Effect of ionic strength and mixing ratio on complex coacervation of soy protein isolate/Flammulina velutipes polysaccharide

Soy protein isolate(SPI)is a commercial protein with balanced amino acids,while the poor solubility impedes its use in traditional foods.To overcome the problem,the complex coacervation of SPI/Flammulina velutipes polysaccharide(FVP)were investigated.Initial results revealed that the suitable amounts of FVP contributed to reducing the turbidity of SPI solution.Under electrostatic interaction,the formation of SPI/FVP coacervates were spontaneous and went through a nucleation and growth process.Low salt concentration(C_(NaCl)=10,50 mmol/L)led to an increase in the critical pH values(pHc,pHφ1)while the critical pH values decreased when C_(NaCl)≥100 mmol/L.The concentration of NaCl ions increased the content ofα-helix.With the increase of FVP,the critical pH values decreased and the content ofβ-sheet increased through electrostatic interaction.At SPI/FVP ratio of 10:1 and 15:1,the complex coacervation of SPI/FVP were saturated,and the coacervates had the same storage modulus value.SPI/FVP coacervates exhibited solid-like properties and presented the strongest storage modulus at C_(NaCl)=50 mmol/L.The optimal pH,SPI/FVP ratio and NaCl concentration of complex coacervation were collected,and the coacervates demonstrated a valuable application potential to protect and deliver bioactives and food ingredients.

Involvement of T-complex protein 1-ring complex/chaperonin containing T-complex protein 1(TRiC/CCT) in retrograde axonal transport through tau phosphorylation

The cytosolic chaperonin T-complex protein 1-ring complex(TRiC)or chaperonin containing T-complex protein 1(CCT)is essential in de novo folding of approximately 10%of the eukaryotic,newly translated polypeptides as well as misfolded proteins.There is a close link between the TRiC/CCT cytosolic chaperonin and neurodegenerative diseases(Lopez et al.,2015).A lot of research suggests that CCT plays neuroprotective roles in neurodegenerative diseases including Huntington’s disease(Lopez et al.,2015).Either overexpression of a single or all eight subunits(CCT1-8)or treatment of the substrate-binding apical domain of yeast CCT1(ApiCCT1)prevented mutant Huntingtin aggregation and improved cellular and neuronal functions(Zhao et al.,2016).Importantly,our recent study has demonstrated that both CCT and ApiCCT could reduce mutant Huntingtin level and enhance both anterograde and retrograde axonal transport of brain-derived neurotrophic factor.These results led to restoration of the trophic status of striatal neurons from a bacterial artificial chromosome transgenic mouse model of Huntington’s disease(Zhao et al.,2016).Axonal transport is regulated by many factors including microtubule-associated protein tau,which promotes tubulin polymerization and stabilizes microtubules.Impaired interaction between tau and microtubules plays a vital role in the pathogenesis of multiple neurodegenerative diseases(Wang and Mandelkow,2016).Interestingly,tau phosphorylation is also observed in brains of several Huntington’s disease mouse models and Huntington’s disease patients(Gratuze et al.,2016).In a recent study,we explored if CCT subunit has any effect on axonal transport in a tau-dependent pathway(Chen et al.,2018b).We focused on the retrograde axonal transport of brain-derived neurotrophic factor,as neurotrophic factor-mediated signaling in the form of signaling endosome is essential in both the developing and the mature nervous system and dysregulation of trafficking of neurotrophic factors is tightly linked to disorders of the nervous system(Chen et al.,2018a).We found that the expression of a single CCT subunit(CCT5)significantly promoted retrograde axonal transport of brain-derived neurotrophic factor in primary cortical neurons.Mechanically,CCT regulated the level of cyclin-dependent kinase 5(CDK5)/p35/p25 and,subsequently contributed to CCT-induced tau phosphorylation,which induced detachment of tau from microtubules(Chen et al.,2018b)(Figure 1).

Discrete Differential Geometry and the Structural Study of Protein Complexes

This paper proposes a novel four-dimensional approach to the structural study of protein complexes. In the approach, the surface of a protein molecule is to be described using the intersection of a pair of four-dimensional triangular cones (with multiple top vertexes). As a mathematical toy model of protein complexes, we consider complexes of closed trajectories of n-simplices (n=2,3,4...), where the design problem of protein complexes corresponds to an extended version of the Hamiltonian cycle problem. The problem is to find “a set of” closed trajectories of n-simplices which fills the n-dimensional region defined by a given pair of n+1 -dimensional triangular cones. Here we give a solution to the extended Hamiltonian cycle problem in the case of n=2 using the discrete differential geometry of triangles (i.e., 2-simplices).

