考马斯亮蓝显色液组分对蛋白质测定的影响

考马斯亮蓝（CBB）显色法测定蛋白质含量的主要缺点之一是线性关系差．通过研究显色液组分对线性关系的影响,发现显色液H⁺浓度是影响线性关系的主要因素,并提出了一个新的显色液配方来改善考马斯亮蓝蛋白质测定法的线性关系．     

Home-range analysis using radio-tracking data–a review of problems and techniques particularly as applied to the study of mammals

Ninety-three papers on home-range analysis using radio-tracking data were reviewed; these papers were found in a literature search of 18 of the major journals likely to include such papers, published in the 5-year period to the end of 1988. The review showed that even 25 years after the first radio-tracking studies, in the majority of papers there was still insufficient attention given to accurate and sufficient data collection, and to using appropriate and sophisticated analytical techniques to assess home-range size and configuration. This paper is designed to help people undertaking a radio-tracking study to avoid some of the most common pitfalls. It is based on some of the problems we have experienced studying several species of larger mammals. We use our collective experience to produce a guide on how to plan a radio-tracking study, to highlight some of the potential problems in designing the study and collecting the data, and to identify some of the difficulties that may be encountered during the analytical stages. The advantages and disadvantages of the most frequently used methods of home-range analysis are discussed and methods for determining the minimum number of radio-fixes and techniques for adjusting inadequate sample sizes are described, as are the problems that may be caused by autocorrelated data.     

Quantitative protein profiling using antibody arrays

Traditional approaches to microarrays rely on direct binding assays where the extent of hybridisation and the signal detected are a measure of the analyte concentration in the experimental sample. This approach, directly imported from the nucleic acid field, may fail if applied to antibody-antigen interactions due to the shortage of characterised antibodies, the significant heterogeneity of antibody affinities, their dependence on the extent of protein modification during labelling and the inherent antibody cross-reactivity. These problems can potentially limit the multiplexing capabilities of protein affinity assays and in many cases rule out quantitative protein profiling using antibody microarrays. A number of approaches aimed at achieving quantitative protein profiling in a multiplex format have been reported recently. Of those reported, the three most promising routes include signal amplification, multicolour detection and competitive displacement approaches to multiplex affinity assays. One in particular, competitive displacement, also overcomes the problems associated with quantitation of affinity interactions and provides the most generic approach to highly parallel affinity assays, including antibody arrays.     

A molecular dynamics approach for the generation of complete protein structures from limited coordinate data

Generation of full protein coordinates from limited information, e.g., the Cα coordinates, is an important step in protein homology modeling and structure determination, and molecular dynamics (MD) simulations may prove to be important in this task. We describe a new method, in which the protein backbone is built quickly in a rather crude way and then refined by minimization techniques. Subsequently, the side chains are positioned using extensive MD calculations. The method is tested on two proteins, and results compared to proteins constructed using two other MD-based methods. In the first method, we supplemented an existing backbone building method with a new procedure to add side chains. The second one largely consists of available methodology. The constructed proteins are compared to the corresponding X-ray structures, which became available during this study, and they are in good agreement (backbone RMS values of 0.5–0.7 Å, and all-atom RMS values of 1.5–1.9 Å). This comparative study indicates that extensive MD simulations are able, to some extent, to generate details of the native protein structure, and may contribute to the development of a standardized methodology to predict reliably (parts of) protein structures when only partial coordinate data are available. © 1994 John Wiley & Sons, Inc.     

Determining beta-sheet stability by Fourier transform infrared difference spectra

We describe here a new method for determining the conformational stability of antiparallel beta-sheets. Due to coupling between the transition dipoles, beta-sheet conformations typically exhibit a characteristic high-frequency amide I component centered at approximately 1680 cm(-1). Using one beta-sheet protein and two small beta-hairpins, we demonstrate that this high-frequency component, which is fairly narrow (approximately 8-10 cm(-1)), can be quantitatively resolved and used in thermal stability determination. Compared with the commonly used CD and fluorescence techniques, this ir method offers advantages. Since the area of this high-frequency component is only proportional to the folded population, it eliminates the need for a priori information of the folded and unfolded baselines encountered in other methods. Thus, it is applicable to a variety of beta-sheet systems.     

