Improved prediction of critical residues for protein function based on network and phylogenetic analyses

Background  

Phylogenetic approaches are commonly used to predict which amino acid residues are critical to the function of a given protein. However, such approaches display inherent limitations, such as the requirement for identification of multiple homologues of the protein under consideration. Therefore, complementary or alternative approaches for the prediction of critical residues would be desirable. Network analyses have been used in the modelling of many complex biological systems, but only very recently have they been used to predict critical residues from a protein's three-dimensional structure. Here we compare a couple of phylogenetic approaches to several different network-based methods for the prediction of critical residues, and show that a combination of one phylogenetic method and one network-based method is superior to other methods previously employed.     

A method for detecting hydrophobic patches on protein surfaces

A method for the detection of hydrophobic patches on the surfaces of protein tertiary structures is presented. It delineates explicit contiguous pieces of surface of arbitrary size and shape that consist solely of carbon and sulphur atoms using a dot representation of the solvent-accessible surface. The technique is also useful in detecting surface segments with other characteristics, such as polar patches. Its potential as a tool in the study of protein-protein interactions and substrate recognition is demonstrated by applying the method to myoglobin, Leu/Ile/Val-binding protein, lipase, lysozyme, azurin, triose phosphate isomerase, carbonic anhydrase, and phosphoglycerate kinase. Only the largest patches, having sizes exceeding random expectation, are deemed meaningful. In addition to well-known hydrophobic patches on these proteins, a number of other patches are found, and their significance is discussed. The method is simple, fast, and robust. The program text is obtainable by anonymous ftp. © 1996 Wiley-Liss, Inc.     

A simple method for detecting protein antigens in flour.

Wheat, barley, rye or oat flour was dissolved in 0.2N NaOH using magnetic stirring followed by sonication. The ensuing clear solutions contained 95% of protein in the dry matter. Aliquots were electrophoresed on 12% polyacrylamide gels which were either stained with Coomassie brilliant blue or Western-blotted on nitrocellulose membrane. Incubation of the latter with serum from persons sensitized to flours allowed the detection of antigenic flour protein classes. It seems that many antigens are present in common kitchen flour.     

Efficient identification of critical residues based only on protein structure by network analysis

Despite the increasing number of published protein structures, and the fact that each protein's function relies on its three-dimensional structure, there is limited access to automatic programs used for the identification of critical residues from the protein structure, compared with those based on protein sequence. Here we present a new algorithm based on network analysis applied exclusively on protein structures to identify critical residues. Our results show that this method identifies critical residues for protein function with high reliability and improves automatic sequence-based approaches and previous network-based approaches. The reliability of the method depends on the conformational diversity screened for the protein of interest. We have designed a web site to give access to this software at http://bis.ifc.unam.mx/jamming/. In summary, a new method is presented that relates critical residues for protein function with the most traversed residues in networks derived from protein structures. A unique feature of the method is the inclusion of the conformational diversity of proteins in the prediction, thus reproducing a basic feature of the structure/function relationship of proteins.     

Identification of residues in beta-lactamase critical for binding beta-lactamase inhibitory protein

beta-Lactamase inhibitory protein (BLIP) is a potent inhibitor of several beta-lactamases including TEM-1 beta-lactamase (Ki = 0.1 nM). The co-crystal structure of TEM-1 beta-lactamase and BLIP has been solved, revealing the contact residues involved in the interface between the enzyme and inhibitor. To determine which residues in TEM-1 beta-lactamase are critical for binding BLIP, the method of monovalent phage display was employed. Random mutants of TEM-1 beta-lactamase in the 99-114 loop-helix and 235-240 B3 beta-strand regions were displayed as fusion proteins on the surface of the M13 bacteriophage. Functional mutants were selected based on the ability to bind BLIP. After three rounds of enrichment, the sequences of a collection of functional beta-lactamase mutants revealed a consensus sequence for the binding of BLIP. Seven loop-helix residues including Asp-101, Leu-102, Val-103, Ser-106, Pro-107, Thr-109, and His-112 and three B3 beta-strand residues including Ser-235, Gly-236, and Gly-238 were found to be critical for tight binding of BLIP. In addition, the selected beta-lactamase mutants A113L/T114R and E240K were found to increase binding of BLIP by over 6- and 11-fold, respectively. Combining these substitutions resulted in 550-fold tighter binding between the enzyme and BLIP with a Ki of 0.40 pM. These results reveal that the binding between TEM-1 beta-lactamase and BLIP can be improved and that there are a large number of sequences consistent with tight binding between BLIP and beta-lactamase.     

