What we just published demonstrates that the traditional approach to antibiotic development is not the only way,” said Schaal.
César de la Fuente, an assistant professor at the University of Pennsylvania, agreed. He is also taking a different approach with his colleagues and instead using artificial intelligence (AI) to look for new antimicrobials, which he says are sorely needed.
“Antibiotic-resistant infections are predicted to kill 10 million people per year by 2050, corresponding to 1 death every 3 seconds… It is important to highlight that these drugs are not only useful to cure deadly infections, but are also crucial for modern medicine,” he said. “Interventions such as organ transplantation, chemotherapy treatments, childbirth, and surgeries would not be feasible without effective antibiotics.”
de la Fuente and colleagues recently published a paper on this topic in the journal Nature Biomedical Engineering. They used the human body as a source of potential new antimicrobials by developing an algorithm to automatically search through thousands of potential drug candidates.
They found several peptides that showed antibacterial activity and seemed to attack the outer membrane of the bacteria, a process that seemed to trigger less drug resistance than more standard antibiotics.
In addition to being able to sift through large amounts of data, AI has the advantage of speeding up the process. “AI can help accelerate the time that it takes to discover new antimicrobials and reduce the cost associated with this process. It currently takes more than 10 years and costs more than $1B to develop a novel drug; for context, this is more than the budget NASA has to take a rocket to the moon.”
This could help with an ongoing problem in antibiotic development, namely, that large development costs discourages many pharma and biotech companies from developing these drugs due to low return on investment.
Selsted also wants to use AI more at Oryn to help design better candidate drugs. “Now we have enough experience, we can start to apply AI algorithms to generate molecules that have features that arguably would be even more powerful,” he said.
“One of the things that AI is really good at is developing three dimensional models… you need to have a starting high-resolution three-dimensional structure of at least one of the compounds you’re dealing with. There are no crystal structures of these cyclic molecules that we’re working with. But we have crystallized several of them. So, we’re close now to be able to take very high-resolution three-dimensional images and begin that AI survey.”