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Mga2p90 is an endoplasmic reticulum (ER)-localized transcription factor that is released from the ER membrane by a unique ubiquitin (Ub)-dependent mechanism. Mga2p90 mobilization requires polyubiquitination of its associating membrane-bound Mga2p120 anchor and subsequent Mga2p120-Mga2p90 complex disassembly that is mediated by ATPase Cdc48p and its heteromeric Ub-binding adaptor Npl4p-Ufd1p. Although previous studies have identified the Ub ligase (i.e., Rsp5p) and ligase-binding site on Mga2p120 that play a role in this process, the amino acids of Mga2p120 that are targets of ubiquitination and promote Mga2p90 mobilization are unknown. We have identified, using mass spectrometry analysis of in vitro ubiquitinated Mga2p120-Mga2p90 complex, that lysine residues 983 and 985 contained within the carboxy-terminal domain of Mga2p120 are Rsp5p-directed Ub-conjugation sites. Mutation of these residues as well as proximally located lysine 980 results in suppression of Mga2p120 ubiquitination in vitro and in vivo, inefficient liberation of Mga2p90 by Cdc48p(Npl4p/Ufd1p)in vitro, and ER retention of Mga2p in cells. Moreover, mga2Delta/spt23ts harboring Rsp5p binding and conjugation mga2 mutants express low OLE1 (an Mga2p90 target gene) transcripts and display reduced growth. We conclude that residues 980, 983, and 985 are targets of Rsp5p-induced polyubiquitination and mediate Cdc48p(Npl4p/Ufd1p)-dependent Mga2p90-Mga2p120 separation and Mga2p90 mobilization.

Many candidate biomarkers emerging from genomics and proteomics research have the potential to serve as predictive indexes for guiding the development of safer and more efficacious drugs. Research and development of biomarker discovery, selection, and clinical qualification, however, is still a relatively new field for the pharmaceutical industry. Advances in technology provide a plethora of analytical tools to discover and analyze mechanism-and-disease-specific biomarkers for drug development. In the discovery phase, differential proteomic analysis using mass spectrometry enables the identification of candidate biomarkers that are associated with a specific mechanism relevant to disease progression and affected by drug treatment. Reliable bioanalytical methods are then developed and implemented to select promising biomarkers for further studies in animals and humans. Quantitative analytical methods capable of generating reliable data constitute a solid basis for statistical assessment of the predictive utility of biomarkers. Biomarker method validation is diverse and for purposes that are very different from those of drug bioanalysis or diagnostic use. Besides being flexible, it should sufficiently demonstrate the method's ability to meet the study intent and the attendant regulatory requirements. Several papers have been published outlining specific requirements for successful biomarker method development and validation using a "Fit-for-Purpose" approach. Many of the challenges faced during biomarker discovery as well as during technology and process translation are discussed in this chapter, including preanalytical planning, assay development, and preclinical and clinical validation. Specific references to protein biomarkers for cancer drug development are also discussed.

Mass spectrometry is currently at the forefront of technologies for mapping protein-protein interactions, as it is a highly sensitive technique that enables the rapid identification of proteins from a variety of biological samples. When used in combination with affinity purification and/or chemical cross-linking, whole or targeted protein interaction networks can be elucidated. Several methods have recently been introduced that display increased specificity and a reduced occurrence of false-positives. In the future, information gained from human protein interaction studies could lead to the discovery of novel pathway associations and therapeutic targets.

The ability to map protein-protein interactions has grown tremendously over the last few years, making it possible to envision the mapping of whole or targeted protein interaction networks and to elucidate their temporal dynamics. The use of mass spectrometry for the study of protein complexes has proven to be an invaluable tool due to its ability to unambiguously identify proteins from a variety of biological samples. Furthermore, when affinity purification is combined with mass spectrometry analysis, the identification of multimeric protein complexes is greatly facilitated. Here, we review recent developments for the analysis of protein interaction networks by mass spectrometry and discuss the integration of different bioinformatic tools for predicting, validating, and managing interaction datasets.