Proteomics - An Introduction

The term “proteome” was coined in 1996 and refers to the total protein complement of a cell, tissue or organism.

Specifically, analysis of a proteome allows the simultaneous measurement and quantification of the expression levels of all proteins in a cell or tissue type at any one time.

The study of the proteome, called proteomics, now evokes not only all the proteins in any given cell, but also the set of all protein isoforms and modifications, the interactions between them, the structural description of proteins and their higher-order complexes, and for that matter almost everything 'post-genomic'. When used in an overall sense, proteomics means protein biochemistry on an unprecedented, high-throughput scale. The hope, now being realized, is that this high-throughput biochemistry will contribute at a direct level to a full description of cellular function.

Proteomics would not be possible without the previous achievements of genomics, which provided the 'blueprint' of possible gene products that are the focal point of proteomics studies.

By studying global patterns of protein content and activity and how these change during development or in response to disease, proteomics research is poised to boost our understanding of systems-level cellular behavior. Clinical research also hopes to benefit from proteomics by both the identification of new drug targets and the development of new diagnostic markers – “biomarkers”.

In drug discovery, biomarkers can help elicit disease targets and pathways, and validate mechanisms of drug action. One can identify or monitor off-target effects very early in the discovery and development process, thereby avoiding setbacks later. It is reported that for every drug candidate that enters human clinical trials, many others will have failed at various stages of discovery.

Proteome analysis will play an increasingly critical role in drug discovery and evaluation, particularly because proteomics can measure many pieces of vital information that genomics cannot predict.

These are:
• if and when gene products (e.g., proteins), are expressed;

• the abundance of these gene products and their modification products;

• the regulation of expression of these proteins;

• the extent of post-translational modifications;

• the effects of mutations;

• the function of open reading frames (ORF's), including smaller ORF’s of <300 nucleotides;

• the phenotype of a cell experiencing multigenic phenomena resulting from modulation of protein expression, due to drug administration, cell-cycle, ontogeny, aging, stress and disease.

Proteome analysis will be particularly relevant for those disease states where multiple genes are involved, notably in the development of cardiovascular dysfunction, cancer, diabetes and other complex disease states.

The drug development process - from initial identification of a disease-associated protein as a target of a drug candidate to the market launch of that candidate as a drug-can take up to ten years and cost upto 800 million dollars. Biomarkers might help reduce development time, costs and increase drug approval chances.