Statistical interior properties of globular proteins

The character of forming long-range contacts affects the three-dimensional structure of globular proteins deeply. As the different ability to form long-range contacts between 20 types of amino acids and 4 categories of globular proteins, the statistical properties are thoroughly discussed in this paper. Two parameters N_C and N_D are defined to confine the valid residues in detail. The relationship between hydrophobicity scales and valid residue percentage of each amino acid is given in the present work and the linear functions are shown in our statistical results. It is concluded that the hydrophobicity scale defined by chemical derivatives of the amino acids and nonpolar phase of large unilamellar vesicle membranes is the most effective technique to characterise the hydrophobic behavior of amino acid residues. Meanwhile, residue percentage P_i and sequential residue length L_i of a certain protein i are calculated under different conditions. The statistical results show that the average value of P_i as well as L_i of all-α proteins has a minimum among these 4 classes of globular proteins, indicating that all-α proteins are hardly capable of forming long-range contacts one by one along their linear amino acid sequences. All-β proteins have a higher tendency to construct long-range contacts along their primary sequences related to the secondary configurations, i.e. parallel and anti-parallel configurations of β sheets. The investigation of the interior properties of globular proteins give us the connection between the three-dimensional structure and its primary sequence data or secondary configurations, and help us to understand the structure of protein and its folding process well.     

Nonlinear signal analysis to understand the dynamics of the protein sequences

Recurrence plots are a useful tool to identify structure in a data set in a time resolved way qualitatively. Recurrence plots and its quantification has become an important research tool in the analysis of nonlinear dynamical systems. In the present work, we utilize the recurrence property to study the protein sequences. The sequences that we analyze belong to two distinct classes, viz., soluble proteins and proteins that form inclusion bodies when over expressed in Escherichia coli. We use Kyte-Doolittle hydrophobicity scale in the analysis. We study the underlying dynamics and extract the information which codes the essential class of a protein using simple statistical and global characteristics based features as well as some advanced features based on recurrence quantification. The extracted features are used in probability estimation using Gaussian Process Classification technique. The results give meaningful insights to the level of understanding the protein sequence dynamics.     

Transformational Homologies in Amino Acid Sequences Suggest Memberships in Protein Families

The 20 amino acid monomers composing polymeric proteins are encoded using their individual properties relatable to thermodynamic potentials such as aqueous partial specific volumes, aqueous molar volumes, and free energies of transfer from hydrocarbon to water solvents. These principally hydrophobic solvation, “hydrophobicity”-derived free energies are minimized in protein folding as well as protein–protein and peptide–receptor interactions. Sequential patterns in the one-dimensional distribution of these energies, reflected in dominant wavelengths of amino acid hydrophobicity, and the locations of singular hierarchical, secondary and supersecondary structures are elucidated by orthogonal decomposition and eigenfunction construction followed by continuous wavelet and all poles, maximum entropy power spectral transformations. The resulting graphs discriminate among examples of structural families of proteins.     

Elucidation of conserved long-range interaction networks in proteins and their significance in determining protein topology

Investigations into the nature of sequence and structural conservation underlying protein folds have recently yielded profound insights into the mechanism of protein folding and stability. Combining this avenue of research with principles being pioneered in the field of network science holds the promise to further extend the boundaries of our knowledge. In this report we propose that critical determinants of a protein's native topology are encoded by a conserved network of interactions between amino acids from geographically important positions. This hypothesis is based on the novel elucidation of a conserved network of long-range interactions within a set of proteins that share a Greek-key topology and similar chain length, but differ in secondary structure composition, function and sequence. Exploratory macromolecular simulations using the conserved networks as constraints were successful in generating the gross native-like topology from a random linear coil for each of the model proteins. The results indicate that the conserved network contains governing features and supports the idea that the geographical location of these residue interactions is a pivotal feature underlying their conservation. The partially folded model proteins also display a clear scale-free distribution of long-range interactions. To further test the hypothesis, the network parameter betweeness-centrality was calculated for the protein structure networks of our model proteins and highlights two structural elements as particularly vital to the structural stability of the network topology.     

