Structural analysis based on state-space modeling.

A new method has been developed to compute the probability that each amino acid in a protein sequence is in a particular secondary structural element. Each of these probabilities is computed using the entire sequence and a set of predefined structural class models. This set of structural classes is patterned after Jane Richardson''s taxonomy for the domains of globular proteins. For each structural class considered, a mathematical model is constructed to represent constraints on the pattern of secondary structural elements characteristic of that class. These are stochastic models having discrete state spaces (referred to as hidden Markov models by researchers in signal processing and automatic speech recognition). Each model is a mathematical generator of amino acid sequences; the sequence under consideration is modeled as having been generated by one model in the set of candidates. The probability that each model generated the given sequence is computed using a filtering algorithm. The protein is then classified as belonging to the structural class having the most probable model. The secondary structure of the sequence is then analyzed using a "smoothing" algorithm that is optimal for that structural class model. For each residue position in the sequence, the smoother computes the probability that the residue is contained within each of the defined secondary structural elements of the model. This method has two important advantages: (1) the probability of each residue being in each of the modeled secondary structural elements is computed using the totality of the amino acid sequence, and (2) these probabilities are consistent with prior knowledge of realizable domain folds as encoded in each model. As an example of the method''s utility, we present its application to flavodoxin, a prototypical alpha/beta protein having a central beta-sheet, and to thioredoxin, which belongs to a similar structural class but shares no significant sequence similarity.     

Crystal structure of Zn(trz)Cl (trz = 11,2,4,-triazolato); a layered compound with triply bridging triazolato groups

ZnCl₂ reacts with 1,2,4-1H-triazole to afford Zn(trz)Cl. A spontaneous deprotonation of Htrz occurs. The crystal structure of Zn(trz)Cl has been solved. The compound crystallizes in the space group P2₁/n. The lattice parameters are a = 8.863(4), B = 9.762(4), C = 6.146(3) Å, β = 99.56(10)°, with Z = 4. The 1,2,4-triazolato bridges three zinc atoms through its three nitrogen atoms, affording a layered structure. The zinc atom is in an N₃Cl tetrahedral coordination. The layers are not planar, but rather corrugated. The chlorine atoms point to either side of the layers, and play the role of spacers. The shortest interlayer ZnZn separation is 5.701 Å.     

Tertiary motifs as building blocks for the design of protein‐binding peptides

Despite advances in protein engineering, the de novo design of small proteins or peptides that bind to a desired target remains a difficult task. Most computational methods search for binder structures in a library of candidate scaffolds, which can lead to designs with poor target complementarity and low success rates. Instead of choosing from pre‐defined scaffolds, we propose that custom peptide structures can be constructed to complement a target surface. Our method mines tertiary motifs (TERMs) from known structures to identify surface‐complementing fragments or “seeds.” We combine seeds that satisfy geometric overlap criteria to generate peptide backbones and score the backbones to identify the most likely binding structures. We found that TERM‐based seeds can describe known binding structures with high resolution: the vast majority of peptide binders from 486 peptide‐protein complexes can be covered by seeds generated from single‐chain structures. Furthermore, we demonstrate that known peptide structures can be reconstructed with high accuracy from peptide‐covering seeds. As a proof of concept, we used our method to design 100 peptide binders of TRAF6, seven of which were predicted by Rosetta to form higher‐quality interfaces than a native binder. The designed peptides interact with distinct sites on TRAF6, including the native peptide‐binding site. These results demonstrate that known peptide‐binding structures can be constructed from TERMs in single‐chain structures and suggest that TERM information can be applied to efficiently design novel target‐complementing binders.     

A new precursor for organo-osmium complexes

The use of potassium osmate, K₂[OsO₂(OH)₄], as a precursor for some cyclopentadienyl-osmium complexes is described. The X-ray structures of OsBr(PPh₃)₂Cp, OsCl(dppe)Cp and OsX(dppe)Cp^∗ (X = Cl, Br) are reported.     

虎杖象甲培植真菌营养特性及对菌丝附属物形成的影响

虎杖象甲培植共生真菌形成的共生体系是植菌昆虫菌业中的典型代表。共生真菌Penicillium herquei如何向虎杖象甲Euops chinensis提供营养尚未明确。本研究发现共生真菌P. herquei的菌丝表面存在大量瘤状凸起物及由凸起物衍生的附属丝等特化结构,该结构可能为虎杖象甲提供营养;对共生真菌的营养研究表明,共生真菌能高效利用山梨醇、蔗糖、海藻糖、葡萄糖等单糖或双糖,以及酪氨酸、甘氨酸、谷氨酰胺等昆虫非必须氨基酸,同时在高碳和最适碳源条件下有利于菌丝特化附属物的产生。研究结果不仅提供了植菌卷叶象甲菌业中共生真菌在营养方面的适应性进化证据,而且为进一步揭示共生真菌适应卷叶象甲的营养机制奠定了基础。     

Understanding Molecular Structures of Buried Interfaces in Halide Perovskite Photovoltaic Devices Nondestructively with Sub‐Monolayer Sensitivity Using Sum Frequency Generation Vibrational Spectroscopy