Antibody Therapies Targeting Complex Membrane Proteins

In analyses of protein families that may serve as drug targets,membrane-associated G-protein-coupled receptors(GPCRs)dominate,followed by ion channels,transporters,and—to a lesser extent—membrane-bound enzymes.However,various challenges put such membrane proteins among key groups of underutilized opportunities for the application of therapeutic antibodies.Antibodies hold the promise of exquisite specificity,as they are able to target even specific conformations of a particular membrane protein,as well as adaptability through engineering into various antibody formats.However,the ease of raising and isolating specific,effective antibodies targeting membrane proteins depends on many factors.In particular,the generation of specific antibodies is easier when targeting larger,simpler,extracellular domains with greater uniqueness of amino acid sequence.The rareness of such ideal conditions is illustrated by the limited number of approved biologics for targeting GPCRs and other complex membrane proteins.Challenges in developing antibodies to complex membrane proteins such as GPCRs,ion channels,transporters,and membrane-bound enzymes can be addressed by the design of the antigen,antibody-generation strategies,lead optimization technologies,and antibody modalities.A better understanding of the membrane proteins being targeted would facilitate mechanism-based drug discovery.This review describes the advantages and challenges of targeting complex membrane proteins with antibodies and discusses the preparation of membrane protein antigens and antibody generation,illustrated by select examples of success.

Review of multimer protein–protein interaction complex topology and structure prediction

Protein–protein interactions (PPI) are important for many biological processes. Theoretical understanding of the structurally determining factors of interaction sites will help to understand the underlying mechanism of protein–protein interactions. At the same time, understanding the complex structure of proteins helps to explore their function. And accurately predicting protein complexes from PPI networks helps us understand the relationship between proteins. In the past few decades, scholars have proposed many methods for predicting protein interactions and protein complex structures. In this review, we first briefly introduce the methods and servers for predicting protein interaction sites and interface residue pairs, and then introduce the protein complex structure prediction methods including template-based prediction and template-free prediction. Subsequently, this paper introduces the methods of predicting protein complexes from the PPI network and the method of predicting missing links in the PPI network. Finally, it briefly summarizes the application of machine/deep learning models in protein structure prediction and action site prediction.

A novel phycocyanin-Chla/c_2-protein complex isolated from chloroplasts of Chroomonas placoidea

Nine pigment-protein complexes were separated and characterized from intact Chroomonasplacoidea chloroplasts by IEF. The bands Ⅰ-Ⅵ with their isoelectric points （pI） values from 4 to 6 were phycocyanin components; bands Ⅷ and Ⅸ （pI = 2.8-3.6） were chlorophyll-protein complexes. According to absorption and fluorescence spectra, band VII was designated as a novel phycocyanin-Chla/c2-protein complex （pI ≈ 3.4-3.7）. These results indicated that phycocyanin is structurally and functionally coupled with chlorophyll-protein complex in C. placoidea, and probably interacted with electrostatic force in combination.

Influence of bioactive sulphated polysaccharide-protein complexes on hepatocarcinogenesis, angiogenesis and immunomodulatory activities