Inferring topological features of proteins from amino acid residue networks

Topological properties of native folds are obtained from statistical analysis of 160 low homology proteins covering the four structural classes. This is done analyzing one, two and three-vertex joint distribution of quantities related to the corresponding network of amino acid residues. Emphasis on the amino acid residue hydrophobicity leads to the definition of their center of mass as vertices in this contact network model with interactions represented by edges. The network analysis helps us to interpret experimental results such as hydrophobic scales and fraction of buried accessible surface area in terms of the network connectivity. Moreover, those networks show assortative mixing by degree. To explore the vertex-type dependent correlations, we build a network of hydrophobic and polar vertices. This procedure presents the wiring diagram of the topological structure of globular proteins leading to the following attachment probabilities between hydrophobic–hydrophobic 0.424(5), hydrophobic-polar 0.419(2) and polar–polar 0.157(3) residues.     

Modifying the physicochemical properties,solubility and foaming capacity of milk proteins by ultrasound-assisted alkaline pH-shifting treatment

This study investigated the effects of different treatment of alkaline pH-shifting on milk protein concentrate (MPC), micellar casein concentrate (MCC) and whey protein isolate (WPI) assisted by the same ultrasound conditions, including changes in the physicochemical properties, solubility and foaming capacity. The solubility of milk proteins had a significant increase with gradual enhancement of ultrasound-assisted alkaline pH-shifting (p < 0.05), especially for MCC up to 99.50 %. Also, treatment made a significant decline in the particle size of MPC and MCC, as well as the turbidity of the proteins (p < 0.05). The foaming capacity of MPC, MCC, and WPI was all improved, especially at pH 11, and at this pH, the milk protein also showed the highest surface hydrophobicity. The best foaming capacity at pH 11 was the result of the combined effect of particle size, potential, protein conformation, solubility, and surface hydrophobicity. In conclusion, ultrasound-assisted pH-shifting treatment was found to be effective in improving the physicochemical properties and solubility and foaming capacity of milk proteins, especially MCC, with promising application prospect in food industry.     

Assessment of acute myocardial infarction in man with magnetic resonance imaging and the use of a new paramagnetic contrast agent gadolinium-bopta

To assess the feasibility of and characterize the new paramagnetic contrast agent gadolinium-BOPTA/dimeglumine (Gd-BOPTA) to detect acute myocardial infarctions with MR imaging, 24 patients (53.3 ± 8.3 yr) were examined 9.3 ± 3.6 days after a first myocardial infarction. Short-axis T₁-weighted and T₂-weighted MR imaging was performed at three slice levels. T₁-weighted images were obtained before, immediately after, 15, 30, and 45 min after injection. Patients received either 0.05 or 0.1 mmol/kg body weight Gd-BOPTA. Images were qualitatively and quantitatively analyzed. Two patients showed no signs of infarction on T₂-weighted images as opposed to contrast-enhanced T₁-weighted images. Contrast-to-noise ratio was not affected by the dosage level. Signal intensity (SI) of normal to infarcted myocardium was significantly improved by both dosages (p < .0005) but a dosage of 0.05 mmol/kg produced significantly higher SI inf/norm (1.42 ± 0.07 vs. 1.34 ± 0.06, respectively, p = .015). SI of normal and infarcted myocardium enhanced immediately after administration of 0.05 mmol/kg (29.3 ± 5.1% and 53.8 ± 9.6% respectively), which decreased thereafter to 5.3 ± 4.8% and 40.2 ± 8.5% respectively, at 45 min (p < .002 for normal myocardium). SI enhancement immediately after 0.1 mmol/kg Gd-BOPTA showed no decrease within the first 45 min. Gd-BOPTA enables the detection of myocardial infarction. Optimal infarct delineation is achieved from 15 to 45 min after administration of 0.05 mmol/kg body weight Gd-BOPTA. Gd-BOPTA at 0.05 mmol/kg does improve image quality as measured by contrast-to-noise ratio and SI enhancement as compared to 0.10 mmol/kg.     

