From depression to neurodegeneration and heart failure: re-examining the potential of MAO inhibitors.

Initially introduced in the 1950s for treating depression, monoamine oxidase (MAO) inhibitors were gradually abandoned, mainly owing to their potential for drug-drug and drug-food interactions, the most widely known being with tyramine-containing food (the 'cheese' effect). Since then, more selective MAO-A or MAO-B inhibitors have been developed with substantially reduced risks, and have been approved for the treatment of depression and Parkinson's disease, respectively. Recent research suggests that some of these drugs also have neuroprotective properties, while preclinical evidence expands the spectrum of potential indications to heart failure, renal diseases and multiple sclerosis.

Literature mining, ontologies and information visualization for drug repurposing.

The immense growth of MEDLINE coupled with the realization that a vast amount of biomedical knowledge is recorded in free-text format, has led to the appearance of a large number of literature mining techniques aiming to extract biomedical terms and their inter-relations from the scientific literature. Ontologies have been extensively utilized in the biomedical domain either as controlled vocabularies or to provide the framework for mapping relations between concepts in biology and medicine. Literature-based approaches and ontologies have been used in the past for the purpose of hypothesis generation in connection with drug discovery.

Drug repurposing and adverse event prediction using high-throughput literature analysis.

Drug repurposing is the process of using existing drugs in indications other than the ones they were originally designed for. It is an area of significant recent activity due to the mounting costs of traditional drug development and scarcity of new chemical entities brought to the market by bio-pharmaceutical companies. By selecting drugs that already satisfy basic toxicity, ADME and related criteria, drug repurposing promises to deliver significant value at reduced cost and in dramatically shorter time frames than is normally the case for the drug development process.

Systems literature analysis.

Systems literature analysis (SLA) is the literature-driven version of systems biology. It treats collections of scientific literature as a system of millions of interconnections between research parameters, such as genes, diseases, tissues, cell events, model organisms, experiment types, and reagents. SLA aims to replace the traditional keyword-based querying of literature databases, which return sorted lists of papers, with a systems-based approach that returns integrated networks of relationships.