I'm Walking into Spiderwebs: Making Sense of Protein-Protein Interaction Data.
Chase L S SkawinskiPriya S ShahPublished in: Journal of proteome research (2024)
Protein-protein interactions (PPIs) are at the heart of the molecular landscape permeating life. Proteomics studies can explore this protein interaction landscape using mass spectrometry (MS). Thanks to their high sensitivity, mass spectrometers can easily identify thousands of proteins within a single sample, but that same sensitivity generates tangled spiderwebs of data that hide biologically relevant findings. So, what does a researcher do when she finds herself walking into spiderwebs? In a field focused on discovery, MS data require rigor in their analysis, experimental validation, or a combination of both. In this Review, we provide a brief primer on MS-based experimental methods to identify PPIs. We discuss approaches to analyze the resulting data and remove the proteomic background. We consider the advantages between comprehensive and targeted studies. We also discuss how scoring might be improved through AI-based protein structure information. Women have been essential to the development of proteomics, so we will specifically highlight work by women that has made this field thrive in recent years.
Keyphrases
- mass spectrometry
- protein protein
- electronic health record
- small molecule
- liquid chromatography
- big data
- ms ms
- multiple sclerosis
- polycystic ovary syndrome
- gas chromatography
- high resolution
- high performance liquid chromatography
- capillary electrophoresis
- heart failure
- healthcare
- data analysis
- high throughput
- machine learning
- type diabetes
- single cell
- adipose tissue
- skeletal muscle
- label free
- binding protein
- drug delivery
- pregnant women
- metabolic syndrome
- health information
- breast cancer risk