High-throughput native mass spectrometry as experimental validation for in silico drug design
EMSL Project ID
60268
Abstract
Enzyme functions can often be modulated via interaction with small molecules. For example, inhibitors are actively sought in the pharmaceutical industry to block protein targets and treat diseases. Similar concept is applicable for treating other organisms (e.g., bioenergy plants and microbes) with designed compounds for desired outcomes. The challenge of finding a small molecule that binds to a protein with high affinity and high specificity is quite well-known. Existing high throughput assays are limited to proteins with at least some prior knowledge of function and are costly and prone to high failure rates. Thus, in silico design holds significant potential for high-throughput, low-cost drug screening without the need for prior knowledge of protein function. However, given the current state of the computational chemistry, the effectiveness of in silico drug design lags in affinity and specificity behind experimental approaches.Native mass spectrometry (native MS) is an emerging proteomics technique to study protein complexes, including protein-drug binding. Compared to the more established methods such as immunoprecipitation, affinity probe, or crosslinking, native MS is unique in that it measures binding directly without requiring labels/probes. Data collection for native MS is also fast, on the order of minutes for confirming ligand binding. In addition, native MS can readily resolve apo/holo proteins and protein oligomers. Since native MS operates under non-denaturing conditions, protein dynamics and enzymatic reactions can be monitored by time-resolved measurements, allowing us to interrogate protein functions in great detail. Such molecular information is extremely useful as feedback for iterative computational compound design and further improving success rate. However, most native MS studies have been performed manually. Automated systems available commercially are not very flexible for complex experimental designs and significant failure rates. To address these challenges, we aim to develop an automated, scalable native MS platform that is compatible with various experimental designs. In parallel, we will develop a computational workflow that is compatible with native MS data. The integrated platform will provide the critical foundation for advanced high-throughput functional proteomics analysis of protein complexes and protein-ligand interactions.
Project Details
Start Date
2021-12-16
End Date
N/A
Status
Active
Released Data Link
Team
Principal Investigator
Team Members