Proteomics for drug target discovery

Proteomics, genomics and metabonomics have, during the last decade, provided researchers with huge amounts of data. The choice of transformation of such data into useful information is dependent on the study aims and objectives. In the present study, projection methods (i.e., Principal Components Analysis [PCA] and Partial List Squares-Discriminant Analysis [PLS-DA]) were used to overview results from two-dimensional (2D) protein gel separations. The aim was to unravel possibilities for target discovery options via an in-depth understanding of quantified alterations in tissue or body fluid sample protein levels related to diseases. Two examples will be included comprising (1) data measured in cerebrospinal fluid (CSF) samples from diagnosed dementia patients and healthy volunteers, and (2) data from liver samples of drug-treated animals (i.e., Rosigltazone and Wy14643). The examples reveal clear clustering, using the protein levels as input, coinciding with the clinical diagnoses in example 1 and by treatment group in example 2.