Sherif Abdelwahed, Ph.D., professor of electrical and computer engineering, is leading a team designing an instrument to automate data processing and analysis in the drug discovery process. The proposed system uses electronic visualization to confirm that a drug molecule is binding to the correct protein in order to be effective.
Confirming that a drug will bind to the right human protein target in a laboratory setting is a major unmet need in drug discovery and translational medicine, Abdelwahed said, adding that the need for rapid, precise antibody binding tests is particularly urgent in the fight against COVID-19.
Abdelwahed, along with researchers from Old Dominion University and Richmond-based industry partner Meru Biotechnologies, has received $700,000 from Virginia Catalyst to develop the new system, which is expected to deliver faster, more accurate results than current binding tests. Virginia Catalyst is a nonprofit corporation that advances economic development through life science research collaborations between industry and academia.
Proteins are structurally complex, and their natural three-dimensional shape is essential to proper function. Abdelwahed explained that current experiments to determine if a drug is binding to the right protein take place outside native cellular environments. This requires fixing the target protein to a solid surface, which nearly always alters a protein’s native shape and function, he said.
The system Abdelwahed and his colleagues are creating uses data processing techniques to eliminate researchers’ need to handle — and thereby alter — target proteins while a drug’s binding capabilities are tested. By automating this process, the researchers expect to help speed up approvals of new drugs by minimizing alterations to the proteins, which can cause costly errors.
A tiny camera mounted to the instrument takes pictures of the binding process as it unfolds in the lab. The pictures become the input for the data analysis phase.
“The process will take data all the way from the initial sampling and collection to the final result, without involving much user interaction,” Abdelwahed said. “It will be able to collect a lot of images and data and analyze [the drug and protein] behavior at every interaction.” This will allow researchers to identify binding anomalies quickly and produce a precise result.
A prototype of this instrument currently exists and is extremely accurate — almost to a fault. It’s so sensitive that it sometimes flags errors in a normal protein binding event. One of the refinements the team will make over the next year is teaching the instrument’s optical properties to recognize a range of acceptable binding outcomes.
Other Department of Electrical and Computer Engineering researchers working on this project are Carl Elks, Ph.D., an associate professor, and Ashraf Tantawy, Ph.D., an assistant professor. Graduate students will also have opportunities to work on this research.
“Automating this aspect of the drug discovery process using precise visual cues provides rich sources of data,” Abdelwahed said. “It could provide a kind of paradigm shift in how [protein] interactions are detected and quantified. The scientific potential, and also the commercial potential, are great.”