Statistical analysis of crystallization database links protein physico-chemical features with crystallization mechanisms.

X-ray crystallography is the predominant method for obtaining atomic-scale information about biological macromolecules. Despite the success of the technique, obtaining well diffracting crystals still critically limits going from protein to structure. In practice, the crystallization process proceeds through knowledge-informed empiricism. Better physico-chemical understanding remains elusive because of the large number of variables involved, hence little guidance is available to systematically identify solution conditions that promote crystallization. To help determine relationships between macromolecular properties and their crystallization propensity, we have trained statistical models on samples for 182 proteins supplied by the Northeast Structural Genomics consortium. Gaussian processes, which capture trends beyond the reach of linear statistical models, distinguish between two main physico-chemical mechanisms driving crystallization. One is characterized by low levels of side chain entropy and has been extensively reported in the literature. The other identifies specific electrostatic interactions not previously described in the crystallization context. Because evidence for two distinct mechanisms can be gleaned both from crystal contacts and from solution conditions leading to successful crystallization, the model offers future avenues for optimizing crystallization screens based on partial structural information. The availability of crystallization data coupled with structural outcomes analyzed through state-of-the-art statistical models may thus guide macromolecular crystallization toward a more rational basis.

Superoxide dismutase mimics: chemistry, pharmacology, and therapeutic potential.

Oxidative stress has become widely viewed as an underlying condition in a number of diseases, such as ischemia-reperfusion disorders, central nervous system disorders, cardiovascular conditions, cancer, and diabetes. Thus, natural and synthetic antioxidants have been actively sought. Superoxide dismutase is a first line of defense against oxidative stress under physiological and pathological conditions. Therefore, the development of therapeutics aimed at mimicking superoxide dismutase was a natural maneuver. Metalloporphyrins, as well as Mn cyclic polyamines, Mn salen derivatives and nitroxides were all originally developed as SOD mimics. The same thermodynamic and electrostatic properties that make them potent SOD mimics may allow them to reduce other reactive species such as peroxynitrite, peroxynitrite-derived CO(3)(*-), peroxyl radical, and less efficiently H(2)O(2). By doing so SOD mimics can decrease both primary and secondary oxidative events, the latter arising from the inhibition of cellular transcriptional activity. To better judge the therapeutic potential and the advantage of one over the other type of compound, comparative studies of different classes of drugs in the same cellular and/or animal models are needed. We here provide a comprehensive overview of the chemical properties and some in vivo effects observed with various classes of compounds with a special emphasis on porphyrin-based compounds.