Objective:To explore the in vivo anticancer,anti-angiogenesis and immunomodulatory efficacies of the bioactive polysaccharide isolated from cold aqueous extract of Jania rubens(JCEM) and Pterocladia capillacea(PCEM) as well as hot aqueous extract of Enteromorpha intestinalis(EHEM) against hepatocellular carcinoma rat model(HCC) and to study their chemical composition.Methods:The sugars and amino acids composition of the bioactive polysaccharides of JCEM,PCEM and EHEM were determined using gas liquid chromatography and amino acid analyzer,respectively.These polysaccharide extracts(20 mg/kg b.wt.for 5 weeks) were assessed on hepatocarcinogenesis in rats and α-fetoprotein(AFP),carcinoembryonic antigen(CEA),glypican-3(GPC-3),hepatocyte growth factor(HGF) and vascular endothelial growth factor(VEGF) and Ig G levels were evaluated.Results:The GLC analysis of JCEM,PCEM and EHEM polysaccharide revealed the presence of 10,9 and10 sugars,in addition the amino acid analyser enable identification of 16,15 and 15 amino acids,respectively.These polysaccharide extracts of JCEM,PCEM and EHEM produced significant decrease in serum AFP,CEA,GPC-3,HGF and VEGF compared with untreated HCC group.JCEM,PCEM and EHEM had an immunostimulatory responses by increasing the IgG levels as compared by naive value(1.23,1.53 and 1.17 folds),respectively.The bioactive polysaccharides in HCC induced rats improved the humoral immune response.The photomicrographs of liver tissue sections of the groups of HCC treated with polysaccharide extracts of Jania rubens and Enteromorpha intestinalis showed intact histological structure.Moreover,fractions HE1,HE4,HE7 obtained from polysaccharide of EHEM showed moderate cytotoxic activity against Hep G2 in vitro with IC_(50) 73.1,42.6,76.2 μg/mL.However,fractions of PCEM and JCEM show no or weak cytotoxicity against Hep G2 in vitro where the cytotoxic activity of their crude polysaccharide extract proved synergetic effect.Conclusions:The pronounced antitumor activity of sulphated polysaccharide-protein complexes of JCEM and EHEM is due to direct cytotoxic activity,anti-hepatocarcinogensis,and anti-angiogenesis.In addition,JCEM,PCEM and EHEM had an immunostimulatory response and improved the humoral immune response in HCC induced rats.

Studies on the Phenylfluorone-Mo(Ⅵ) Complex as Interacting Mode Spectroscopic Probe of Protein in OP Microemulsion Medium

The application of phenylfluorone (PF)-Mo(VI) complex as a spectroscopic probe is studied. In the presence of OP microemulsion at pH 3.04, PF-Mo(Ⅵ) complex combines protein rapidly to form a stable compound and the absorbance at 527 nm is in proportion to the concentration of protein in the range 0-16 μg mL-1 for bovine serum albumin (BSA). OP microemuslion media is introduced into protein determination, it has increased markedly the sensitivity of the system. The molar absorption coefficient was 5.98×l06 L mol-1 cm-1 for BSA. The assay, with sensitivity, simplicity and tolerance to many foreign substances, is applied to the determination of protein in samples with satisfactory results. Moreover, the binding number of BSA with the complex, which is determined by molar ratio and slope ratio methods, is in good agreement.

Whey Protein-Carboxymethylcellulose Obtained by Complex Coacervation as an Ingredient in Probiotic Fermented Milk

Discharge of whey proteins is still a current practice by small cheese producers. The development of low-cost alternatives for recovery of these proteins is fundamental for small producers who cannot apply expensive techniques. The present study investigated the complex coacervation technique as a cheap technology to recover proteins from sweet whey using carboxymethylcellulose, and the coacervate used as an ingredient in the formulation of probiotic fermented milk. The nutritional properties of whey-carboxymethylcellulose coacervates (WP-CMC) were evaluated in trials with animals (rats) using casein as a reference. All these parameters—the coefficient of feed efficiency (CEA), protein digestibility-corrected amino acid score (PDCAAS), and net protein ratio (NPR), as well as weight gain—were determined to evaluate protein quality. A sensory acceptance test was applied to evaluate the sensory characteristics of the product. The complex coacervation technique recovered 86% of the protein from sweet whey. No significant (p > 0.05) differences were observed in the biological tests for both groups (WP-CMC and Casein groups) when NPR (4.98 to 5.04), digestibility (92.35 to 90.64), and CEA (0.40 to 0.42) were evaluated. Probiotic fermented milk beverage containing WP-CMC (0.78%) and guar gum (0.68%) presented good acceptability as determined by sensory evaluation. WP-CMC can be considered an ingredient with high nutritional and biological value that could be applied in probiotic fermented milk as an alternative to small producers to allocate the residual whey from cheese manufacture.

Prediction of Intrinsically Disordered Proteins with a Low Computational Complexity Method

The prediction of intrinsically disordered proteins is a hot research area in bio-information.Due to the high cost of experimental methods to evaluate disordered regions of protein sequences,it is becoming increasingly important to predict those regions through computational methods.In this paper,we developed a novel scheme by employing sequence complexity to calculate six features for each residue of a protein sequence,which includes the Shannon entropy,the topological entropy,the sample entropy and three amino acid preferences including Remark 465,Deleage/Roux,and Bfactor(2STD).Particularly,we introduced the sample entropy for calculating time series complexity by mapping the amino acid sequence to a time series of 0-9.To our knowledge,the sample entropy has not been previously used for predicting IDPs and hence is being used for the first time in our study.In addition,the scheme used a properly sized sliding window in every protein sequence which greatly improved the prediction performance.Finally,we used seven machine learning algorithms and tested with 10-fold cross-validation to get the results on the dataset R80 collected by Yang et al.and of the dataset DIS1556 from the Database of Protein Disorder(DisProt)(https://www.disprot.org)containing experimentally determined intrinsically disordered proteins(IDPs).The results showed that k-Nearest Neighbor was more appropriate and an overall prediction accuracy of 92%.Furthermore,our method just used six features and hence required lower computational complexity.

