proteomics

Proteomics is the large-scale study of the structure, function, and interactions of proteins in a given organism, tissue, or cell. It seeks to identify and quantify the full complement of proteins (the proteome) and to characterize their properties, including post-translational modifications and interactions. Proteins are the primary effectors of cellular processes, and their abundance and modification state determine phenotypes, so proteomics complements genomics and transcriptomics by directly measuring functional molecules.

Historically developed alongside advances in mass spectrometry and protein separation, modern proteomics relies primarily on mass spectrometry-based approaches. Typical workflows involve protein extraction and digestion (often with trypsin), separation by liquid chromatography, and tandem mass spectrometry to sequence peptides and infer proteins. Quantitative strategies include label-free methods and labeling approaches such as SILAC, iTRAQ, and TMT. Data analysis uses specialized software and protein databases (e.g., UniProt) to identify proteins and assess post-translational modifications, interactions, and abundances. High-resolution instruments such as Orbitraps and Q-TOFs enable precise mass measurements and deep coverage.

Applications of proteomics include biomarker discovery for disease, understanding signaling networks and protein interactions, mapping protein complexes, and aiding drug discovery and personalized medicine. Challenges include sample complexity, wide dynamic range of protein abundances, and the analysis of dynamic post-translational modifications. Ongoing developments aim to improve coverage, quantification accuracy, and integration with other omics data.