Rigorous mean-field model for coherent-potential approximation: Anderson model with free random variables

A model of a randomly disordered system with site-diagonal random energy fluctuations is introduced. It is an extension of Wegner'sn-orbital model to arbitrary eigenvalue distribution in the electronic level space. The new feature is that the random energy values are not assumed to be independent at different sites, but free. Freeness of random variables is an analog of the concept of independence for noncommuting random operators. A possible realization is the ensemble of randomly rotated matrices at different lattice sites. The one- and two-particle Green functions of the proposed Hamiltonian are calculated exactly. The eigenstates are extended and the conductivity is novanishing everywhere inside the band. The long-range behavior and the zero-frequency limit of the two-particle Green function are universal with respect to the eigenvalue distribution in the electronic level space. The solutions solve the CPA equation for the one- and two-particle Green function of the corresponding Anderson model. Thus our (multisite) model is a rigorous mean-field model for the (single-site) CPA. We show how the Lloyd model is included in our model and treat various kinds of noises.     

基于时序Sentinel-2A影像的玉米秸秆覆盖区智能识别研究

秸秆还田是减少土壤侵蚀、增加土壤有机碳的重要措施，对黑土地保护具有重要意义。区域范围内玉米秸秆覆盖区的准确、快速识别，对监测保护性耕作实施、农业补贴政策的制定具有重要作用。以实施保护性耕作的典型区吉林省四平市为研究区，基于GEE(google earth engine)云平台，结合2020年5月—11月的Sentinel-2时序遥感影像，依据玉米生长季和收获后的秸秆状态构建光谱特征和指数特征，指数特征包括归一化差值植被指数(NDVI)和归一化差值秸秆指数(NDRI)。为避免数据冗余，对时序特征值按大小排序，同时利用分位法以0%，25%，50%，75%，100%分位选取分位(QT)特征，进而构建数据集。应用参数优化后的随机森林方法对按照7∶3划分的样本集进行训练和验证，然后对数据集分类，结合连通域标定法去除分类过程中产生的细小连通域，进一步优化全局结果。通过Kappa和整体精度(OA)定量和定性评价，实验结果表明：(1) 基于不同特征集组成数据集的分类模型(M1/M2/M3/M4/M5)定量评价结果均优于90%，其中所设计数据集的分类模型M5效果最好，Kappa和OA分别为97.41%和97.91%，相比于未加入QT特征集的分类模型M2的Kappa和OA分别提升4.52%和3.64%，同时M5识别结果可以有效保留边缘细节信息；(2)针对不同时间尺度的QT特征集，利用5月—11月时序遥感影像的QT特征集分类模型M5_6/M5可以极大地抑制其他作物秸秆的影响，相比仅利用11月时序影像QT特征的M5_1模型分类结果的Kappa和OA分别提升了3.9%和3.12%；(3) 基于M5模型，结合连通域标定法的分类模型M6的Kappa和OA分别为96.76%和97.36%，仅次于M5模型识别结果，模型M6在保证较高精度的同时避免了细碎图斑，优化了分类可视化效果。该研究提出的M6模型适用于识别研究区玉米秸秆覆盖区，该方法能够在GEE云平台环境下快速执行，适合推广应用于东北地区秸秆覆盖区。     

Do topological parameters of amino acids within protein contact networks depend on their physico-chemical properties?

