Macrocyclic peptides as regulators of protein-protein interactions

Protein-protein interactions are attractive but challenging targets for drug discovery. Recent technological progress and examples using macrocyclic peptides as protein interaction modulators are reviewed.     

Designing anti-Zika virus peptides derived from predicted human-Zika virus protein-protein interactions

The production of anti-Zika virus (ZIKV) therapeutics has become increasingly important as the propagation of the devastating virus continues largely unchecked. Notably, a causal relationship between ZIKV infection and neurodevelopmental abnormalities has been widely reported, yet a specific mechanism underlying impaired neurological development has not been identified. Here, we report on the design of several synthetic competitive inhibitory peptides against key pathogenic ZIKV proteins through the prediction of protein–protein interactions (PPIs). Often, PPIs between host and viral proteins are crucial for infection and pathogenesis, making them attractive targets for therapeutics. Using two complementary sequence-based PPI prediction tools, we first produced a comprehensive map of predicted human-ZIKV PPIs (involving 209 human protein candidates). We then designed several peptides intended to disrupt the corresponding host-pathogen interactions thereby acting as anti-ZIKV therapeutics. The data generated in this study constitute a foundational resource to aid in the multi-disciplinary effort to combat ZIKV infection, including the design of additional synthetic proteins.     

Building and analysis of protein-protein interactions related to diabetes mellitus using support vector machine,biomedical text mining and network analysis

In order to understand the molecular mechanism underlying any disease, knowledge about the interacting proteins in the disease pathway is essential. The number of revealed protein-protein interactions (PPI) is still very limited compared to the available protein sequences of different organisms. Experiment based high-throughput technologies though provide some data about these interactions, those are often fairly noisy. Computational techniques for predicting protein–protein interactions therefore assume significance. 1296 binary fingerprints that encode a combination of structural and geometric properties were developed using the crystallographic data of 15,000 protein complexes in the pdb server. In a case study, these fingerprints were created for proteins implicated in the Type 2 diabetes mellitus disease. The fingerprints were input into a SVM based model for discriminating disease proteins from non disease proteins yielding a classification accuracy of 78.2% (AUC value of 0.78) on an external data set composed of proteins retrieved via text mining of diabetes related literature. A PPI network was constructed and analysed to explore new disease targets. The integrated approach exemplified here has a potential for identifying disease related proteins, functional annotation and other proteomics studies.     

Real-time PCR detection of telomerase activity using specific molecular beacon probes

Telomerase is a potentially important biomarker and a prognostic indicator of cancer. Several techniques for assessing telomerase activity, including the telomeric repeat amplification protocol (TRAP) and its modified versions, have been developed. Of these methods, real-time quantitative TRAP (RTQ-TRAP) is considered the most promising. In this work, a novel RTQ-TRAP method is developed in which a telomeric repeats-specific molecular beacon is used. The use of the molecular beacon can improve the specificity of the RTQ-TRAP assay, making the method suitable for studying the overall processivity results and the turnover rate of telomerase. In addition, the real-time, closed-tube protocol used obviates the need for post-amplification procedures, reduces the risk of carryover contamination, and supports high throughput. Its performance in synthetic telomerase products and cell extracts suggests that the developed molecular beacon assay can further enhance the clinical utility of telomerase activity as a biomarker/indicator in cancer diagnosis and prognosis. The method also provides a novel approach to the specific detection of some particular gene sequences to which sequence-specific fluorogenic probes cannot be applied directly. Figure Real-time PCR detection of telomerase activity using specific molecular beacon probes Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Analysis and interpretation of data from real-time PCR trace detection methods using quantitation of GM soya as a model system

Recent years have seen an increased interest in DNA trace detection methods involved in many areas of bioanalytical research, such as quantitation of genetically modified (GM) ingredients in food products. There is little in the way of standardisation of data handling from these methods, and the data generated needs to be analysed appropriately if the results are to be interpreted correctly. This paper describes particular aspects of real-time PCR trace detection methods in order to increase the understanding of data generated using this bioanalytical technique. Using the specific example of GM soya detection and quantitation, it focuses on the production of calibration curves based on the mean and individual data values, the interpretation of correlation coefficients, regression techniques, and discusses suitable data analysis arising from simple and more complex experimental designs following transformation. By using the approaches outlined in this paper, more accurate analysis of data from real-time PCR and GM trace detection methods could be achieved.     

