June 21, 2023 — Researchers from the Wilmer Eye Institute, John Hopkins Medicine, have implemented artificial intelligence (AI) and machine-learning algorithms to successfully predict which small proteins can bind to cell structures and safely deliver therapeutic drugs to animal eye cells.
A collaboration with researchers from the University of Maryland, the project has potential for innovating new and more tolerable drug treatments for common, chronic, vision-threatening diseases like glaucoma and macular degeneration.
“We believe we are well on the way to finding solutions in trying to improve patient care and quality of life using drug delivery systems. The ultimate goal is creating something that we can translate out of the lab and actually make people’s lives better,” says Laura Ensign, Ph.D., the Marcella E. Woll professor of ophthalmology at the Johns Hopkins University School of Medicine. “Moving forward, researchers will need to find ways to further extend the duration of action, to test the success rate of the AI model’s drug delivery predictions with other drugs, and to determine safety in humans.”
New research published in Nature Communications, coauthored by Ensign, showed that “artificial intelligence-designed models accurately predicted an effective sequence of amino acids, also known as peptides or small proteins, that would bind to a particular chemical in rabbit eye cells and safely dispense medications over several weeks, reducing the need for frequent, strict treatment schedules,” explains a statement from John Hopkins Medicine. “The team specifically investigated peptides that bind to melanin, a compound that provides color to the eye but has the advantage of being widely present throughout specialized structures in eye cells.”
Wanting to find peptides that would successfully bind with a widespread eye compound, the team employed rapid machine learning using AI methods to predict an effective peptide sequence to try, according to Ensign.
The team fed the machine-learning model thousands of data points, enabling it to learn the properties of certain amino acid combinations so that it could predict peptide sequences for drug delivery using melanin. The AI model generated 127 peptides, and of these, the model predicted that a peptide called HR97 had the highest success rate of binding.
“To test the model’s prediction, researchers attached HR97 to the drug brimonidine—which is used to treat glaucoma by lowering inner eye pressure—and injected it into adult rabbit eyes. To determine HR97’s performance, researchers measured the levels of brimonidine in the eye cells by testing the cells’ concentrations of the drug after administering the experimental drug delivery system,” the statement explains. “They found that high amounts of brimonidine were present for up to one month, indicating that HR97 successfully penetrated cells, bound to melanin, and released the drug over a longer period of time. Researchers also confirmed that the eye pressure-lowering effect of brimonidine lasted for up to 18 days when bound to HR97 and found no indication of irritation in the rabbits’ eyes.”
For more information: hopkinsmedicine.org.