Integrating mass spectrometry into membrane protein drug discovery.
ABSTRACT Membrane proteins represent a valuable source of potential drug targets due to their intimate involvement in a wide variety of disease states, including diabetes, cancer and neurological disorders. Defining the proteome of these often rare amphipathic molecules can be accomplished by exploiting the highly accurate and sensitive nature of mass spectrometry (MS). Technical advances have enabled MS to become a valuable tool for detailed mechanistic investigations into membrane proteins of unknown and known structure. The transfer of MS-screening strategies that have already been successfully used to identify interactions between soluble proteins and potential ligands, should allow the identification of drug candidates for membrane proteins in the near future.
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ABSTRACT: Integral membrane proteins reside within the bilayer membranes that surround cells and organelles, playing critical roles in movement of molecules across them and the transduction of energy and signals. While their extreme amphipathicity presents technical challenges, biological mass spectrometry has been applied to all aspects of membrane protein chemistry and biology, including analysis of primary, secondary, tertiary and quaternary structure, as well as the dynamics that accompany functional cycles and catalysis.Analytical Chemistry 01/2013; 85(5). DOI:10.1021/ac303064a · 5.83 Impact Factor
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ABSTRACT: Like other forms of engineering, metabolic engineering requires knowledge of the components (the 'parts list') of the target system. Lack of such knowledge impairs both rational engineering design and diagnosis of the reasons for failures; it also poses problems for the related field of metabolic reconstruction, which uses a cell's parts list to recreate its metabolic activities in silico. Despite spectacular progress in genome sequencing, the parts lists for most organisms that we seek to manipulate remain highly incomplete, due to the dual problem of 'unknown' proteins and 'orphan' enzymes. The former are all the proteins deduced from genome sequence that have no known function, and the latter are all the enzymes described in the literature (and often catalogued in the EC database) for which no corresponding gene has been reported. Unknown proteins constitute up to about half of the proteins in prokaryotic genomes, and much more than this in higher plants and animals. Orphan enzymes make up more than a third of the EC database. Attacking the 'missing parts list' problem is accordingly one of the great challenges for post-genomic biology, and a tremendous opportunity to discover new facets of life's machinery. Success will require a co-ordinated community-wide attack, sustained over years. In this attack, comparative genomics is probably the single most effective strategy, for it can reliably predict functions for unknown proteins and genes for orphan enzymes. Furthermore, it is cost-efficient and increasingly straightforward to deploy owing to a proliferation of databases and associated tools.Biochemical Journal 01/2010; 425(1):1-11. DOI:10.1042/BJ20091328 · 4.78 Impact Factor
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ABSTRACT: Cellular membranes are composed of proteins and glyco- and phospholipids and play an indispensible role in maintaining cellular integrity and homeostasis, by physically restricting biochemical processes within cells and providing protection. Membrane proteins perform many essential functions, which include operating as transporters, adhesion-anchors, receptors, and enzymes. Recent advancements in proteomic mass spectrometry have resulted in substantial progress towards the determination of the plasma membrane (PM) proteome, resolution of membrane protein topology, establishment of numerous receptor protein complexes, identification of ligand-receptor pairs, and the elucidation of signaling networks originating at the PM. Here, we discuss the recent accelerated success of discovery-based proteomic pipelines for the establishment of a complete membrane proteome.Trends in Biochemical Sciences 05/2011; 36(7):388-96. DOI:10.1016/j.tibs.2011.04.005 · 13.52 Impact Factor