Breaking boundaries in biomedicine: Advanced Photon Source enables protein design

By Judy Myers

This advancement has wide applications for biomedicine and environmental protection.

From growth hormones to cancer drugs, small molecules play a crucial role in our health. Monitoring them is essential to keeping us healthy; it enables physicians to calculate dosages and patients to monitor their medical conditions at home, for example.

Monitoring small molecules depends on sensing where they are, and in what concentrations. While scientists have developed sensors to detect some small molecules, these sensors are used primarily in research and drug discovery and can only detect a limited range of molecules with particular qualities. There is a compelling need for sensors that can detect and signal the presence of diverse small molecules of different shapes, sizes, flexibility and polarity. 

Using artificial intelligence (AI), a team of scientists led by Nobel Prize winner David Baker at the University of Washington has created a computational method for generating proteins that bind and signal a wide range of small molecules with great effectiveness. Baker won the 2024 Nobel Prize in Chemistry for computational protein design.

The research described here, published in Science and conducted in part at the Advanced Photon Source (APS), exemplifies that approach. The APS is a U.S. Department of Energy (DOE) Office of Science user facility at DOE’s Argonne National Laboratory.

The sensor design problem

Creating a protein sensor for small molecules is very difficult. The protein must first bind to the small molecule, then signal its presence. 

The team solved both problems with modular design strategies. Their AI-generated proteins consist of identical repeating subunits surrounding a central cavity. The cavity holds a pocket where the small molecule binds.

The subunits, being modular, are easily disassembled. In this way, the small molecule binding proteins can be treated like Lego blocks and be connected to well-established signaling proteins (such as split green fluorescent protein, or GFP), to make a full sensing protein device. When a small molecule binds in the pocket, the subunits reassemble, which leads to the signaling module sending a signal that the small molecule is present.

First step: Binding

The team chose a diverse spectrum of ligands (molecules that bind to protein receptors to send signals between cells), including cholic acid, a biomarker for liver disease; methotrexate, a cancer drug, which requires regular monitoring; thyroxine, a human hormone that indicates thyroid conditions; and a cyclic peptide.

The scientists constructed a machine learning algorithm based on AlphaFold2 (a protein structure predictor whose developers, John Jumper and Demis Hassabis, shared the Nobel Prize in Chemistry with Baker) and other machine learning protein design algorithms to generate thousands of proteins to bind the small molecules.

After computational design, the team tested the designed proteins in the laboratory and identified binders to particular ligands, following computational design and using machine learning methods to choose the best designs for experimental tests.

To confirm the accuracy of their design approach, the Baker team turned to the APS. They used the ultrabright X-ray beams to collect data on the atomic structure of the binding proteins. Using the Northeastern Collaborative Access Team (NE-CAT) beamlines at 24-ID at the APS, the team determined the structures of crystals formed from one of the designed proteins. 

“Prediction algorithms are excellent tools, but without verification of the structures, there’s no proof that the predictions match reality,” said Kay Perry of Cornell University, staff scientist at NE-CAT. ​“X-ray crystallography remains one of the best ways to make that confirmation, and the team was able to do so in this case.”

Second step: Signaling

The next challenge was turning the binding proteins into signaling proteins. The scientists took advantage of their modularity to create two different types of signaling events. 

The team built ligand-induced dimerization proteins from the binders. Linna An, the first author of this study, said the technology can be used in many health-related applications, such as regulating the release of drugs in cancer therapies.

In a different type of signaling event, the scientists fused the binding proteins to a newly designed nanopore, a protein creating a channel allowing ion flow. The fused unit was constructed in such a way that when a small molecule blocked the binding pocket, the whole nanopore was blocked, preventing the flow of ions and loss of current. Loss of current signaled the presence of the small molecule. 

Wide applications

Current commercially available tests for detecting three of the four target molecules used in this research — cholic acid, methotrexate and thyroxine — cannot distinguish individual molecules from variants or bound forms from free forms. Creating higher affinity and more specific binders would enable rapid at-home testing for liver disease, certain cancers and thyroid conditions. 

In applications outside of biomedicine, some of the members of Baker’s team are developing proteins that can sense microplastics and environmental toxins. 

But it doesn’t have to stop there. Imagination and creativity gave rise to the vision of engineering proteins that never existed before. Applying that same spirit of imagination to the wider world may yield sensing solutions waiting to be discovered. 

About the Advanced Photon Source

The U. S. Department of Energy Office of Science’s Advanced Photon Source (APS) at Argonne National Laboratory is one of the world’s most productive X-ray light source facilities. The APS provides high-brightness X-ray beams to a diverse community of researchers in materials science, chemistry, condensed matter physics, the life and environmental sciences, and applied research. These X-rays are ideally suited for explorations of materials and biological structures; elemental distribution; chemical, magnetic, electronic states; and a wide range of technologically important engineering systems from batteries to fuel injector sprays, all of which are the foundations of our nation’s economic, technological, and physical well-being. Each year, more than 5,000 researchers use the APS to produce over 2,000 publications detailing impactful discoveries, and solve more vital biological protein structures than users of any other X-ray light source research facility. APS scientists and engineers innovate technology that is at the heart of advancing accelerator and light-source operations. This includes the insertion devices that produce extreme-brightness X-rays prized by researchers, lenses that focus the X-rays down to a few nanometers, instrumentation that maximizes the way the X-rays interact with samples being studied, and software that gathers and manages the massive quantity of data resulting from discovery research at the APS.

This research used resources of the Advanced Photon Source, a U.S. DOE Office of Science User Facility operated for the DOE Office of Science by Argonne National Laboratory under Contract No. DE-AC02-06CH11357.

Argonne National Laboratory seeks solutions to pressing national problems in science and technology by conducting leading-edge basic and applied research in virtually every scientific discipline. Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science.

The U.S. Department of Energy’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of the most pressing challenges of our time. For more information, visit https://​ener​gy​.gov/​s​c​ience.