The three dimensional structure of a protein is determined by the interactions of its constituent amino acids. Considering the amino acids as nodes and the non-bonded interactions among them in 3D space as edges, researchers have constructed protein contact networks and analyzed the values of several topological parameters to uncover different important aspects of proteins. Here, we have analyzed some of the topological parameters such as degree, strength, clustering coefficients, betweenness and closeness centrality of each of the twenty amino acids in a set of non-redundant proteins covering all classes and folds. The results show that the values of these topological parameters vary widely with different amino acids. Also, these values differ significantly with different length scales of proteins. Most of the hydrophobic residues along with Cys, Arg and His have larger contributions to the long range connectivities than short range. We have also studied whether the values of topological parameters have any significant dependency on the physico-chemical properties of the amino acids. While the clustering coefficients show a strong negative correlation with residual volumes, surface areas and number of atoms in the side chains of amino acids; the degrees, strengths and betweenness show positive correlations with the mentioned properties. All the topological parameters show high dependency on bulkiness and average area buried of the amino acid residues in all-range residue networks. The average degree shows higher dependency on hydrophobicity, while the average strength is more able to capture the essences of surface area, residual volume and number of atoms of amino acids. The hydrophobicities of the amino acids and their corresponding degrees show a higher positive correlation in long range networks (LRNs) than short range networks (SRNs). The closeness centrality shows high correlation with two hydrophobic scales and no correlation with surface area, residual volume or number of atoms in LRNs. We have further explored the relationship in hydrophobic, hydrophilic and charged residues separately. Interestingly, charged residues show a higher dependency on the number of atoms than their residual volumes and surface areas. Finally, we present a linear regression model relating the network parameters with physico-chemical properties of amino acids.     

Prediction of mucin-type <Emphasis Type="Italic">O</Emphasis>-glycosylation sites by a two-staged strategy

The mucin-type O-glycosylation of a protein is an important type of protein post-translational modification. This process is mediated by a family of UDP-GalNAc:polypeptide N-acetylgalactosaminyltransferases which transfer the N-acetylgalactosamine (GalNAc) to the serine or threonine residues with unknown specificity. In order to determine the glycosylation sites of a given protein, we present a two-staged prediction method here, which first determines whether a protein is a glycoprotein, and then determines the glycosylation sites of a protein that has been predicted to be glycosylated in the first stage. In the first stage, a protein is encoded by the protein families in PFAM, which is a collective annotated database of classified protein families; then it is predicted by a predictor trained by the training set. In the second stage, nonapeptides of the predicted mucin-type glycoproteins, with serine or threonine residues at their fifth sites, are represented by indices in AAIndex. Then, it is predicted whether the nonapeptides are attached by GalNAc by a predictor, which is constructed with features selected by feature selection methods [Maximum Relevance Minimum Redundancy (mRMR) method and Incremental Feature Selection method]. The prediction accuracy of the first stage is 94.9% validated by Leave-One-Out validation method; the prediction accuracy of the second stage is 99.4%. These results show that this method is valuable to study the mucin-type O-glycosylation. The analysis of the features used to construct the predictor of the second stage confirms the previously obtained results from other groups. The residues at position −1 and +3 have great impact on the prediction. Among other amino acid indices, the indices about alpha and turn propensities and indices about hydrophobicity of the residues in nonapeptide also influence the recognition of the GalNAc transferases. A web server is available at .     

Curcumin as a tool to assess the surface hydrophobicity of proteins

ABSTRACT

Curcumin is non-fluorescent in aqueous media; however, in the vicinity of hydrophobic surface it fluoresces. This property is used to assess the use of curcumin as a surface hydrophobic probe. The surface hydrophobicity of proteins was measured by calculating the binding affinity and surface hydrophobicity index value. Surface hydrophobicity of bovine serum albumin, β-lactoglobulin, soy lipoxygenase-1, ovalbumin, and lysozyme is in the following order: bovine serum albumin?>?β-lactoglobulin?>?soy lipoxygenase-1?>?ovalbumin?>?lysozyme. The binding affinities of curcumin decreased with the decrease in surface hydrophobicity of proteins. The orders of surface hydrophobicity index value, determined using curcumin, show similar trend with the reported values of standard probes, viz. cis-parinaric acid and 1-anilinonaphthalene-8-sulfonate. The surface hydrophobicity index value of proteins determined using curcumin decreased in the presence of urea, suggesting the possible use of curcumin as a probe to determine the surface hydrophobicity of proteins.     