Determination of protein oligomeric structure from small‐angle X‐ray scattering

Small‐angle X‐ray scattering (SAXS) is useful for determining the oligomeric states and quaternary structures of proteins in solution. The average molecular mass in solution can be calculated directly from a single SAXS curve collected on an arbitrary scale from a sample of unknown protein concentration without the need for beamline calibration or protein standards. The quaternary structure in solution can be deduced by comparing the experimental SAXS curve to theoretical curves calculated from proposed models of the oligomer. This approach is especially robust when the crystal structure of the target protein is known, and the candidate oligomer models are derived from the crystal lattice. When SAXS data are obtained at multiple protein concentrations, this analysis can provide insight into dynamic self‐association equilibria. Herein, we summarize the computational methods that are used to determine protein molecular mass and quaternary structure from SAXS data. These methods are organized into a workflow and demonstrated with four case studies using experimental SAXS data from the published literature.     

A short history,principles, and types of ELISA,and our laboratory experience with peptide/protein analyses using ELISA

Playing a critical role in the metabolic homeostasis of living systems, the circulating concentrations of peptides/proteins are influenced by a variety of patho-physiological events. These peptide/protein concentrations in biological fluids are measured using various methods, the most common of which is enzymatic immunoassay EIA/ELISA and which guide the clinicians in diagnosing and monitoring diseases that inflict biological systems. All the techniques where enzymes are employed to show antigen–antibody reactions are generally referred to as enzymatic immunoassay EIA/ELISA method. Since the basic principles of EIA and ELISA are the same. The main objective of this review is to present an overview of the historical journey that had led to the invention of EIA/ELISA, an indispensible method for medical and research laboratories, types of ELISA developed after its invention [direct (the first ELISA method invented), indirect, sandwich and competitive methods], problems encountered during peptide/protein analyses (pre-analytical, analytical and post-analytical), rules to be followed to prevent these problems, and our laboratory experience of more than 15 years.     

蛋白质晶体的优化生长

蛋白质晶体的优化生长是获得高质量蛋白质晶体, 进而得到高精度晶体结构的有效途径.针对不同的晶体生长方法,已尝试了不同的优化手段,这对改善某些蛋白质晶体的质量显示了明显的成效.然而,鉴于蛋白质晶体生长的多样性与复杂性,这些方面均未发展成为实用的技术.文章综述了这类研究进展,分析了各手段的利弊,并指出了应着重解决的问题.     

In-cell protein NMR and protein leakage

In-cell nuclear magnetic resonance spectroscopy is a tool for studying proteins under physiologically relevant conditions. In some instances, however, protein signals from leaked protein are observed in the liquid surrounding the cells. Here, we examine the expression of four proteins in Escherichia coli. We describe the controls that should be used for in-cell NMR experiments and show that leakage is likely when the protein being studied exceeds ～20% of the total cellular protein.     

Knowledge-based computational intelligence development for predicting protein secondary structures from sequences

In the postgenomic age, with the avalanche of protein sequences generated and relatively slow progress in determining their structures by experiments, it is important to develop automated methods to predict the structure of a protein from its sequence. The membrane proteins are a special group in the protein family that accounts for approximately 30% of all proteins; however, solved membrane protein structures only represent less than 1% of known protein structures to date. Although a great success has been achieved for developing computational intelligence techniques to predict secondary structures in both globular and membrane proteins, there is still much challenging work in this regard. In this review article, we firstly summarize the recent progress of automation methodology development in predicting protein secondary structures, especially in membrane proteins; we will then give some future directions in this research field.     