As performance of halide perovskite devices progresses, the device structure becomes more complex with more layers. Molecular interfacial structures between different layers play an increasingly important role in determining the overall performance in a halide perovskite device. However, current understanding of such interfacial structures at a molecular level nondestructively is limited, partially due to a lack of appropriate analytical tools to probe buried interfacial molecular structures in situ. Here, sum frequency generation (SFG) vibrational spectroscopy, a state‐of‐the‐art nonlinear interface sensitive spectroscopy, is introduced to the halide perovskite research community and is presented as a powerful tool to understand molecule behavior at buried halide perovskite interfaces in situ. It is found that interfacial molecular orientations revealed by SFG can be directly correlated to halide perovskite device performance. Here how SFG can examine molecular structures (e.g., orientations) at the perovskite/hole transporting layer and perovskite/electron transporting layer interfaces is discussed. This will promote the use of SFG to investigate molecular structures of buried interfaces in various halide perovskite materials and devices in situ nondestructively with a sub‐monolayer interface sensitivity. Such research will help to elucidate structure–function relationships of buried interfaces, aiding in the rational design/development of halide perovskite materials/devices with improved performance.     

Local Treatment of Murine Tumors by Electric Direct Current

Low-level direct current (0.2–1.8 mA) was demonstrated to be an antitumor agent on two different murine tumor models (fibrosarcoma Sa-1 and melanoma B-16), and has been suggested for regional cancer treatment. Its antitumor effect was achieved by introduction of single or multiple–array needle electrodes (Pt-Ir alloy) in the tumor and (an)other electrode(s) subcutaneously in its vicinity. The electrode inserted in the tumor was made anodic (anodic electrotherapy, ET) or cathodic (cathodic ET). In control groups, animals were subjected to exactly the same procedures with needle electrodes inserted at usual sites without current. In single-stimulus ET performed after the tumors have reached approximately 50 mm3 in volume with 0.2, 0.6, and 1.O mA for 30, 60, and 90 min, cathodic ET exhibited better antitumor effect than anodic ET. In both cases and at all ET durations, the antitumor effect depended proportionally on the current level applied. The antitumor effect was evaluated by following tumor growth and by microscopic estimation of the necrotization of the tumor area immediately after ET, and 24, 48, and 72 h posttreatment.

Necrotization produced by cathodic ET was observed to be immediate and extensive whereas anodic ET resulted in increased necrotization only at 24 h posttreatment. In both cases the extent of necrosis was significantly higher than in control and was centrally located (site of electrode), whereas in controls it was sporadic, distributed randomly over the whole tumor area. When current was delivered via multiple–array electrode ET, the antitumor effect was slightly better in cathodic ET compared to single-electrode ET. Employing cathodic multiple-array electrode ET and using higher currents, i.e., 1.0, 1.4, and 1.8 mA in melanoma B-16, 20% and 40% cures were achieved by 1.4 and 1.8 mA single-shot ET of 1 h duration, respectively, whereas in fibrosarcoma Sa-1 no cures were accomplished. In general, different susceptibility of the two tumor models to ET was noticeable. Comparing tumor growth and necrotization after the application of direct current (0.6 mA) and alternating current (0.0 mA mean, 0.6 mA RMS), it appeared that alternating current had no impact either on necrotization of tumor tissue or on tumor growth. ET was performed on normal tissues as well. In subcutaneous tissue, thigh muscle, and liver of healthy mice immediately after 1 h of treatment using 0.6 mA in both cathodic and anodic modes, local necrotization at the site of electrode insertion was evident, with signs of acute inflammation in the vicinity. In anodic ET, vacuolization around the electrode was noticed.     

Comparing methods for metabolic network analysis and an application to metabolic engineering

Bioinformatics tools have facilitated the reconstruction and analysis of cellular metabolism of various organisms based on information encoded in their genomes. Characterization of cellular metabolism is useful to understand the phenotypic capabilities of these organisms. It has been done quantitatively through the analysis of pathway operations. There are several in silico approaches for analyzing metabolic networks, including structural and stoichiometric analysis, metabolic flux analysis, metabolic control analysis, and several kinetic modeling based analyses. They can serve as a virtual laboratory to give insights into basic principles of cellular functions. This article summarizes the progress and advances in software and algorithm development for metabolic network analysis, along with their applications relevant to cellular physiology, and metabolic engineering with an emphasis on microbial strain optimization. Moreover, it provides a detailed comparative analysis of existing approaches under different categories.     

Temperature‐dependent conformational change affecting Tyr11 and sweetness loops of brazzein

The sweet protein brazzein, a member of the Csβα fold family, contains four disulfide bonds that lend a high degree of thermal and pH stability to its structure. Nevertheless, a variable temperature study has revealed that the protein undergoes a local, reversible conformational change between 37 and 3°C with a midpoint about 27°C that changes the orientations and side‐chain hydrogen bond partners of Tyr8 and Tyr11. To test the functional significance of this effect, we used NMR saturation transfer to investigate the interaction between brazzein and the amino terminal domain of the sweet receptor subunit T1R2; the results showed a stronger interaction at 7°C than at 37°C. Thus the low temperature conformation, which alters the orientations of two loops known to be critical for the sweetness of brazzein, may represent the bound state of brazzein in the complex with the human sweet receptor. Proteins 2013; © 2012 Wiley Periodicals, Inc.