UCLA researchers in the Department of Biological Chemistry have developed a chemoproteomics-based method for improved and efficient protein and drug studies.
BACKGROUND: Quantitative proteomics is a method scientists use to find out how much of each protein is in a sample. It is used to compare protein levels in different situations. This information is useful for discovering how diseases work and finding new targets for medicines. This process involves tagging specific spots on proteins so scientists can capture and measure them using specific quantitative machines. However, making these tags has been difficult and expensive, and the current methods are slow and limited. Recently, new tags have been developed that allow for studying multiple samples at once, but remain costly and complex.
INNOVATION: The innovative part of this technology lies in the development of a new method called scLIP (silane-based Cleavable Linkers for Isotopically-labeled Proteomics), which makes it much easier and cheaper to create the special tags needed to study proteins. Traditional methods are complicated, expensive, and slow. Our new method simplifies the process, reduces costs, and improves accuracy. This allows scientists to study multiple protein samples at once more effectively, leading to better understanding and faster discoveries in protein research and drug development.
POTENTIAL APPLICATIONS:
- Helps identify important regions on proteins that can be targeted by new drugs.
- Allow scientists to understand how proteins behave differently in healthy versus diseased cells.
- Make it easier and cheaper to study many proteins at once, speeding up research and discoveries.
ADVANTAGES:
- The new method makes it easier and less expensive to create the special tags needed to study proteins, time and cost-effective.
- It allows scientists to study multiple protein samples at once more accurately and efficiently.
DEVELOPMENT-TO-DATE: Researchers have proved this workflow methodology.
KEYWORDS: proteomics, proteins, mass spectrometry, protein labeling