3-hydroxy-L-kynurenamine is an immunomodulatory biogenic amine.

Tryptophan catabolism is a major metabolic pathway utilized by several professional and non-professional antigen presenting cells to maintain immunological tolerance. Here we report that 3-hydroxy-L-kynurenamine (3-HKA) is a biogenic amine produced via an alternative pathway of tryptophan metabolism. In vitro, 3-HKA has an anti-inflammatory profile by inhibiting the IFN-γ mediated STAT1/NF-κΒ pathway in both mouse and human dendritic cells (DCs) with a consequent decrease in the release of pro-inflammatory chemokines and cytokines, most notably TNF, IL-6, and IL12p70. 3-HKA has protective effects in an experimental mouse model of psoriasis by decreasing skin thickness, erythema, scaling and fissuring, reducing TNF, IL-1ß, IFN-γ, and IL-17 production, and inhibiting generation of effector CD8+ T cells. Similarly, in a mouse model of nephrotoxic nephritis, besides reducing inflammatory cytokines, 3-HKA improves proteinuria and serum urea nitrogen, overall ameliorating immune-mediated glomerulonephritis and renal dysfunction. Overall, we propose that this biogenic amine is a crucial component of tryptophan-mediated immune tolerance.

In silico pharmacology for a multidisciplinary drug discovery process.

The process of bringing new and innovative drugs, from conception and synthesis through to approval on the market can take the pharmaceutical industry 8-15 years and cost approximately $1.8 billion. Two key technologies are improving the hit-to-drug timeline: high-throughput screening (HTS) and rational drug design. In the latter case, starting from some known ligand-based or target-based information, a lead structure will be rationally designed to be tested in vitro or in vivo. Computational methods are part of many drug discovery programs, including the assessment of ADME (absorption-distribution-metabolism-excretion) and toxicity (ADMET) properties of compounds at the early stages of discovery/development with impressive results. The aim of this paper is to review, in a simple way, some of the most popular strategies used by modelers and some successful applications on computational chemistry to raise awareness of its importance and potential for an actual multidisciplinary drug discovery process.

Synthesis and biological evaluation of novel 1-deoxy-1-[6-[((hetero)arylcarbonyl)hydrazino]- 9H-purin-9-yl]-N-ethyl-beta-D-ribofuranuronamide derivatives as useful templates for the development of A2B adenosine receptor agonists.

The lack of molecules endowed with selective and potent agonistic activity toward the hA2B adenosine receptors has limited the studies on this pharmacological target and consequently the evaluation of its therapeutic potential. We report the design and the synthesis of the first potent (EC50 in the nanomolar range) and selective hA2B adenosine receptor agonists consisting of 1-deoxy-1-[6-[((hetero)arylcarbonyl)hydrazino]-9H-purin-9-yl]-N-ethyl-beta-D-ribofuranuronamide derivatives. The concurrent effect of 6-substitution of the purine nucleus with a ((hetero)arylcarbonyl)hydrazino function and a 2-chloro substitution has been investigated in such NECA derivatives.