CHARACTERIZATION OF MOLECULAR MASS OF SIX WATER-SOLUBLE POLYSACCHARIDE -PROTEIN COMPLEXES FROM GANODERMA TSUGAE MYCELIUM

Six water-soluble polysaccharide-protein complexes coded as GM1, GM2, GM3, GM4, GM5 and GM6 wereisolated from the mycelium of Ganoderma tsugae by extracting with 0.2 mol/L phosphate buffer solution at 25, 40 and80℃, water at 120℃, 0.5 mol/L aqueous NaOH solution at 25 and 65℃, consecutively. Their chemical components wereanalyzed by using IR, GC, HPLC and ^(13)C-NMR, and some new results were obtained. The four samples GM1, GM2, GM3and GM4 are heteropolysaccharide-prote in complexes, in which, α- (1→3) linked D-glucose is the major monosaccharidewhile galactose, mannose and ribose are the secondary ones. GM5 and GM6 are β-(1→3)-D-glucan-protein complexes. Theprotein content increased from 32% to 69% with the progress of isolation. Weight-average molecu1ar mass M_w and theintrinsic viscosity [η] of the GM samples in 0.5 mol/L aqueous NaCl solution at 25℃ were measured systematically by laserlight scartering (LLS), size exclusion chromatography (SEC) combined with LLS, and viscometry. The M_w of GM1 to GM6are 35.5, 46.8, 58.9, 41.6, 3.3 and 22.0×10~4, respectively. The conformation and molecular mass of the two fractions of sample GM5 were characterized satisfactorily by SEC-LLS without further fractionation.

Enhancing the treatment effects of tumor cell purified autogenous heat shock protein 70-peptide complexes on HER-3-overexpressing breast cancer

Objective The aim of this study was to enhance the treatment effect of tumor purified autogenous heat shock protein 70-peptide complexes(HSP70-PCs)on HER-3-overexpressing breast cancer.Methods In this study,we first studied the expression of HER-3 in breast cancer tissues and its relationship with patient characteristics.We then purified HSP70-PCs from primary breast cancer cells with different HER-2 and HER-3 expression profiles and determined the cytotoxicity of autogenous dendritic cells(DCs)and CD8+T cells induced by these complexes.Third,recombinant human HSP70-HER-3 protein complexes were used to inhibit the autogenous HSP70-PCs purified from HER-3-overexpressing breast cancer cells,and the resulting immunological response was examined.Results The results show that HSP70-PCs can be combined with recombinant HSP70-HER-3 protein complexes to induce stronger immunological responses than autogenous HSP70-PCs alone and that these treatments induce autogenous CD8+T cell killing of HER-3-positive breast cancer cells.Conclusion These findings provide a new direction for HSP70-DC-based immunotherapy for patients with HER-3-overexpressing breast cancer.

Factors That Affect the Computational Prediction of Hot Spots in Protein-Protein Complexes

Protein-protein complexes play an important role in the physiology and the pathology of cellular functions, and therefore are attractive therapeutic targets. A small subset of residues known as “hot spots”, accounts for most of the protein-protein binding free energy. Computational methods play a critical role in identifying the hotspots on the proteinprotein interface. In this paper, we use a computational alanine scanning method with all-atom force fields for predicting hotspots for 313 mutations in 16 protein complexes of known structures. We studied the effect of force fields, solvation models, and conformational sampling on the hotspot predictions. We compared the calculated change in the protein-protein interaction energies upon mutation of the residues in and near the protein-protein interface, to the experimental change in free energies. The AMBER force field (FF) predicted 86% of the hotspots among the three commonly used FF for proteins, namely, AMBER FF, Charmm27 FF, and OPLS-2005 FF. However, AMBER FF also showed a high rate of false positives, while the Charmm27 FF yielded 74% correct predictions of the hotspot residues with low false positives. Van der Waals and hydrogen bonding energy show the largest energy contribution with a high rate of prediction accuracy, while the desolvation energy was found to contribute little to improve the hot spot prediction. Using a conformational ensemble including limited backbone movement instead of one static structure leads to better predicttion of hotpsots.