Effects of ultrasound on the structural and emulsifying properties and interfacial properties of oxidized soybean protein aggregates

Oxidative attack leads to the oxidative aggregation and structural and functional feature weakening of soybean protein. We aimed to investigate the impact of ultrasonic treatment (UT) with different intensities on the structure, emulsifying features and interfacial features of oxidized soybean protein aggregates (OSPI). The results showed that oxidative treatment could disrupt the native soy protein (SPI) structure by promoting the formation of oxidized aggregates with β1-sheet structures through hydrophobic interactions. These changes led to a decrease in the solubility, emulsification ability and interfacial activity of soybean protein. After low-power ultrasound (100 W, 200 W) treatment, the relative contents of β1-sheets, β2-sheets, random coils, and disulfide bonds of the OSPI increased while the surface hydrophobicity, absolute ζ-potential value and free sulfhydryl content decreased. Moreover, protein aggregates with larger particle sizes and poor solubility were formed. The emulsions prepared using the OSPI showed bridging flocculation and decreased protein adsorption and interfacial tension. After applying medium-power ultrasound (300 W, 400 W, and 500 W) treatments, the OSPI solubility increased and particle size decreased. The α-helix and β-turn contents, surface hydrophobicity and absolute ζ-potential value increased, the structure unfolded, and the disulfide bond content decreased. These changes improved the emulsification activity and emulsion state of the OSPI and increased the protein adsorption capacity and interfacial tension of the emulsion. However, after a high-power ultrasound (600 W) treatment, the OSPI showed a tendency to reaggregate, which had a certain negative effect on the emulsification activity and interfacial activity. The results showed that UT at an appropriate power could depolymerize OSPI and improve the emulsification and interfacial activity of soybean protein.     

Hydrophobizing coatings for cultural heritage. A detailed study of resin/stone surface interaction

Conservation of historical buildings is an important issue and the environmental conditions seriously affect the monument’s stones. The protection of cultural heritage buildings and monuments by surface treatment with polymers is a common practice due to their ability to form a protective layer on the monument’s surface as well as to control the transport of different fluids from the surface to the monument’s interior. In this work, three different substrates were used: Carrara marble, Botticino limestone, and Angera stone. A commercially available Si-based resin (Alpha^®SI30) was used as protective agent to improve the hydrophobicity features of the different tested materials. The surface properties of the coating and the relative interaction with the adopted stones were studied using different techniques such as contact angle measurements, electron microscope coupled with an energy dispersive spectrometer, X-ray photoelectron spectroscopy, atomic force microscopy, and attenuated total reflection infrared spectroscopy.     

Libraries of 2β-(N-substituted piperazino)-5α-androstane-3α, 17β-diols: chemical synthesis and cytotoxic effects on human leukemia HL-60 cells and on normal lymphocytes

Libraries of steroid derivatives with two levels of molecular diversity were prepared to optimize the antiproliferative activity on leukemia HL-60 cells by first varying the amino acid (AA) at R¹ (libraries A, B, C, and D: with 45, 45, 20, and 20 members, respectively) and, subsequently, the capping group at R² (library E: 168 members). The screening of these aminosteroids revealed interesting structure–activity relationships. In library A, the compounds bearing a tetrahydroisoquinolone residue as the first element of diversity showed potent cytotoxicity, principally when isovaleric or cyclohexyl acetic acid was used as a capping group (>40% of cell growth inhibition at 1 μM). In library B, the phenylalanine (Phe) derivatives bearing a cyano group induced a higher growth inhibition than the other Phe derivatives. The screening of library C indicated the increase of hydrophobicity of proline (Pro) seems to preserve the cytotoxic effect achieved by the lead compound. However, the synthesis of structural Pro variants (library D) clearly shows weaker activities when compared to L-Pro building blocks. Finally, by incorporating some of the most active AA of libraries A–D in library E, we observed that the amide coupling functionality gave stronger cytotoxic activity compared to the corresponding sulfonamides or benzylamines. Six of the most active amide derivatives (E-37P, E-41P, E-42P, E-46P, E-48F, and E-12T) were selected and IC₅₀ determined on HL-60 cells as well as on normal human lymphocytes. Among this series of new anticancer agents, good to high selectivity indices (SI = IC₅₀ (lymphocytes)/IC₅₀ (HL-60 cells) = 5 - 55) were obtained.     

