Mechanistic implications for the formation of the diiron cluster in ribonucleotide reductase provided by quantitative EPR spectroscopy

The small subunit of Escherichia coli ribonucleotide reductase (R2) is a homodimeric (betabeta) protein, in which each beta-peptide contains a diiron cluster composed of two inequivalent iron sites. R2 is capable of reductively activating O(2) to produce a stable tyrosine radical (Y122*), which is essential for production of deoxyribonucleotides on the larger R1 subunit. In this work, the paramagnetic Mn(II) ion is used as a spectroscopic probe to characterize the assembly of the R2 site with EPR spectroscopy. Upon titration of Mn(II) into samples of apoR2, we have been able to quantitatively follow three species (aquaMn(II), mononuclear Mn(II)R2, and dinuclear Mn(2)(II)R2) and fit each to a sequential two binding site model. As previously observed for Fe(II) binding within apoR2, one of the sites has a greater binding affinity relative to the other, K(1) = (5.5 +/- 1.1) x 10(5) M(-)(1) and K(2) = (3.9 +/- 0.6) x 10(4) M(-)(1), which are assigned to the B and A sites, respectively. In multiple titrations, only one dinuclear Mn(2)(II)R2 site was created per homodimer of R2, indicating that only one of the two beta-peptides of R2 is capable of binding Mn(II) following addition of Mn(II) to apoR2. Under anaerobic conditions, addition of only 2 equiv of Fe(II) to R2 (Fe(2)(II)R2) completely prevented the formation of any bound MnR2 species. Upon reaction of this sample with O(2) in the presence of Mn(II), both Y122* and Mn(2)(II)R2 were produced in equal amounts. Previous stopped-flow absorption spectroscopy studies have indicated that apoR2 undergoes a protein conformational change upon binding of metal (Tong et al. J. Am. Chem. Soc. 1996, 118, 2107-2108). On the basis of these observations, we propose a model for R2 metal incorporation that invokes an allosteric interaction between the two beta-peptides of R2. Upon binding the first equiv of metal to a beta-peptide (beta(I)), the aforementioned protein conformational change prevents metal binding in the adjacent beta-peptide (beta(II)) approximately 25 A away. Furthermore, we show that metal incorporation into beta(II) occurs only during the O(2) activation chemistry of the beta(I)-peptide. This is the first direct evidence of an allosteric interaction between the two beta-peptides of R2. Furthermore, this model can explain the generally observed low Fe occupancy of R2. We also demonstrate that metal uptake and this newly observed allosteric effect are buffer dependent. Higher levels of glycerol cause loss of the allosteric effect. Reductive cycling of samples in the presence of Mn(II) produced a novel mixed metal Fe(III)Mn(III)R2 species within the active site of R2. The magnitude of the exchange coupling (J) determined for both the Mn(2)(II)R2 and Fe(III)Mn(III)R2 species was determined to be -1.8 +/- 0.3 and -18 +/- 3 cm(-)(1), respectively. Quantitative spectral simulations for the Fe(III)Mn(III)R2 and mononuclear Mn(II)R2 species are provided. This work represents the first instance where both X- and Q-band simulations of perpendicular and parallel mode spectra were used to quantitatively predict the concentration of a protein bound mononuclear Mn(II) species.     

“Golden” Cascade Cyclization to Benzo[c]-Phenanthridines

Herein, we describe a gold-catalyzed cascade cyclization of Boc-protected benzylamines bearing two tethered alkyne moieties in a domino reaction initiated by a 6-endo-dig cyclization. The reaction was screened intensively, and the scope was explored, resulting in nine new Boc-protected dihydrobenzo[c]phenanthridines with yields of up to 98 %; even a π-extension and two bidirectional approaches were successful. Furthermore, thermal cleavage of the Boc group and subsequent oxidation gave substituted benzo[c]phenanthridines in up to quantitative yields. Two bidirectional approaches under the optimized conditions were successful, and the resulting π-extended molecules were tested as organic semiconductors in organic thin-film transistors.     

On the Formation of a Protic Ionic Liquid in Nature

The practical utility of ionic liquids (ILs) makes the absence (heretofore) of reported examples from nature quite puzzling, given the facility with which nature produces many other types of exotic but utilitarian substances. In that vein, we report here the identification and characterization of a naturally occurring protic IL. It can be formed during confrontations between the ants S. invicta and N. fulva. After being sprayed with alkaloid‐based S. invicta venom, N. fulva detoxifies by grooming with its own venom, formic acid. The mixture is a viscous liquid manifestly different from either of the constituents. Further, we find that the change results as a consequence of formic acid protonation of the N centers of the S. invicta venom alkaloids. The resulting mixed‐cation ammonium formate milieu has properties consistent with its classification as a protic IL.     

On the convergence rate improvement of a primal-dual splitting algorithm for solving monotone inclusion problems

We present two modified versions of the primal-dual splitting algorithm relying on forward–backward splitting proposed in V\(\tilde{\mathrm{u}}\) (Adv Comput Math 38(3):667–681, 2013) for solving monotone inclusion problems. Under strong monotonicity assumptions for some of the operators involved we obtain for the sequences of iterates that approach the solution orders of convergence of \(\mathcal{{O}}(\frac{1}{n})\) and \(\mathcal{{O}}(\omega ^n)\), for \(\omega \in (0,1)\), respectively. The investigated primal-dual algorithms are fully decomposable, in the sense that the operators are processed individually at each iteration. We also discuss the modified algorithms in the context of convex optimization problems and present numerical experiments in image processing and pattern recognition in cluster analysis.     

A double smoothing technique for solving unconstrained nondifferentiable convex optimization problems

The aim of this paper is to develop an efficient algorithm for solving a class of unconstrained nondifferentiable convex optimization problems in finite dimensional spaces. To this end we formulate first its Fenchel dual problem and regularize it in two steps into a differentiable strongly convex one with Lipschitz continuous gradient. The doubly regularized dual problem is then solved via a fast gradient method with the aim of accelerating the resulting convergence scheme. The theoretical results are finally applied to an l ₁ regularization problem arising in image processing.