ABRF-PRG07: Advanced Quantitative Proteomics Study

A major challenge for core facilities is determining quantitative protein differences across complex biological samples. Although there are numerous techniques in the literature for relative and absolute protein quantification, the majority is nonroutine and can be challenging to carry out effectively. There are few studies comparing these technologies in terms of their reproducibility, accuracy, and precision, and no studies to date deal with performance across multiple laboratories with varied levels of expertise. Here, we describe an Association of Biomolecular Resource Facilities (ABRF) Proteomics Research Group (PRG) study based on samples composed of a complex protein mixture into which 12 known proteins were added at varying but defined ratios. All of the proteins were present at the same concentration in each of three tubes that were provided. The primary goal of this study was to allow each laboratory to evaluate its capabilities and approaches with regard to: detection and identification of proteins spiked into samples that also contain complex mixtures of background proteins and determination of relative quantities of the spiked proteins. The results returned by 43 participants were compiled by the PRG, which also collected information about the strategies used to assess overall performance and as an aid to development of optimized protocols for the methodologies used. The most accurate results were generally reported by the most experienced laboratories. Among laboratories that used the same technique, values that were closer to the expected ratio were obtained by more experienced groups.     

Refinement of protein structure homology models via long, all-atom molecular dynamics simulations

Accurate computational prediction of protein structure represents a longstanding challenge in molecular biology and structure-based drug design. Although homology modeling techniques are widely used to produce low-resolution models, refining these models to high resolution has proven difficult. With long enough simulations and sufficiently accurate force fields, molecular dynamics (MD) simulations should in principle allow such refinement, but efforts to refine homology models using MD have for the most part yielded disappointing results. It has thus far been unclear whether MD-based refinement is limited primarily by accessible simulation timescales, force field accuracy, or both. Here, we examine MD as a technique for homology model refinement using all-atom simulations, each at least 100 μs long-more than 100 times longer than previous refinement simulations-and a physics-based force field that was recently shown to successfully fold a structurally diverse set of fast-folding proteins. In MD simulations of 24 proteins chosen from the refinement category of recent Critical Assessment of Structure Prediction (CASP) experiments, we find that in most cases, simulations initiated from homology models drift away from the native structure. Comparison with simulations initiated from the native structure suggests that force field accuracy is the primary factor limiting MD-based refinement. This problem can be mitigated to some extent by restricting sampling to the neighborhood of the initial model, leading to structural improvement that, while limited, is roughly comparable to the leading alternative methods.     

A Comparison of Protein Quantitation Assays for Biopharmaceutical Applications

Dye-based protein determination assays are widely used to estimate protein concentration, however various reports suggest that the response is dependent on the composition and sequence of the protein, limiting confidence in the resulting concentration estimates. In this study a diverse set of model proteins representing various sizes of protein and covalent modifications, some typical of biopharmaceuticals have been used to assess the utility of dye-based protein concentration assays. The protein concentration assays (Bicinchoninic acid (BCA), Bradford, 3-(4-carboxybenzoyl)quinoline-2-carboxaldehyde (CBQCA), DC, Fluorescamine and Quant-i) were compared to the 'gold standard' assay, quantitative amino acid analysis (AAA). The assays that displayed the lowest variability between proteins, BCA and DC, also generated improved estimates when BSA was used as a standard, when compared to AAA derived concentrations. Assays read out by absorbance tended to display enhanced robustness and repeatability, whereas the fluorescence based assays had wider quantitation ranges and lower limits of detection. Protein modification, in the form of glycosylation and PEGylation, and the addition of excipients, were found to affect the estimation of protein concentration for some of the assays when compared to the unmodified protein. We discuss the suitability and limitations of the selected assays for the estimation of protein concentration in biopharmaceutical applications.     

Detection and determination of antimalarial drugs and their metabolites in body fluids

