Synthesis and Study of Multifunctional Cyclodextrin-Deferasirox Hybrids.

Metal dyshomeostasis is central to a number of disorders that result from, inter alia, oxidative stress, protein misfolding, and cholesterol dyshomeostasis. In this respect, metal deficiencies are usually readily corrected by treatment with supplements, whereas metal overload can be overcome by the use of metal-selective chelation therapy. Deferasirox, 4-[(3Z,5E)-3,5-bis(6-oxo-1-cyclohexa-2,4-dienylidene)-1,2,4-triazolidin-1-yl]benzoic acid, Exjade, or ICL670, is used clinically to treat hemosiderosis (iron overload), which often results from multiple blood transfusions. Cyclodextrins are cyclic glucose units that are extensively used in the pharmaceutical industry as formulating agents as well as for encapsulating hydrophobic molecules such as in the treatment of Niemann-Pick type C or for hypervitaminosis. We conjugated deferasirox, via an amide coupling reaction, to both 6A -amino-6A -deoxy-ß-cyclodextrin and 3A -amino-3A -deoxy-2A (S),3A (S)-ß-cyclodextrin, at the upper and lower rim, respectively, creating hybrid molecules with dual properties, capable of both metal chelation and cholesterol encapsulation. Our findings emphasize the importance of the conjugation of ß-cyclodextrin with deferasirox to significantly improve the biological properties and to decrease the cytotoxicity of this drug.

Layered metal organosulfides: hydrothermal synthesis, structure and magnetic behaviour of the spin-canted magnet Co(1,2-(O2C)(S)C6H4).

Reaction of cobalt(II) salts with the thiosalicylate dianion under hydrothermal conditions yields green lamellar Co((O2C)(S)C6H4) which displays canted antiferromagnetism.

Evolutionary computational methods to predict oral bioavailability QSPRs.

This review discusses evolutionary and adaptive methods for predicting oral bioavailability (OB) from chemical structure. Genetic Programming (GP), a specific form of evolutionary computing, is compared with some other advanced computational methods for OB prediction. The results show that classifying drugs into 'high' and 'low' OB classes on the basis of their structure alone is solvable, and initial models are already producing output that would be useful for pharmaceutical research. The results also suggest that quantitative prediction of OB will be tractable. Critical aspects of the solution will involve the use of techniques that can: (i) handle problems with a very large number of variables (high dimensionality); (ii) cope with 'noisy' data; and (iii) implement binary choices to sub-classify molecules with behavior that are qualitatively different. Detailed quantitative predictions will emerge from more refined models that are hybrids derived from mechanistic models of the biology of oral absorption and the power of advanced computing techniques to predict the behavior of the components of those models in silico.