Description
Artificial intelligence tools have enabled the rapid prediction of drug binding events. We can now generate drug-bound protein structures with minimal input, leading to an explosion in the number of in silico drug-binding models. However, the empirical determination of how a drug may be to a protein is reliant on relatively low-throughput structural biology methods such as X-ray crystallography, NMR spectroscopy, and, more recently, cryo-electron microscopy.Here, we present a robotic workflow for structurally screening small-molecule drugs using a Waters cyclic IMS equipped with an electron capture dissociation (ECD) cell, allowing for HDX-MS/MS. This approach allows detection of drug binding at single–amino acid residue resolution, which we compare to other structural methods. Furthermore, we define spatial Kd values for both the overall protein and each amino acid—that is, the relative contribution of each residue to the protein’s affinity for the compound—and compare these results with gold-standard biophysical affinity analyses.
Overall, we introduce a new model for structurally screening drugs that enables rapid, semi-automated, high-throughput testing of predicted protein–drug interactions in solution, which also allows for quantification of binding affinity.
| Period | 9 Sept 2025 |
|---|---|
| Event title | British Mass Spectrometry Society Annual Meeting |
| Event type | Conference |
| Location | Edinburgh, United KingdomShow on map |
| Degree of Recognition | International |