Nanostructured biochip for label-free and real-time optical detection of polymerase chain reaction

In this report, Au-coated nanostructured biochip with functionalized thiolated primers on its surface is developed for label-free and real-time optical detection of polymerase chain reaction (PCR). A PCR chamber of 150 μm in thickness containing Au-coated nanostructured substrate in the bottom layer was bordered with SU-8 100 walls. After immobilization of 5′-thiolated primers on the surface, simultaneous DNA amplification and detection were performed without any labeled molecules via the relative reflected intensity (RRI) of Au-coated nanostructured substrate. When human genomic DNA at several concentrations of 0.2, 0.5 and 1 ng μL⁻¹ was included in the initial DNA samples, the increases in the RRI peak values were clearly observed with the increasing PCR cycle numbers. We found that the starting point of the optical signal, which was divergent from the background in our PCR biochip, was around 3-4 cycles, much lower than that of the fluorescent real-time PCR analysis (around 23-25 cycles). Our proposed PCR device using Au-coated nanostructured substrate holds noteworthy promise for rapid, label-free and real-time DNA detection for point-of-care testing (POCT) applications.     

Exponentially modified Gaussian relevance to the distributions of translocation events in nanopore-based single molecule detection

Nanopore technique plays an important role in single molecule detection, which illuminates the properties of an individual molecule by analyzing the blockage durations and currents. However, the traditional exponential function is lack of efficiency to describe the distributions of blockage durations in nanopore experiments. Herein, we introduced an exponentially modified Gaussian （EMG） function to fit the duration histograms of both simulated events and experimental events. In comparison with the traditional exponential function, our results demonstrated that the EMG provides a better fit while covers the entire range of the distributions. In particular, the fitted parameters of EMG could be directly used to discriminate the sequence length of the oligonucleotides at single molecule level.     

Construction and analysis of a diabetic nephropathy related protein-protein interaction network reveals nine critical and functionally associated genes

Diabetic nephropathy (DN) is one of the common diabetic complications, but the mechanisms are still largely unknown. In this study, we constructed a DN related protein-protein interaction network (DNPPIN) on the basis of RNA-seq analysis of renal cortices of DN and normal mice, and the STRING database. We analyzed DNPPIN in detail revealing nine critical proteins which are central in DNPPIN, and contained in one network module which is functionally enriched in ribosome, nucleic acid binding and metabolic process. Overall, this study identified nine critical and functionally associated protein-coding genes concerning DN. These genes could be a starting point of future research towards the goal of elucidating the mechanisms of DN pathogenesis and progression.     

Analysis of protein-protein interactions with a multi-capillary electrophoresis instrument

Protein-protein interactions were analyzed by zone electrophoresis of premixed equilibrium mixtures of a fluorescence-labeled protein at a constant concentration and unlabeled protein at a variety of concentrations using a 96-CE instrument equipped with a LIF detector. The interactions between labeled-con A versus succinylated ovalbumin, labeled-trypsin versus four proteinaceous trypsin inhibitors and labeled-insulin versus seven anti-insulin monoclonal antibodies were analyzed using a dual buffer system, in which a 60 mM borate-Na buffer (pH 9.35) was used as electrophoresis buffer and 60 mM MOPS-Na (pH 7.35) containing 0.1% Tween 20 was used as a sample buffer. The dual buffer system allowed fast and reproducible analyses of interactions at a physiological pH using uncoated fused-silica capillaries. The change in the mobility moment, the first statistical moment of an electropherogram on the mobility axis (Shimura, K., Uchiyama, N., Enomoto, M., Matsumoto, H., Kasai, K., Anal. Chem. 2005, 77, 564-572), of the labeled proteins were analyzed as a function of the concentration of unlabeled proteins. The dissociation constants for seven antibodies ranging from sub nanomolar to micromolar was determined based on the results of one cycle of parallel electrophoresis runs, which completed in 30 min using 20 pmol (120 ng) of labeled insulin and 5 pmol (750 ng) each of the mAb.     

A novel approach for the detection of DNA using immobilized peptide nucleic acid (PNA) probes and signal enhancement by real-time immuno-polymerase chain reaction (RT-iPCR)

A new approach for the detection of DNA target molecules is described, using capture probes and subsequent signal enhancement by a uniform polymerase chain reaction (PCR). Peptide nucleic acid probes were immobilized in real-time PCR-compatible microtiter plates. After hybridization of biotinylated DNA targets, detection was performed by real-time immuno-PCR, a method formerly used for protein detection. We demonstrate the feasibility of this strategy for the qualitative detection of DNA oligonucleotides with a detection limit (LOD) of 6 attomol. Furthermore, the method was applied to PCR-amplified samples from genetically modified maize DNA (Mon810). A 483-bp DNA fragment was detected in mixture with 99.9% of noncomplementary DNA with a sensitivity down to the level of attomole. Figure       