This review of methods for determining antimalarial drugs in biological fluids has focused on the various analytical techniques for the assay of chloroquine, quinine, amodiaquine, mefloquine, proguanil, pyrimethamine, sulphadoxine, primaquine and some of their metabolites. The methods for determining antimalarials and their metabolites in biological samples have changed rapidly during the last eight to ten years with the increased use of chromatographic techniques. Chloroquine is still the most used antimalarial drug, and various methods of different complexity exist for the determination of chloroquine and its metabolites in biological fluids. The pharmacokinetics of chloroquine and other antimalarials have been updated using these new methods.The various analytical techniques have been discussed, from simple colorimetric methods of intermediate selectivity and sensitivity to highly sophisticated, selective and sensitive chromatographic methods applied in a modern analytical laboratory. Knowledge concerning the method for a particular study is determined by the type of application and the facilities, equipment and personnel available. Often is it useful to apply various methods when conducting a clinical study in malaria-endemic areas. Field-adapted methods for the analysis of urine samples can be applied at the study site for screening, and corresponding blood samples can be preserved for subsequent analysis in the laboratory. Selecting samples for laboratory analysis is based on clinical, parasitological and field-assay data. The wide array of methods available for chloroquine permit carefully tailored approaches to acquire the necessary analytical information in clinical field studied concerning the use of this drug. The development of additional field-adapted and field-interfaced methods for other commonly used antimalarials will provide similar flexibility in field studies of these drugs.     

Using linear algebra for protein structural comparison and classification

In this article, we describe a novel methodology to extract semantic characteristics from protein structures using linear algebra in order to compose structural signature vectors which may be used efficiently to compare and classify protein structures into fold families. These signatures are built from the pattern of hydrophobic intrachain interactions using Singular Value Decomposition (SVD) and Latent Semantic Indexing (LSI) techniques. Considering proteins as documents and contacts as terms, we have built a retrieval system which is able to find conserved contacts in samples of myoglobin fold family and to retrieve these proteins among proteins of varied folds with precision of up to 80%. The classifier is a web tool available at our laboratory website. Users can search for similar chains from a specific PDB, view and compare their contact maps and browse their structures using a JMol plug-in.     

Using codon optimization, chaperone co-expression, and rational mutagenesis for production and NMR assignments of human eIF2α

Producing a well behaved sample at high concentration is one of the main hurdles when starting a new project on an interesting protein. Especially when one attempts to overexpress a eukaryotic protein in bacteria, some difficulties are encountered, such as low expression level, low solubility, or even lack of folded structure. Overexpression in prokaryotic systems is highly desirable for cost-effective production of different isotope-labeled samples needed for NMR studies. Here we describe generally applicable methods for obtaining highly concentrated protein samples efficiently. This approach was developed as we tried to produce a NMR-suitable sample of the 35 kDa human translation initiation factor eIF2 alpha, a protein that expresses poorly in E. coli and has very low solubility. First, an E. coli codon-optimized gene was synthesized on a thermal cycler, which increased the expression level by a factor of two. Second, we used co-expression of bacterial chaperone proteins, which largely increased the fraction of correctly folded protein found in the soluble phase. Third, we used rational mutagenesis guided by both the sequence alignment among homologues and the homology of one domain to a known fold for improving solubility and stability of the target protein by tenfold. Combining all these methods made it possible to produce from a one-liter preparation a 0.5 mM sample of human eIF2 alpha that showed well-resolved NMR spectra and enabled nearly complete assignment of the protein. These methods may be generally useful for studies of other eukaryotic proteins that are otherwise difficult to express and exhibit poor solubility.     

Prediction of protein binding regions

Identifying protein binding sites provides important clues to the function of a protein. Experimental methods to identify the binding sites such as determining the crystal structures of protein complexes are extremely laborious and expensive. Here, we present a computational technique called spatial aggregation propensity (SAP) based on molecular simulations to predict protein binding sites. We apply this technique to two model proteins, an IgG1 antibody and epidermal growth factor receptor (EGFR) and demonstrate that SAP predicts protein binding regions with very good accuracy. In the case of the IgG1 antibody, SAP accurately predicts binding regions with the Fc-receptor, protein-A, and protein-G. For EGFR, SAP accurately predicts binding regions with EGF, TGFα, and with another EGFR. The resolution of SAP is varied to obtain a detailed picture of these binding sites. We also show that some of these binding sites overlap with protein self-aggregation prone regions. We demonstrate how SAP analysis can be used to engineer the protein to remove unfavorable aggregation prone regions without disturbing protein binding regions. The SAP technique could be also used to predict the yet unknown binding sites of numerous proteins, thereby providing clues to their function.