苦咸水反渗透淡化中膜面结垢预测及防垢进展

苦咸水反渗透（BWRO）中的防垢过程,首先取决于给水水质,而根据水质条件和垢在膜面的形成机理采取相应的防垢措施是非常重要的。 显然,有效地管控膜面无机结垢及抑制膜面污染需要开展无机结垢趋势的预测、防垢措施和非破坏性无机垢监控等方面的技术研究。 一系列传统和新兴的分析技术,包括摩尔比率法、直接目测法和光谱法等已应用于BWRO过程中膜面防垢研究。 本文详细综述了该过程中无机结垢趋势的预测、防垢方法和非破坏性无机垢监控技术等方面的研究进展。 此外,针对目前的研究方向提出了建议。     

Hydrophobic collapse in (in silico) protein folding

A model of hydrophobic collapse, which is treated as the driving force for protein folding, is presented. This model is the superposition of three models commonly used in protein structure prediction: (1) 'oil-drop' model introduced by Kauzmann, (2) a lattice model introduced to decrease the number of degrees of freedom for structural changes and (3) a model of the formation of hydrophobic core as a key feature in driving the folding of proteins. These three models together helped to develop the idea of a fuzzy-oil-drop as a model for an external force field of hydrophobic character mimicking the hydrophobicity-differentiated environment for hydrophobic collapse. All amino acids in the polypeptide interact pair-wise during the folding process (energy minimization procedure) and interact with the external hydrophobic force field defined by a three-dimensional Gaussian function. The value of the Gaussian function usually interpreted as a probability distribution is treated as a normalized hydrophobicity distribution, with its maximum in the center of the ellipsoid and decreasing proportionally with the distance versus the center. The fuzzy-oil-drop is elastic and changes its shape and size during the simulated folding procedure.     

Prediction of Rheological Properties of Multi-Component Dispersions by Using Artificial Neural Networks

This article shows the ability of artificial neural network (ANN) technology for predicting the correlation between rheological properties of multi-component food model systems and their chemical compositions. Multi-component food model systems were made of whey protein isolate (WPI) (2, 4 wt%), Iranian tragacanth gum (TG) (Astragalus gossypinus) (0.5, 1 wt%) and oleic acid (5, 10% v/v). The input parameters of the neural networks (NN) were these chemical compositions, namely WPI and TG concentrations, and oleic acid volume fractions. The output parameters of the NN models were rheological properties of multi-component food model systems (flow and consistency indices, viscosity, loss and storage moduli). Results showed that, ANN with training algorithm of back propagation (BP) was the best one for the creation of nonlinear mapping between input and output parameters. The best topology was 3-10-5. The ANN model predicted the rheological properties of multi-component food model systems with average RMSE 4.529 and average MAE 3.018. These results show that the ANN can potentially be used to estimate rheological parameters of multi-component food model systems from chemical composition. This development may have significant potential to improve product quality control and reduce time and costs by minimizing the rheological experiments.     

Multidimensional umbrella sampling and replica‐exchange molecular dynamics simulations for structure prediction of transmembrane helix dimers

Structural information of a transmembrane (TM) helix dimer is useful in understanding molecular mechanisms of important biological phenomena such as signal transduction across the cell membrane. Here, we describe an umbrella sampling (US) scheme for predicting the structure of a TM helix dimer in implicit membrane using the interhelical crossing angle and the TM–TM relative rotation angles as the reaction coordinates. This scheme conducts an efficient conformational search on TM–TM contact interfaces, and its robustness is tested by predicting the structures of glycophorin A (GpA) and receptor tyrosine kinase EphA1 (EphA1) TM dimers. The nuclear magnetic resonance (NMR) structures of both proteins correspond to the global free‐energy minimum states in their free‐energy landscapes. In addition, using the landscape of GpA as a reference, we also examine the protocols of temperature replica‐exchange molecular dynamics (REMD) simulations for structure prediction of TM helix dimers in implicit membrane. A wide temperature range in REMD simulations, for example, 250–1000 K, is required to efficiently obtain a free‐energy landscape consistent with the US simulations. The interhelical crossing angle and the TM–TM relative rotation angles can be used as reaction coordinates in multidimensional US and be good measures for conformational sampling of REMD simulations. © 2013 Wiley Periodicals, Inc.     

SSThread: Template‐free protein structure prediction by threading pairs of contacting secondary structures followed by assembly of overlapping pairs

Acquiring the three‐dimensional structure of a protein from its amino acid sequence alone, despite a great deal of work and significant progress on the subject, is still an unsolved problem. SSThread, a new template‐free algorithm is described here that consists of making several predictions of contacting pairs of α‐helices and β‐strands derived from a database of experimental structures using a knowledge‐based potential, secondary structure prediction, and contact map prediction followed by assembly of overlapping pair predictions to create an ensemble of core structure predictions whose loops are then predicted. In a set of seven CASP10 targets SSThread outperformed the two leading methods for two targets each. The targets were all β‐strand containing structures and most of them have a high relative contact order which demonstrates the advantages of SSThread. The primary bottlenecks based on sets of 74 and 21 test cases are the pair prediction and loop prediction stages. © 2014 Wiley Periodicals, Inc.     

Prediction of Retention Time of Solutes under Linear Gradient Elution Conditions in RP-HPLC

A model for prediding retention time of solutes undeir linear gradient elulioa conditions has been established. In this model,the theorelkal expressions under different eluflon modes were derived and tested with the retention behaviors of p-hydroxy-benzaldehyde, vanilUn, biphenyl, phenanthrene in gradient elution. With halting into account the dwell time of the instrumeatal system, the theoretically predicted retention times agreewell with those experimentally determined.     

The importance of short structural motifs in protein structure analysis

Summary Proteins tend to use recurrent structural motifs on all levels of organization. In this paper we first survey the topics of recurrent motifs on the local secondary structure level and on the global fold level. Then, we focus on the intermediate level which we call the short structural motifs. We were able to identify a set of structural building blocks that are very common in protein structure. We suggest that these building blocks can be used as an important link between the primary sequence and the tertiary structure. In this framework, we present our latest results on the structural variability of the extended strand motifs. We show that extended strands can be divided into three distinct structural classes, each with its own sequence specificity. Other approaches to the study of short structural motifs are reviewed.