A multi-network clustering method for detecting protein complexes from multiple heterogeneous networks

Background

The accurate identification of protein complexes is important for the understanding of cellular organization. Up to now, computational methods for protein complex detection are mostly focus on mining clusters from protein-protein interaction (PPI) networks. However, PPI data collected by high-throughput experimental techniques are known to be quite noisy. It is hard to achieve reliable prediction results by simply applying computational methods on PPI data. Behind protein interactions, there are protein domains that interact with each other. Therefore, based on domain-protein associations, the joint analysis of PPIs and domain-domain interactions (DDI) has the potential to obtain better performance in protein complex detection. As traditional computational methods are designed to detect protein complexes from a single PPI network, it is necessary to design a new algorithm that could effectively utilize the information inherent in multiple heterogeneous networks.

Results

In this paper, we introduce a novel multi-network clustering algorithm to detect protein complexes from multiple heterogeneous networks. Unlike existing protein complex identification algorithms that focus on the analysis of a single PPI network, our model can jointly exploit the information inherent in PPI and DDI data to achieve more reliable prediction results. Extensive experiment results on real-world data sets demonstrate that our method can predict protein complexes more accurately than other state-of-the-art protein complex identification algorithms.

Conclusions

In this work, we demonstrate that the joint analysis of PPI network and DDI network can help to improve the accuracy of protein complex detection.

     

A novel strategy for defining critical amino acid residues involved in protein/glycosaminoglycan interactions

The binding of proteins to glycosaminoglycans (GAGs) is the prerequisite for a large number of cellular processes and regulatory events and is associated to many pathologies. However, progress in the understanding of these mechanisms has been hampered by the lack of simple and comprehensive analytical tools for the identification of the structural attributes involved in protein/saccharide interaction. Characterization of GAG binding motifs on proteins has so far relied on site-directed mutagenesis studies, protein sequence mapping using synthetic peptides, molecular modeling, or structural analysis. Here, we report the development of a novel approach for identifying protein residues involved in the binding to heparin, the archetypal member of the GAG family. This method, which uses native proteins, is based on the formation of cross-linked complexes of the protein of interest with heparin beads, the proteolytic digestion of these complexes, and the subsequent identification of the heparin binding containing peptides by N terminus sequencing. Analysis of the CC chemokine regulated on activation, normal T-cell expressed, and secreted (RANTES), the envelope glycoprotein gC from pseudorabies virus and the laminin-5 alpha 3LG4/5 domain validated the techniques and provided novel information on the heparin binding motifs present within these proteins. Our results highlighted this method as a fast and valuable alternative to existing approaches. Application of this technique should greatly contribute to facilitate the structural study of protein/GAG interactions and the understanding of their biological functions.     

Charged residues at protein interaction interfaces: unexpected conservation and orchestrated divergence

Protein-protein interactions play an essential role in the functioning of cell. The importance of charged residues and their diverse role in protein-protein interactions have been well studied using experimental and computational methods. Often, charged residues located in protein interaction interfaces are conserved across the families of homologous proteins and protein complexes. However, on a large scale, it has been recently shown that charged residues are significantly less conserved than other residue types in protein interaction interfaces. The goal of this work is to understand the role of charged residues in the protein interaction interfaces through their conservation patterns. Here, we propose a simple approach where the structural conservation of the charged residue pairs is analyzed among the pairs of homologous binary complexes. Specifically, we determine a large set of homologous interactions using an interaction interface similarity measure and catalog the basic types of conservation patterns among the charged residue pairs. We find an unexpected conservation pattern, which we call the correlated reappearance, occurring among the pairs of homologous interfaces more frequently than the fully conserved pairs of charged residues. Furthermore, the analysis of the conservation patterns across different superkingdoms as well as structural classes of proteins has revealed that the correlated reappearance of charged residues is by far the most prevalent conservation pattern, often occurring more frequently than the unconserved charged residues. We discuss a possible role that the new conservation pattern may play in the long-range electrostatic steering effect.     