AG-GATCN:A novel method for predicting essential proteins

Essential proteins play an important role in disease diagnosis and drug development.Many methods have been devoted to the essential protein prediction by using some kinds of biological information.However,they either ignore the noise presented in the biological information itself or the noise generated during feature extraction.To overcome these problems,in this paper,we propose a novel method for predicting essential proteins called attention gate-graph attention network and temporal convolutional network(AG-GATCN).In AG-GATCN method,we use improved temporal convolutional network(TCN)to extract features from gene expression sequence.To address the noise in the gene expression sequence itself and the noise generated after the dilated causal convolution,we introduce attention mechanism and gating mechanism in TCN.In addition,we use graph attention network(GAT)to extract protein–protein interaction(PPI)network features,in which we construct the feature matrix by introducing node2vec technique and 7 centrality metrics,and to solve the GAT oversmoothing problem,we introduce gated tanh unit(GTU)in GAT.Finally,two types of features are integrated by us to predict essential proteins.Compared with the existing methods for predicting essential proteins,the experimental results show that AG-GATCN achieves better performance.

SSINCC: Simple separation of interacting nucleoprotein complex components

Protein-DNA binding assays have been used in a va-riety of applications from fundamental studies re-garding the binding process itself to serve as probes for the detection, quantification and separation of target analytes. Here we describe a novel method of analyzing and identifying intermolecular DNA interactions that allows for the simple separation of interacting nucleoprotein complex components (SSINCC), focusing specifically on DNA-DNA interactions using P1 plasmid active partition system nucleoprotein complexes as a model to demonstrate DNA sequence specificity and tolerance of composite factor complexity. Traditional and recent assays of protein-DNA interaction are summarized and compared with SSINC. Although SSINC is examined here employing P1 partition nucleoprotein complex as an example of DNA-DNA intermolecular association, universal applications of this methodology to nucleo-protein complex studies can be envisioned.

Effects of heat shock protein-antigen peptide complexes (HACs) in melanoma B16 cell line on transplanted tumor development in mice

目的 :建立黑色素瘤 B16细胞热休克蛋白 -抗原肽复合物 (HACs)的制备方法并测其抑瘤效应。方法 :应用 Sephacryl S- 2 0 0凝胶过滤制备 HAC粗提物 ,应用 SDS- PAGE纯化 HACs,并测其抑瘤效应。结果 :应用 SDS- PAGE纯化的 HAC6 0、 HAC75和 HAC97不同程度地降低肿瘤发生率 ,延迟肿瘤发生时间和减慢肿瘤生长速度。结论 :6 0 0 0 0～ 970 0 0

基于特征图网络和多种生物信息预测关键蛋白质的深度学习框架

针对生物实验识别关键蛋白质费时费力,使用计算方法预测关键蛋白质无法有效整合生物信息的问题,提出一个深度学习框架.首先利用网络拓扑结构、基因表达数据和GO(gene ontology)注释数据构建加权蛋白质相互作用网络;然后分别使用特征图网络和双向长短期记忆细胞从亚细胞定位数据、蛋白质复合物数据和基因表达数据中提取特征向量;最后将这些特征向量输入到任务学习层预测关键蛋白质.实验结果表明,相比于现有的计算方法,该方法预测性能更好.

光照条件变化对蓝隐藻色素蛋白复合物表达含量的影响

前期研究发现蓝隐藻(Chroomonas placoidea)藻蓝蛋白PC645存在未报道过的β亚基,但其受光照条件的影响及表达情况不明。实验比较了6组不同光照条件下培养的蓝隐藻对数生长期细胞的色素组成变化及PC645亚基的表达差异。发现光照增加对叶绿素a/c-蛋白复合物影响不明显,但有利于PC645的积累;且影响PC645中两种β亚基的相对表达量,而对α亚基含量影响很小。1级12 h和24 h时β_(2)亚基相对含量最高,较低或过高强度的光照都不利于β_(2)的表达。说明PC645在蓝隐藻光适应机制中可能担负调节作用,β_(2)亚基的存在不仅影响隐藻藻胆蛋白的聚合形式,也与藻细胞的光能传递功能可调性相关。实验结果将为分析新亚基的功能,阐明隐藻特异的光合系统结构与机理提供依据。