Prediction of human-Streptococcus pneumoniae protein-protein interactions using logistic regression

Streptococcus pneumoniae is a major cause of mortality in children under five years old. In recent years, the emergence of antibiotic-resistant strains of S. pneumoniae increases the threat level of this pathogen. For that reason, the exploration of S. pneumoniae protein virulence factors should be considered in developing new drugs or vaccines, for instance by the analysis of host-pathogen protein-protein interactions (HP-PPIs). In this research, prediction of protein-protein interactions was performed with a logistic regression model with the number of protein domain occurrences as features. By utilizing HP-PPIs of three different pathogens as training data, the model achieved 57–77 % precision, 64–75 % recall, and 96–98 % specificity. Prediction of human-S. pneumoniae protein-protein interactions using the model yielded 5823 interactions involving thirty S. pneumoniae proteins and 324 human proteins. Pathway enrichment analysis showed that most of the pathways involved in the predicted interactions are immune system pathways. Network topology analysis revealed β-galactosidase (BgaA) as the most central among the S. pneumoniae proteins in the predicted HP-PPI networks, with a degree centrality of 1.0 and a betweenness centrality of 0.451853. Further experimental studies are required to validate the predicted interactions and examine their roles in S. pneumoniae infection.     

An inexpensive microslab gel DNA electrophoresis system with real-time fluorescence detection

In this paper, we describe the construction of a simple yet powerful gel electrophoresis apparatus that can be used to perform size-selective separations of DNA fragments in virtually any laboratory. This system employs a microslab gel format with a novel gel casting technique that eliminates the need for delicate combs to define sample loading wells. The compact size of the microslab gel format allows rapid separations to be performed at low voltages using submicroliter sample volumes. Real time fluorescence detection of the migrating DNA fragments is accomplished using an inexpensive digital microscope that directly connects to any PC with a USB interface. The microscope is readily adaptable for this application by replacing its white light source with a blue light-emitting diode (LED) and adding an appropriate emission filter. Both polyacrylamide and agarose gels can be used as separation matrices. Separation performance was characterized using standard dsDNA ladders, and correct sizing of a 191 bp PCR product was achieved in 15 min. The low cost and simplicity of this system makes it ideally suited for use in a variety of laboratory and educational settings.     

Effect of example weights on prediction of protein-protein interactions

Protein-protein interactions (PPIs) prediction is an important issue in biology. Recently many computational methods have been proposed to determine PPIs. However, there is no golden standard dataset for these methods now. Furthermore, there exists different quality among training examples and the quality is always ignored by the current methods. In the condition of low-quality examples, the system should tolerate the data noise. Example weighting strategy is used in this paper to build a robust system and solve the problem of data noise. Training examples are investigated and a new example selecting/using strategy is proposed. Training example weighting method based on confidence is proposed. Different weight setting strategies are discussed and the corresponding results are given in the experiment. A new model integrating example weighting strategy, attraction-repulsion (AR) weight model, is proposed. Experimental results on Saccharomyces cerevisiae demonstrate that the new model outperforms the original AR model in the ROC score measure by over 8%. Furthermore, the example weighting strategy is applied to another domain-based PPIs prediction method, maximum likelihood estimation (MLE) method, and the modified MLE method obtains better performance than the original MLE method. At same time, our examples weighting strategy can be applied to any other training example based PPIs prediction methods.     

Real-time two-dimensional wavelet compression and its application to real-time modeling of ion mobility data

Real-time data analysis is important in many applications. However, many chemometric algorithms have difficulty processing data in real-time. A novel real-time two-dimensional wavelet compression (WC²) has been developed to compress data as it is acquired from analytical instrumentation. The WC algorithm was enhanced so that data with an arbitrary number of points were compressed, and truncation or padding to a dyadic number was avoided. After compression, the noise level is reduced while useful chemical information is retained. A modified simple-to-use interactive self-modeling mixture analysis (SIMPLISMA) algorithm was applied to the wavelet-compressed data and the model was transformed back to the original representation while leaving the data compressed. The reduced size of the wavelet-compressed data furnished a faster implementation of SIMPLISMA that facilitates real-time acquisition.

This real-time WC²-SIMPLISMA algorithm was applied to the rapid identification of explosives by ion mobility spectrometry (IMS). SIMPLISMA resolved concentration profiles and component spectra were displayed simultaneously while the data was acquired from an ion mobility spectrometer with a LabVIEW virtual instrument (VI).     

