Electrokinetic characterization of hybrid NOA 81-glass microchips: Application to protein microchip electrophoresis with indirect fluorescence detection

A low-cost and straightforward hybrid NOA (Norland optical adhesive) 81-glass microchip electrophoresis device was designed and developed for protein separation using indirect fluorescence detection. This new microchip was first characterized in terms of surface charge density via electroosmotic mobility measurement and stability over time. A systematic determination of the electroosmotic mobility (μ_eo) over a wide pH range (2–10) and at various ionic strengths (20–50 mM) was developed for the first time via the neutral marker approach in an original simple frontal methodology. The evolution of μ_eo was proved consistent with the silanol and thiol functions arising from the glass and the NOA materials, respectively. The repeatability and reproducibility of the measurements on different microchips (RSD < 14%) and within 15 days (less than 5% decrease) were successfully demonstrated. The microchip was then applied for the efficient electrophoretic separation of proteins in a zonal mode coupled with indirect fluorescence detection, which is, to our knowledge, the first proof of concept of capillary zone electrophoresis in this hybrid microsystem.     

Effects of mussel-inspired co-deposition of 2-hydroxymethyl methacrylate and poly (2-methoxyethyl acrylate) on the hydrophilicity and binding tendency of common hemodialysis membranes: Molecular dynamics simulations and molecular docking studies

Despite advances in the field, hemoincompatibility remains a critical issue for hemodialysis (HD) as interactions between various human blood constituents and the polymeric structure of HD membranes results in complications such as activation of immune system cascades. Adding hydrophilic polymer structures to the membranes is one modification approach that can decrease the extent of protein adsorption. This study conducted molecular dynamics (MD) simulations to understand the interactions between three human serum proteins (fibrinogen [FB], human serum albumin, and transferrin) and common HD membranes in untreated and modified forms. Poly(aryl ether sulfone) (PAES) and cellulose triacetate were used as the common dialyzer polymers, and membrane modifications were performed with 2-hydroxymethyl methacrylate (HEMA) and poly (2-methoxyethyl acrylate) (PMEA), using polydopamine-assisted co-deposition. The MD simulations were used as the framework for binding energy simulations, and molecular docking simulations were also performed to conduct molecular-level investigations between the two modifying polymers (HEMA and PMEA) and FB. Each of the three proteins acted differently with the membranes due to their unique nature and surface chemistry. The simulations show PMEA binds less intensively to FB with a higher number of hydrogen bonds, which reflects PMEA's superior performance compared to HEMA. The simulations suggest PAES membranes could be used in modified forms for blood-contact applications as they reflect the lowest binding energy to blood proteins.     

RDX分子内振动能量重分配的动力学研究

基于从头算分子动力学(Born-oppenheimer molecular dynamics, BOMD)模拟, 构建了环硝胺六氢-1,3,5-三硝基-1,3,5-三嗪(RDX)单分子不同振动模式之间的耦合矩阵, 并计算了在不同加载能量下从低频振动模式到高频振动模式的最优能量传输路径. 结果表明, RDX单分子中—NNO₂基团更有利于能量局域化, 振动模式v₃和v₄在从低频振动模式到高频振动模式的能量传输过程中扮演着重要角色. 通过对v₃和v₄两个振动模式的进一步分析发现, 加载能量的不同会导致RDX单分子能量传输路径的不同. 当加载能量较低时, RDX单分子倾向于从低频振动模式到中频振动模式再到高频振动模式的能量传输路径; 当加载能量较高时, 能量更倾向于从低频振动模式直接传输到高频振动模式上. 揭示了RDX分子内振动耦合能量转移的微观机制, 为进一步探索RDX将“机械能”转化为“化学能”的微观过程提供了理论基础.     

