Systems Analysis of Arrestin Pathway Functions - Progress in Molecular Biology and Translational Science - page 425

pharmacotherapeutic effects are mediated by alterations in whole gene/
protein networks, as opposed to simple activation or inhibition of linear
signal transduction pathways. A common phrase often used to describe this
shift in molecular biology is that “pathways no longer exist, there are only
networks.” This view does not disregard the data collected from many
years of prior signal transduction research but suggests perhaps that the
delineation of discrete signaling pathways potentially represents an abstrac-
tion of the true, hypercomplex, signaling network, due to our previous
deficiencies in analytical technologies.
In the following sections, we discuss the present variety of efficient and
sensitive techniques which an investigator can use to assess genomic or pro-
teomic differences in distinct pharmacological scenarios, including fluores-
cent transcriptomic array analysis, genome-wide association screening and
massive parallel sequencing, antibody arrays, protein-binding microarrays,
quantitative mass spectrometry (MS), and MS-physical interactomics. These
era-changing mass analytical technologies, however, often cause experi-
menters considerable issues concerning the choice of the best analytical
mechanisms to allow the fullest appreciation of such a surplus of functional
data. The application of biologically relevant mathematical processes to
divine the eventual physiological meaning of these datasets will also be dis-
cussed. The analytical tools and processes described will be applicable to
both genomic and proteomic data and will hopefully facilitate a deeper
understanding of the creation and eventual pharmacological targeting of sig-
nal transduction networks associated with b -arrestin functions. The primary
goal of these bioinformatic analytical tools is the rational and biologically rel-
evant condensation of mass data lists into outputs that predict the functional
activities of the genes/proteins modulated between the control and test
datasets. The clustering of gene/protein factors into functional groups, sig-
naling pathways or even three-dimensional objects will help to categorize
idiosyncratic gene/protein sets for future diagnostic and therapeutic use.
Therefore, in the future, patient diagnosis, drug development, testing,
and design may all take place initially at the signaling network level rather
than at the single gene/protein measurement index level.

3.1. Transcriptomic analysis
With the demonstration that GPCR systems can routinely control transcrip-
tional pathways, the importance of measuring the genomic actions of recep-
tor

is evident. 71,84,87 Most GPCR systems have now been ligands