活体pH实时检测研究进展

酸碱度异常即pH改变与机体的健康状况有密不可分的关系,活体实时pH检测不仅可以为临床诊疗提供支持信息,而且有助于一些疾病发病机理的研究.本文详细介绍了 pH的定义、pH检测的发展历史、活体实时pH生物传感器所需满足的条件,重点介绍了各类型活体实时pH生物传感器包括电化学传感器、荧光传感器、光纤传感器以及超声传感器的原理...     

Differential interference contrast microscopy for real-time dynamics and manipulation of single cells in microchannels

Nomarski differential interference contrast (DIC) microscopy was used for real-time dynamics of intact single cells in various microchannels for adaptation to microfluidic chip application. The cheek cell was chosen as a model, single cell and the dynamics was measured at the microchannels. The image resolution of single cell was shaper and more distinct in DIC than in conventional microscopy. The individual single living cells were also manipulated by both hydrodynamic and electrokinetic flow-driving forces at the microchannels. The DIC contrast was enhanced according to the order of round-, square-, and rectangle-type microchannels. The velocity of the single living cell was consistently increased with increasing electric field strength and pH. However, the velocity of cell was decreased with increasing run buffer concentration. The driving direction of the individual single cell was simply controlled by changing the polarity of the applied voltage and the electric field strength. The cells were consistently manipulated in the microchannel under the co-application of the low electric field of 2.44 V/cm, instead of the solo application of the hydrodynamic force.     

The electrochemical behavior of a system with a limited number of molecules

In this paper, based on Einstein relationship between diffusion and random walk, the electrochemical behavior of a system with a limited number of molecules was simulated and explored theoretically. The transition of the current vs time responses from discrete to continuous was clearly obtained as the number of redox molecules increased from 10 to 10⁶. By correlation analysis between the simulation results and the results of analytical expressions, a quantized extent parameter was proposed to investigate the underlying rules of these discrete signals, which looked stochastic. The results revealed that this parameter would be useful to describe such systems.     

Label-free detection of protein-protein interactions at the GaAs/water interface through surface infrared spectroscopy: discrimination between specific and nonspecific interactions by using secondary structure analysis

Here, we propose a label-free detection of protein-protein interactions that enables simultaneous qualitative analysis of target proteins by using Fourier transform infrared (FTIR) absorption spectroscopy in multiple internal reflection geometry (MIR-FTIR). Using this method, the target proteins were detected based on the peak height of the amide I and amide II bands, while discrimination of specific and nonspecific signals is made based on the secondary structure of the analytes, which is determined through second-derivative analysis of the amide I band. As a model system, an antigen peptide was immobilized on the surface of GaAs, which was transparent to mid-infrared light, and the interaction with its antibody was examined in aqueous media. We demonstrated that the binding of the antibody to the antigen immobilized on a GaAs surface selectively gave rise to beta-sheet amide I vibrations (1639 and 1690 cm-1), while no structurally related signals were induced by nonspecifically adsorbed proteins. The peak height of the beta-peak (1639 cm-1) in the amide I band linearly increased with the antiserum concentration as well as that of the amide II band. The detection limit (S/N = 3) was a 1:36 000 dilution for the amide I signal. In addition, through the use of surface-sensitive MIR-FTIR, the present sensor selectively detected the antigen-antibody interactions at the surfaces without being affected by the presence of bulk species, enabling rapid and wash-free detection. Our method provides not only rapid label-free detection of protein-protein interactions but a more accurate discrimination between specific and nonspecific interactions through the use of the secondary structure of the target proteins as a measure for the specific signals.     

Capillary electrophoresis‐based approaches for the study of affinity interactions combined with various sensitive and nontraditional detection techniques

Nearly all processes in living organisms are controlled and regulated by the synergy of many biomolecule interactions involving proteins, peptides, nucleic acids, nucleotides, saccharides, and small molecular weight ligands. There is growing interest in understanding them, not only for the purposes of interactomics as an essential part of system biology, but also in their further elucidation in disease pathology, diagnostics, and treatment. The necessity of detailed investigation of these interactions leads to the requirement of laboratory methods characterized by high efficiency and sensitivity. As a result, many instrumental approaches differing in their fundamental principles have been developed, including those based on capillary electrophoresis. Although capillary electrophoresis offers numerous advantages for such studies, it still has one serious limitation, its poor concentration sensitivity with the most commonly used detection method–ultraviolet‐visible spectrometry. However, coupling capillary electrophoresis with a more sensitive detector fulfils the above‐mentioned requirement. In this review, capillary electrophoresis combined with fluorescence, mass spectrometry, and several nontraditional detection techniques in affinity interaction studies are summarized and discussed, together with the possibility of conducting these measurements in microchip format.