A strategy based on protein-protein interface motifs may help in identifying drug off-targets

Networks are increasingly used to study the impact of drugs at the systems level. From the algorithmic standpoint, a drug can "attack" nodes or edges of a protein-protein interaction network. In this work, we propose a new network strategy, "The Interface Attack", based on protein-protein interfaces. Similar interface architectures can occur between unrelated proteins. Consequently, in principle, a drug that binds to one has a certain probability of binding to others. The interface attack strategy simultaneously removes from the network all interactions that consist of similar interface motifs. This strategy is inspired by network pharmacology and allows inferring potential off-targets. We introduce a network model that we call "Protein Interface and Interaction Network (P2IN)", which is the integration of protein-protein interface structures and protein interaction networks. This interface-based network organization clarifies which protein pairs have structurally similar interfaces and which proteins may compete to bind the same surface region. We built the P2IN with the p53 signaling network and performed network robustness analysis. We show that (1) "hitting" frequent interfaces (a set of edges distributed around the network) might be as destructive as eleminating high degree proteins (hub nodes), (2) frequent interfaces are not always topologically critical elements in the network, and (3) interface attack may reveal functional changes in the system better than the attack of single proteins. In the off-target detection case study, we found that drugs blocking the interface between CDK6 and CDKN2D may also affect the interaction between CDK4 and CDKN2D.     

Boradiazaindacene (Bodipy)-based building blocks for the construction of energy transfer cassettes

Energy transfer cassettes composed entirely of boradiazaindacene (Bodipy) units were designed and synthesized to capture photonic energy and convert it to longer wavelength fluorescence emission. The new energy transfer systems obtained by simple condensation reactions are capable of elaborating efficient energy transfer from donor Bodipy units to the distyryl-Bodipy acceptor.     

Design, testing and two-dimensional flow modeling of a multiple-disk fan

A multiple-disk Tesla type fan has been designed, tested and analyzed two-dimensionally using the conservation of angular momentum principle. Experimental results showed that such multiple-disk fans exhibited exceptionally low performance characteristics, which could be attributed to the low viscosity, tangential nature of the flow, and large mechanical energy losses at both suction and discharge sections that are comparable to the total input power. By means of theoretical analysis, local and overall shearing stresses on the disk surfaces have been determined based on tangential and radial velocity distributions of the air flow of different volume flow rates at prescribed disk spaces and rotational speeds. Then the total power transmitted by rotating disks to air flow, and the power acquired by the air flow in the gap due to transfer of angular momentum have been obtained by numerically integrating shearing stresses over the disk surfaces. Using the measured shaft and hydraulic powers, these quantities were utilized to evaluate mechanical energy losses associated with the suction and discharge sections of the fan.     

Calculation of the stability and mechanical and phonon properties of NbRuB,TaRuB, and NbOsB compounds

The structural, mechanical, and phonon properties of NbRuB, TaRuB, and NbOsB compounds with orthorhombic space groups Pmma (No. 51) and Pbam (No. 55) are investigated by using first-principles calculations. The elastic constants and moduli, Debye temperature, Poisson’s ration, Pugh’s ratio, elastic anisotropy factors, and minimum thermal conductivities have been predicted to understand the mechanical behavior of these ternary compounds. The mechanical anisotropy is discussed via several anisotropy indices and two-dimensional (2D) surface constructions. We observe that all compounds ought to be classified as ductile materials and exhibit elastically anisotropy. Their mechanical and dynamical stability is confirmed via the calculated elastic constants and phonon dispersion curves, respectively. This work should provide a useful guide for designing ternary boride materials that have excellent thermoelectric performance.     

The effect of B2O3 addition to the microstructure and magnetic properties of Ni0.4Zn0.6Fe2O4 ferrite

The effects of 0.01 and 0.1 mol B₂O₃ addition to the microstructure and magnetic properties of a Ni–Zn ferrite composition expressed by a molecular formula of Ni_0.4Zn_0.6Fe₂O₄ were investigated. The toroid-shaped samples prepared by pressing the milled raw materials used in the preparation of the composition were sintered in the range of 1000–1300 °C. The addition of 0.01 mol B₂O₃ increased the grain growth and densification giving rise to reduced intergranular and intragranular porosity due to liquid-phase sintering. The sintered toroid sample at 1300 °C gave the optimum magnetic properties of B_r=170 mT, H_c=0.025 kA/m and a high initial permeability value of μ_i=4000. The increment of the B₂O₃ content to 0.1 mol resulted in a pronounced grain growth and also gave rise to large porosity due to the evaporation of B₂O₃ at higher sintering temperatures. Hence, it resulted in an air-gap effect in the hysteresis curves of these samples.     

离子液体作为溶剂/催化剂用于卤代烃对胺的选择性烷基化反应

在三乙胺存在下,在离子液体([bmim]I和[bmim]PF6)中进行了各种卤代烃对胺类化合物中氨基的选择性烷基化反应.反应在相对温和的条件下进行,转化率和选择性优异.离子液体可以回收并重复使用.     

Neural Network Structure Optimization by Simulated Annealing

A critical problem in large neural networks is over parameterization with a large number of weight parameters, which limits their use on edge devices due to prohibitive computational power and memory/storage requirements. To make neural networks more practical on edge devices and real-time industrial applications, they need to be compressed in advance. Since edge devices cannot train or access trained networks when internet resources are scarce, the preloading of smaller networks is essential. Various works in the literature have shown that the redundant branches can be pruned strategically in a fully connected network without sacrificing the performance significantly. However, majority of these methodologies need high computational resources to integrate weight training via the back-propagation algorithm during the process of network compression. In this work, we draw attention to the optimization of the network structure for preserving performance despite compression by pruning aggressively. The structure optimization is performed using the simulated annealing algorithm only, without utilizing back-propagation for branch weight training. Being a heuristic-based, non-convex optimization method, simulated annealing provides a globally near-optimal solution to this NP-hard problem for a given percentage of branch pruning. Our simulation results have shown that simulated annealing can significantly reduce the complexity of a fully connected network while maintaining the performance without the help of back-propagation.     

Near‐IR‐Triggered,Remote‐Controlled Release of Metal Ions: A Novel Strategy for Caged Ions

A ligand incorporating a dithioethenyl moiety is cleaved into fragments which have a lower metal‐ion affinity upon irradiation with low‐energy red/near‐IR light. The cleavage is a result of singlet oxygen generation which occurs on excitation of the photosensitizer modules. The method has many tunable factors that could make it a satisfactory caging strategy for metal ions.