NFFinder: an online bioinformatics tool for searching similar transcriptomics experiments in the context of drug repositioning.

Drug repositioning, using known drugs for treating conditions different from those the drug was originally designed to treat, is an important drug discovery tool that allows for a faster and cheaper development process by using drugs that are already approved or in an advanced trial stage for another purpose. This is especially relevant for orphan diseases because they affect too few people to make drug research de novo economically viable. In this paper we present NFFinder, a bioinformatics tool for identifying potential useful drugs in the context of orphan diseases. NFFinder uses transcriptomic data to find relationships between drugs, diseases and a phenotype of interest, as well as identifying experts having published on that domain. The application shows in a dashboard a series of graphics and tables designed to help researchers formulate repositioning hypotheses and identify potential biological relationships between drugs and diseases. NFFinder is freely available at http://nffinder.cnb.csic.es.

siRNA screen identifies QPCT as a druggable target for Huntington's disease.

Huntington's disease (HD) is a currently incurable neurodegenerative condition caused by an abnormally expanded polyglutamine tract in huntingtin (HTT). We identified new modifiers of mutant HTT toxicity by performing a large-scale 'druggable genome' siRNA screen in human cultured cells, followed by hit validation in Drosophila. We focused on glutaminyl cyclase (QPCT), which had one of the strongest effects on mutant HTT-induced toxicity and aggregation in the cell-based siRNA screen and also rescued these phenotypes in Drosophila. We found that QPCT inhibition induced the levels of the molecular chaperone αB-crystallin and reduced the aggregation of diverse proteins. We generated new QPCT inhibitors using in silico methods followed by in vitro screening, which rescued the HD-related phenotypes in cell, Drosophila and zebrafish HD models. Our data reveal a new HD druggable target affecting mutant HTT aggregation and provide proof of principle for a discovery pipeline from druggable genome screen to drug development.

Functional and systems biology approaches to Huntington's disease.

Huntington's disease (HD) is a hereditary, progressively degenerative and fatal brain disorder classified as a rare, or 'orphan', disease. HD is caused by the extension of trinucleotide repeats encoding a stretch of glutamine residues at the amino-terminal end of the large huntingtin (HTT) protein. Since the discovery of the mutated HTT gene in 1993, the mechanisms by which the mutant HTT protein induces neurodegeneration remain poorly understood and no disease-modifying therapy is currently available. Several functional approaches combining different experimental models and experimental technologies have been used to shed some light on the mechanisms underlying this disease. This review presents these functional approaches, highlights their potential and limitations.

Multiplexed homogeneous proximity ligation assays for high-throughput protein biomarker research in serological material.

A high throughput protein biomarker discovery tool has been developed based on multiplexed proximity ligation assays in a homogeneous format in the sense of no washing steps. The platform consists of four 24-plex panels profiling 74 putative biomarkers with sub-pm sensitivity each consuming only 1 µl of human plasma sample. The system uses either matched monoclonal antibody pairs or the more readily available single batches of affinity purified polyclonal antibodies to generate the target specific reagents by covalently linking with unique nucleic acid sequences. These paired sequences are united by DNA ligation upon simultaneous target binding forming a PCR amplicon. Multiplex proximity ligation assays thereby converts multiple target analytes into real-time PCR amplicons that are individually quantified using microfluidic high capacity qPCR in nano liter volumes. The assay shows excellent specificity, even in multiplex, by its dual recognition feature, its proximity requirement, and most importantly by using unique sequence specific reporter fragments on both antibody-based probes. To illustrate the potential of this protein detection technology, a pilot biomarker research project was performed using biobanked plasma samples for the detection of colorectal cancer using a multivariate signature.

Drug discovery and development for Huntington's disease - an orphan indication with high medical need.

Huntington's disease (HD) is a rare neurodegenerative disorder that progressively destroys the mental capacity and motor control of patients. This loss of motor control results in abnormal body movements (chorea) - the hallmark of HD. Given that no disease-modifying therapy for HD exists and that available symptomatic treatments are not highly efficacious, the medical need for this 'orphan' disease remains high. The number of compounds that are undergoing discovery and development for the treatment of HD has increased significantly in recent years, spurred by legislative incentives for orphan drug development and by support from non-profit foundations. Thus, hope exists for patients with HD that efficacious medicines will become available.

In vitro and in silico processes to identify differentially expressed proteins.

We present an integrated proteomics platform designed for performing differential analyses. Since reproducible results are essential for comparative studies, we explain how we improved reproducibility at every step of our laboratory processes, e.g. by taking advantage of the powerful laboratory information management system we developed. The differential capacity of our platform is validated by detecting known markers in a real sample and by a spiking experiment. We introduce an innovative two-dimensional (2-D) plot for displaying identification results combined with chromatographic data. This 2-D plot is very convenient for detecting differential proteins. We also adapt standard multivariate statistical techniques to show that peptide identification scores can be used for reliable and sensitive differential studies. The interest of the protein separation approach we generally apply is justified by numerous statistics, complemented by a comparison with a simple shotgun analysis performed on a small volume sample. By introducing an automatic integration step after mass spectrometry data identification, we are able to search numerous databases systematically, including the human genome and expressed sequence tags. Finally, we explain how rigorous data processing can be combined with the work of human experts to set high quality standards, and hence obtain reliable (false positive < 0.35%) and nonredundant protein identifications.