1. Introduction the Current State of Proteomic Technology
2. Impact of Automation on Proteomics
Presents several key components of automation in proteomics technology, and the improvements required to obtain not simply more information, but high quality information. This is critical for a complex system such as the proteome, where inexact results could lead researchers down many wrong paths in discovery.
2.1 Proteomics Relies on Automation
2.6 Case Example in the Identification of Protein-Protein Interactions
3. Convergent Solutions to Binding at a Protein-Protein Interface
The rapidly growing number of protein structures is permitting an examination to reveal the consensus characteristics of protein-protein interactions. These characteristics are described here. Because so many disease pathways involve interactions between proteins, the implications of deciphering the rules of interaction on the development of peptide and small molecule therapeutics can be significant.
4. Finding Inhibitors of Protein-Protein Interactions
Functional proteomics is yielding large databases of interacting proteins and extensive pathway maps of these interactions are being deciphered by novel high throughput technologies. However, traditional methods of screening have not been very successful in identifying protein-protein interaction inhibitors. Described in this chapter are technologies used to rapidly screen for compounds that inhibit protein-protein interactions, including allosteric inhibitors.
5. Protein Expression Profiling on Microarrays by Rolling Circle Amplification
Rolling circle amplification (RCA) is emerging as the signal amplification method of choice for DNA and RNA microarrays. A modification of RCA enables protein expression profiling on microarrays.
5.1 What is Rolling Circle Amplification?
6. Protein Chips and Phage Display
Discusses the use of phage display technology to bind the proteome onto a chip. By coupling phage displays capability of generating diverse libraries of human antibodies in vitro and protein chip microarrays, the two technologies can potentially fill a large gap in current approaches to proteomics. Applications enable recognition of protein modifications and differential expression of hundreds of proteins at once.
6.2 Exploiting the Combination of Phage Display and Microarray Technologies
6.5 Applications of Phage Selected Antibodies
6.6 Phage Display and Microarrays -- Monitoring Functionally Relevant Proteins
6.8 Dyax Business Strategy
7. Application of Novel Protein Chip Technology to Human Disease
Protein chips are an emerging technology useful for the discovery and measurement of protein biomarkers for therapeutic and diagnostic applications. The hope is that they will replicate some of the remarkable capabilities that DNA microarrays brought to the field of genomics. Examples of SELDI protein chip technology are presented along with their use in the discovery, identification and characterization of protein biomarkers for prostate cancer and other diseases.
7.1 Fishing for Therapeutic and Diagnostic Targets
7.4 Application Disease Target and Marker Discovery
7.5 Application Protein Identification and Purification
7.6 Cluster Analysis to Identify Complex Patterns in Multiple Mass Spectra
7.8 Application Assay Development
8. Identification of Kinase Targets from Proteomic Libraries using ProFusion Technology
A discussion on the method of covalently linking proteins to their mRNA, creating a link between protein and genotype. The protein moiety can be selected for under the most robust conditions and its genetic material amplified by PCR.. Profusion libraries can be constructed from the mRNA of any organism or tissue of interest, and screened for novel protein-protein, enzyme-substrate and protein-drug interactions.
8.1 mRNA/Protein Fusion
9. Determination of Protein Functionality Using Live Cell Assays
Obtain functional information on a wide variety of cellular effects, including apoptosis, proliferation, differentiation, migration and protein secretion. Enables a better understanding of protein functionality in normal and diseased states.
10. Proteomics Panel Discussion