TARGETS最新文献

Despite current drug therapies, including those that target enzymes, channels and known G-protein-coupled receptors (GPCRs), cardiovascular disease remains the major cause of ill health, which suggests that other transmitter systems might be involved in this disease. In humans, ∼175 genes have been predicted to encode ‘orphan’ GPCRs, where the endogenous ligand is not yet known. As a result of intensive screening using ‘reverse pharmacology’, an increasing number of orphan receptors are being paired with their cognate ligands, many of which are peptides. The existence of some of these peptides such as urotensin-II and relaxin had been known for some time but others, including ghrelin and apelin, represent novel sequences. The pharmacological characterization of these emerging peptide–receptor systems is a tantalising area of cardiovascular research, with the prospect of identifying new therapeutic targets.

The tremendous progress of the genome sequencing centers, combined with computational advances in algorithms for genome assembly and gene model prediction, provide the research community with valuable new resources in the form of complete, or nearly complete, genome sequences for a wide variety of organisms that serve as platforms to investigate biological systems. The challenge facing the bioinformatics community is how to integrate the rapidly emerging genomic data with experimental data, such as gene expression, protein interactions, cell processes and systems characteristics under select perturbations. Data integration is key to understanding at all levels because the process of integration brings together disparate types of data in formats that support effective data mining, pattern detection and hypothesis generation. Databases for model organisms are valuable sources of integrated data from the level of the genome to that of the phenotype. Databases for model organisms promote data integration through the development and implementation of nomenclature standards, controlled vocabularies and ontologies, that allow data different organisms to be compared and contrasted.

We present the development of Proteo-Mode, an instrument for automated, high-throughput preparation of phosphoproteins for proteomics analysis of complex cellular signalling networks involving multiple, time-dependent protein phosphorylation events. Proteo-Mode automates all steps in the network analysis of phosphoproteins by proteomics method. This enables the integrated response of complex cellular signalling networks to be analyzed in normal and abnormal (disease) states and provides new perspectives in targeting and evaluation of the effects of therapeutic compounds on such networks.

New discoveries in life sciences depend on accurate analysis of biomolecules, which in turn depends on the extraction of high-quality molecules in high quantities from the tissues of plants, animals or microorganisms. The extraction process for hard-to-lyse cells and tissues has been a bottleneck in the path to discovery for many years. This review describes extraction methods currently in use, and compares them to a newly developed, automated process involving patented pressure cycling technology (PCT). The PCT sample preparation system (SPS) uses an instrument capable of rapid, temperature-controlled pressure cycling between ambient and high pressures, and single-use sample tubes containing a ram and a lysis disk. The quality and quantity of nucleic acid and protein prepared by the PCT SPS method are comparable to the older methods, whereas ease and safety of processing, reproducibility, speed and control are enhanced.