Macrocycle Dynamics in a Branched [8]Catenane Controlled by Three Different Stimuli in Three Different Regions

A branched [8]catenane from an efficient one-pot synthesis (72 % HPLC yield, 59 % isolated yield) featuring the simultaneous use of three kinds of templates and cucurbit[6]uril-mediated azide–alkyne cycloaddition (CBAAC) for ring-closing is reported. Design and assembly of the [8]catenane precursors are unexpectedly complex that can involve cooperating, competing and non-influencing interactions. Due to the branched structure, dynamics of the [8]catenane can be modulated in different extent by rigidifying/loosening the mechanical bonds at different regions by using solvent polarity, acid-base and metal ions as the stimuli. This work not only highlights the importance of understanding the delicate interplay of the weak and non-obvious supramolecular interactions in the synthesis of high-order [n]catenane, but also demonstrates a complex control of dynamics and flexibility for exploiting [n]catenanes applications.     

A two-point calibration method for quantifying organic binary mixtures using secondary ion mass spectrometry in the presence of matrix effects

Quantification of the composition of binary mixtures in secondary ion mass spectrometry (SIMS) is required in the analyses of technological materials from organic electronics to drug delivery systems. In some instances, it is found that there is a linear dependence between the composition, expressed as a ratio of component volumes, and the secondary ion intensities, expressed as a ratio of intensities of ions from each component. However, this ideal relationship fails in the presence of matrix effects and linearity is observed only over small compositional ranges, particularly in the dilute limits. In this paper, we assess an empirical method, which introduces a power law dependence between the intensity ratio and the volume fraction ratio. A previously published physical model of the organic matrix effect is employed to test the limits of the method and a mixed system of 3,3′-bis(9-carbazolyl) biphenyl and tris(2-phenylpyridinato)iridium (III) is used to demonstrate the method. This paper introduces a two-point calibration, which determines both the exponent in the power law and the sensitivity factor for the conversion of ion intensity ratio into volume fraction ratio. We demonstrate that this provides significantly improved accuracy, compared with a one-point calibration, over a wide compositional range in SIMS quantification and with a weak dependence on matrix effects. Because the method enables the use of clearly identifiable secondary ions for quantitative purposes and mitigates commonly observed matrix effects in organic materials, the two-point calibration method could be of significant benefit to SIMS analysts.     

Analysis of drug interactions with serum proteins and related binding agents by affinity capillary electrophoresis: A review

Biomolecules such as serum proteins can interact with drugs in the body and influence their pharmaceutical effects. Specific and precise methods that analyze these interactions are critical for drug development or monitoring and for diagnostic purposes. Affinity capillary electrophoresis (ACE) is one technique that can be used to examine the binding between drugs and serum proteins, or other agents found in serum or blood. This article will review the basic principles of ACE, along with related affinity-based capillary electrophoresis (CE) methods, and examine recent developments that have occurred in this field as related to the characterization of drug–protein interactions. An overview will be given of the various formats that can be used in ACE and CE for such work, including the relative advantages or weaknesses of each approach. Various applications of ACE and affinity-based CE methods for the analysis of drug interactions with serum proteins and other binding agents will also be presented. Applications of ACE and related techniques that will be discussed include drug interaction studies with serum agents, chiral drug separations employing serum proteins, and the use of CE in hybrid methods to characterize drug binding with serum proteins.     

多组件学习器实现有机分子沸点的精准预测

沸点(BP)是有机分子液体的基本物理化学量, 也是化学工业生产中的重要参数. 有机分子的沸点由分子结构决定, 呈现复杂的结构-沸点关系, 函数法(Function Method)、基团贡献法(Group Contribution Method)等传统方法无法应对复杂多样有机分子结构的预测, 应用范围狭窄, 预测精度低. 本研究中, 我们利用基于人工神经网络(ANN)和支持向量机(SVM)的多组件学习器实现有机分子沸点的精准预测. 我们构建了基于可解释性描述符的ANN、基于相关性描述符的ANN及基于复合分子指纹的SVM三个异质模型, 并通过包含4550个各种类别的有机分子沸点的数据集进行训练得到了三个异质性学习器, 最后集成三个学习器对有机分子沸点进行预测. 相比于传统方法和此前的定量结构性质关系(QSPR)模型, 多组件模型结合了三种模型的优点, 展现出很好的预测精度和泛化能力以及低的过拟合, 实现了对多种类型有机分子的沸点的有效预测.