支持向量机复合核函数的高光谱显微成像木材树种分类

采用体视显微高光谱成像方法,构建木材树种分类识别模型。利用SOC710VP体视显微高光谱图像采集系统获取可见光/近红外（372.53～1 038.57 nm）波段内的木材高光谱图像。首先,采用ENVI软件提取木材样本感兴趣区域（ROI）的平均光谱,分别采用连续投影算法（SPA）和竞争性自适应重加权算法(CARS)对光谱数据进行降维。再利用支持向量机（SVM）分别建立木材样本采集波段和特征波长下的分类模型。然后,在空间维采用第一主成分图像,计算基于灰度共生矩阵（GLCM）的木材纹理特征。在0°,45°,90°和135°四个方向计算能量、熵、惯性矩、相关性等16个特征参数后输入SVM进行木材树种分类处理。最后,采用四个复合核函数SVM进行光谱维和空间维的特征融合及分类识别。20个树种的分类实验结果表明,CARS的特征波长选择效果和运行速度较好一些,采用普通SVM进行木材光谱维特征分类处理时,测试集分类准确率达到了92.166 7%。采用基于GLCM的木材空间维纹理特征时,采用普通SVM的测试集分类准确率是60.333 0%,具有较低的分类精度。在将光谱维和空间维纹理特征进行数据融合及分类处理时,采用复合核函数SVM分类具有更好的效果。采用第二个复合核函数的SVM分类精度最高,测试集分类正确率是94.166 7%,运行时间为0.254 7 s。另外,采用第一个和第三个复合核函数的SVM的测试集分类准确率分别是93.333 3%和92.610 0%,运行时间分别为0.180 0和0.260 2 s。可以看出,采用这3种复合核函数的SVM进行木材树种分类,分类精度都高于采用普通SVM的光谱维或者空间维的分类识别精度。因此,利用体视显微高光谱成像和复合核函数SVM可以提高木材树种分类精度,为木材树种快速分类提供了参考。     

厅堂声学计算机模型的应用(英)

此处所介绍的厅堂声学计算机模型计算了房间和多功能厅的声学响应。这个模型是以房厅的三维表示为基础的。每个墙面都赋予一个吸声系数,并且分成更小的单元。首先计算了单元间影响系数所组成的矩阵。对于给定的声源,可以计算每个单元收到的能量,并由此定出房厅内任一点的声级,这样又能够算出（ａ）随距离变化的衰减,（ｂ）在任一平面上的声照度,和（ｃ）任一点所收到声能的接收指向性．可以算出房厅内任一被选定点的回波图,作为接收器所在地接收指向性随时间的演变;这么一个特点使得有可能核对目视图象和声图象之间的可能不符。这个软件能够设法任意修改房间的形状,以最优化房间的声学特征．本文列举了一个厅堂声学的研究例,是关于沙特拉伯首都Ｒｉｙａｄｈ的 Ａｈｕｒａ主厅的。     

Effects of ultrasound on the thermal and structural characteristics of proteins in reconstituted whey protein concentrate

The sonication-induced changes in the structural and thermal properties of proteins in reconstituted whey protein concentrate (WPC) solutions were examined. Differential scanning calorimetry, UV-vis, fluorescence and circular dichroism spectroscopic techniques were used to determine the thermal properties of proteins, measure thiol groups and monitor changes to protein hydrophobicity and secondary structure, respectively. The enthalpy of denaturation decreased when WPC solutions were sonicated for up to 5 min. Prolonged sonication increased the enthalpy of denaturation due to protein aggregation. Sonication did not alter the thiol content but resulted in minor changes to the secondary structure and hydrophobicity of the protein. Overall, the sonication process had little effect on the structure of proteins in WPC solutions which is critical to preserving functional properties during the ultrasonic processing of whey protein based dairy products.