Has the yo-yo stopped? An assessment of human protein-coding gene number

Serine/threonine/tyrosine phosphorylation of the LHX3 LIM-homeodomain transcription factor

LHX3 is a LIM homeodomain transcription factor with essential roles in pituitary and motor neuron development in mammals. Patients with mutations in the LHX3 gene have combined pituitary hormone deficiency and other symptoms. In this study, we show that the LHX3 protein can be modified post-translationally by phosphorylation. LHX3 can serve as a substrate for protein kinase C and casein kinase II. Overexpression of these kinases reduces the transcriptional capacity of LHX3 to activate target genes. Following exposure of LHX3 to cellular kinases, mass spectrometry was used to map the phosphorylation of five amino acid residues within the human LHX3a isoform. Two phosphorylated residues (threonine 63 and serine 71) lie within the first LIM domain of the protein. Three other modified amino acids (tyrosine 227, serine 234, and serine 238) are located in the carboxyl terminus. Targeted replacement of these amino acids with non-modifiable residues significantly reduced the ability of LHX3 to activate both synthetic and pituitary hormone reporter genes. However, the amino acid replacements did not significantly affect the capability of LHX3 to interact with the NLI, PIT1, and MRG1 partner proteins, or its ability to bind to a high affinity DNA site. In conclusion, we have identified unique amino acids within LHX3 that are important for its transcriptional activity and are phosphorylated.

A newly discovered human alpha-globin gene

A previously undefined transcript with significant homology to the pseudo-alpha2 region of the alpha-globin locus on human chromosome 16 was detected as part of an effort to better define the transcriptional profiles of human reticulocytes. Cloning and sequencing of that transcript (GenBank AY698022; named mu-globin) revealed an insert with a 423-nucleotide open reading frame. BLASTP and ClustalW and phylogenetic analyses of the predicted protein demonstrated a high level of homology with the avian alpha-D globin. In addition, the heme- and globin-binding amino acids of mu-globin and avian alpha-D globin are largely conserved. Using quantitative real-time polymerase chain reaction (PCR), mu-globin was detected at a level of approximately 0.1% that measured for alpha-globin in erythroid tissues. Erythroid-specific expression was detected by Northern blot analysis, and maximal expression during the erythroblast terminal differentiation was also detected. Despite this highly regulated pattern of mu-globin gene transcription, mu-globin protein was not detected by mass spectrometry. These results suggest the human genome encodes a previously unrecognized globin member of the avian alpha-D family that is transcribed in a highly regulated pattern in erythroid cells.

Target identification and validation in drug discovery: the role of proteomics

Proteomics, the study of cellular protein expression, is an evolving technology platform that has the potential to identify novel proteins involved in key biological processes in the cell that may serve as potential drug targets. While proteomics has considerable theoretical promise, individual cells/tissues have the potential to generate many millions of proteins while the current analytical technologies that involve the use of time-consuming two dimensional gel electrophoresis (2DIGE) and various mass spectrometry (MS) techniques are unable to handle complex biological samples without multiple high-resolution purification steps to reduce their complexity. This can significantly limit the speed of data generation and replication and requires the use of bioinformatic algorithms to reconstitute the parent proteome, a process that does not always result in a reproducible outcome. In addition, membrane bound proteins, e.g., receptors and ion channels, that are the targets of many existing drugs, are not amenable to study due, in part, to limitations in current proteomic techniques and also to these being present in low abundance and thus disproportionally represented in proteome profiles. Subproteomes with reduced complexity have been used to generate data related to specific, hypothesis-driven questions regarding target identification, protein-interaction networks and signaling pathways. However progress to date, with the exception of diagnostic proteomics in the field of cancer, has been exceedingly slow with an inability to put such studies in the context of a larger proteome, limiting the value of the information. Additionally the pathway for target validation (which can be more accurately described at the preclinical level as target confidence building) remains unclear. It is important that the ability to measure and interrogate proteomes matches expectations, avoiding a repetition of the disappointment and subsequent skepticism that accompanied what proved to be unrealistic expectations for the rapid contribution of data based on the genome maps, to biomedical research.

How to Bring the “Unseen” Proteome to the Limelight via Electrophoretic Pre-Fractionation Techniques

The present review reports a panoply of electrophoretic methods as pre-fractionation tools in proteomic investigations in preparation for mass spectrometry or two-dimensional electrophoresis map analysis. Such electrophoretic pre-fractionation protocols include all those electrokinetic methodologies which are performed in free solution, most of them relying on isoelectric focusing steps (although some approaches based on gels and granulated media are also discussed). Devices associated with electrophoretic separations are multi-chamber apparatuses, such as the multi-compartment electrolyzers equipped with either isoelectric membranes or with isoelectric beads, Off-Gel electrophoresis in a multi-cup device and the Rotofor, an instrument also based on a multi-chamber system but exploiting the conventional technique of carrier-ampholyte-focusing. Other free-flow systems, as well as miniaturized chambers, are also described.

Bioinformatics in drug development and assessment

Bioinformatics is playing an increasingly important role in nearly all aspects of drug discovery, drug assessment, and drug development. This growing importance lies not only in the role that bioinformatics plays in handling large volumes of data, but also in the utility of bioinformatics tools to predict, analyze, or help interpret clinical and preclinical findings. This review focuses on describing and evaluating some of the newer or more important bioinformatics resources (i.e., databases and software) that are of growing importance to understanding or predicting drug metabolism, especially with respect to the absorption, distribution, metabolism, excretion, (ADME), and toxicity (T) of both existing drugs and potential drug leads. Detailed descriptions and critical assessments of a number of potentially useful bioinformatics/cheminformatics databases and predictive ADMET software tools are provided. Additionally, several pharmaceutically important applications of both the databases and software are highlighted. Given the rapid growth in this area and the rapid changes that are taking place, a special emphasis is placed on freely available or Web-accessible resources.