An interdisciplinary team of University of Pennsylvania (Penn) researchers has used a carefully designed algorithm to discover potentially thousands of antimicrobial peptides (AMPs) concealed within the human proteome. In vivo experiments showed that some of the lead “encrypted peptide antibiotics” demonstrated synergistic antimicrobial activity, and could target infections in rodent models.
“The human body is a treasure trove of information, a biological dataset,” said César de la Fuente, PhD, presidential assistant professor in bioengineering, microbiology, psychiatry, and chemical and biomolecular engineering, spanning both Penn Engineering and Penn Medicine. “By using the right tools, we can mine for answers to some of the most challenging questions … In this study, we applied a new way of using AI for antibiotic discovery in previously unrecognized places. What better place to start than by exploring our very own biological information, the collection of genes and proteins that make us who we are.”
de la Fuente, together with colleagues including postdocs Marcelo Torres, PhD, and Marcelo Melo, PhD, and collaborators Orlando Crescenzi, PhD, and Eugenio Notomista, PhD, of the University of Naples Federico II, reported on their research in Nature Biomedical Engineering, in a paper titled, “Mining for encrypted peptide antibiotics in the human proteome.”
CDC figures suggest that in 2019 there were 2.8 million antibiotic-resistant infections in the United States, leading to approximately 35,000 deaths, the authors noted. “Such untreatable infections are projected to reach 10 million people per year worldwide, becoming the leading cause of death in our society.” It’s a sobering scenario, especially given what the researchers refer to as a “lack of innovation in antibiotic discovery.” Most antibiotics available today have been used for more than 30 years, many have unintended side effects, and are losing effectiveness in the face of antibiotic resistance, the team pointed out. “Thus there is an urgent need to discover new antimicrobial agents to target drug-resistant infections.”
Antimicrobial peptides are small, naturally occurring molecules, produced by almost every living organism. Because of their ability to defend the body from infection, identifying new AMPs has been an active area of research, but traditional search methods, mostly based on chemical intuition and experimentation, have limited the discovery of peptide antibiotics beyond conventional AMPs.
Computational approaches could represent a promising approach to AMP design, and while the application of such methods for antibiotic discovery is still in its infancy, the researchers pointed out, “the computer-aided design of antimicrobial peptides (AMPs) has surged as a promising source of new bioactive compounds, which could provide alternatives to conventional antibiotics.”
The investigators’ approach to identifying new AMPs focused on the physicochemical characteristics that all AMPs have in common: they are 8 to 50 amino acids in length, positively charged, and possess both hydrophobic and hydrophilic parts. With these features set as requisite, the team could then generate a search function to identify peptides with antimicrobial properties, in genomes and proteomes.
“Imagine you want to find a specific word in a huge Word document such as an encyclopedia, said de la Fuente. “You would simply use the search function, set the parameters for the text you are looking for, and the algorithm would rapidly highlight all of the areas in the document that match. That’s essentially the approach we took when searching for new antibiotics. We knew the sort of molecules we were looking for and utilized the algorithm to act like a search function to find them throughout the human body.”
Through its search of the proteome—the complete set of proteins in the body—the algorithm returned 43,000 peptides of 8 to 50 amino acids in length, many of which were found in a region of the proteome unrelated to the immune system. This set of potential antimicrobials was then filtered to 2,603 encrypted peptides based on their fitness function inclusive of all the parameters. “We use the word ‘encrypted’ to describe the antimicrobial peptides we found because they are hidden within larger proteins that seem to have no connection to the immune system, the area where we expect to find this function,” de la Fuente commented.
To validate the antimicrobial properties of these algorithm-derived peptides, 55 were synthesized and exposed to eight different pathogens including E. coli and bacteria that cause staph infection and pneumonia. “We found that 63.6% of these 55 encrypted peptides displayed antimicrobial activity,” de la Fuente continued. “Interestingly, these peptides not only fought off infection by some of the most harmful bacteria in the world, they also targeted gut and skin commensal organisms that are beneficial to us. We speculate that this could be indicative of a microbiota modulating role that these peptides may possess as well.”
The team also tested the ability of the peptides to act synergistically and found that cocktails of peptides derived from the same biogeographic area within the body were able to potentiate their individual ability to fight off infection by 100-fold. “We also show, in vitro and in the two mouse models of infection, that encrypted antibiotic peptides from the same biogeographical area display synergistic antimicrobial activity,” the investigators wrote. “Remarkably, one pair of encrypted peptides synergized to kill pathogens at low micromolar to nanomolar concentrations both in vitro and in animal models, displaying activity comparable to, and with even higher potency in some cases than, the most potent venom-derived peptides and defensins from the human immune system.”
“This synergistic effect is likely already happening in our bodies,” commented de la Fuente. “Some of the peptides discovered by our algorithm exhibited antimicrobial activity at levels that are physiologically relevant. These molecules are found throughout the body, including the immune system. A surprising finding was that these peptides were not only encoded in the immune system but were also found in the digestive, circulatory, and nervous systems, for example, indicating that fighting off infections caused by invading organisms may be a more holistic approach than previously thought.”
When tested in vivo in relevant preclinical mouse models, these peptides again proved to fend off infection, decreasing the bacterial load by three orders of magnitude, an ability on par with known potent antibiotics and AMPs. Additionally, using these peptides as antibiotics in the mouse models did not lead to any signs of toxicity.
Bacterial resistance is one of the main concerns of antibiotic discovery, so the team also addressed this potential issue. “Because these encrypted peptides have potential to be applied as natural antibiotics, we need to understand how they influence the mutation of bacteria to understand if they will promote resistance,” stated de la Fuente. “What we found was that these encrypted molecules attack bacteria by permeating their outer membranes, an integral organelle for survival. This more damaging membrane permeation would require a great amount of energy and multiple generations of mutations to create resistance in bacteria, indicating that these newly discovered peptides are good candidates for sustainable antibiotics.”
The authors concluded, “Our results point to the proteome as a previously untapped source of novel antibiotics and reveal the multifunctional nature of numerous proteins that were traditionally thought to have only a single biological function … Because our approach computationally identifies antibiotics already optimized by nature and produced in our own bodies, we expect they will serve as excellent candidates for antibiotic development.”
Understanding that under certain circumstances there are some proteins that can be cleaved to secrete encrypted peptides will provide new insights into the human body’s ability to naturally protect itself against infection while it also conserves energy at the genomic level, where one gene encodes one protein, which can perform many useful functions beyond its initial physiological role. “… we speculate that the existence of proteins with multiple functions, enabled by encrypted fragments, reflects an evolutionary protein capability while minimizing genomic expansion,” the authors further explained. “This reduced the number of protein-coding genes that perform all the functionalities necessary to operate and defend the human body.”
“This work highlights that every organism is a dataset of code to which AI can be applied to find relevant molecules,” said de la Fuente. “This tool can potentially be applied to ‘omes’ other than the genome and proteome, such as the transcriptome and metabolome, to quickly and thoroughly search a wide range of places for those molecules, whether they be antimicrobial, anticancer, or antiviral, opening new doors in many areas of drug discovery and molecular research.”