A new method for quantifying residue conservation and its applications to the protein folding nucleus

The conservation of residues in columns of a multiple sequence alignment (MSA) reflects the importance of these residues for maintaining the structure and function of a protein. To date, many scores have been suggested for quantifying residue conservation, but none has achieved the full rigor both in biology and statistics. In this paper, we present a new approach for measuring the evolutionary conservation at aligned positions. Our conservation measure is related to the logarithmic probabilities for aligned positions, and combines the physicochemical properties and the frequencies of amino acids. Such a measure is both biologically and statistically meaningful. For testing the relationship between an amino acid's evolutionary conservation and its role in the Phi-value defined protein folding kinetics, our results indicate that the folding nucleus residues may not be significantly more conserved than other residues by using the biological-relevance weighted statistical scoring method suggested in this paper as an alternative to entropy-based procedures.     

A continuum method for determining membrane protein insertion energies and the problem of charged residues

Continuum electrostatic approaches have been extremely successful at describing the charged nature of soluble proteins and how they interact with binding partners. However, it is unclear whether continuum methods can be used to quantitatively understand the energetics of membrane protein insertion and stability. Recent translation experiments suggest that the energy required to insert charged peptides into membranes is much smaller than predicted by present continuum theories. Atomistic simulations have pointed to bilayer inhomogeneity and membrane deformation around buried charged groups as two critical features that are neglected in simpler models. Here, we develop a fully continuum method that circumvents both of these shortcomings by using elasticity theory to determine the shape of the deformed membrane and then subsequently uses this shape to carry out continuum electrostatics calculations. Our method does an excellent job of quantitatively matching results from detailed molecular dynamics simulations at a tiny fraction of the computational cost. We expect that this method will be ideal for studying large membrane protein complexes.     

A modification of the Lowry method for detecting protein in media containing lignocellulosic substrates

Summary Clostridium thermocellum culture media containing crude cellulosic substrates, prepared by the steam-explosion of wood or straw, were found to interfere strongly with the Lowry method of protein determination. Investigations into the mode of interferences demonstrated that either the intercept (blank value) and/or the slope (intensity of color development) were affected. The efficiencies of precipitation procedures using the trichloroacetic acid method and the deoxycholate-trichloroacetic acid method were compared.     

基于微纳技术的循环肿瘤细胞免疫检测新方法北大核心CSCD

本研究旨在探索一种高灵敏度、高特异性检测循环肿瘤细胞(circulating tumor cells, CTCs)的免疫检测新方法,以尽早地检出结直肠癌,提高该疾病的检出率。首先制备含有线性微柱结构的微芯片,通过在其表面孵育氧化石墨烯-链霉亲和素(graphite oxide-streptavidin, GO-SA)及偶联广谱一抗(antibody1, Ab₁),即上皮特异性黏附分子(epithelial cell adhesion molecule, EpCAM)单克隆抗体以捕获CTCs。运用羧基化多壁碳纳米管(carboxylated multi-walled carbon nanotubes, MWCNTs-COOH)与结直肠癌相关抗体,即特异性二抗(antibody 2, Ab₂)偶联制备抗体复合物。在捕获CTCs的微芯片上孵育该抗体复合物,构建以Ab₁-CTCs-Ab₂为主体的超级三明治结构,通过电化学工作站检测并验证其高灵敏度和高特异性。结果发现,在免疫传感器的构建中结合应用微纳技术,极大地提高了CTCs的检测灵敏度和特异性。本研究验证了该免疫传感器应用于临床血样检测的可行性,并通过该免疫传感器对结直肠癌患者外周血中CTCs进行检测和计数。结果表明,基于微纳技术的超级三明治式免疫传感器为CTCs的检测提供了新的途径,对临床工作中的疾病诊断及病情实时监控方面均具有潜在的应用价值。     

A convenient method for detecting sulphate-reducing bacteria

Sulphate-reducing bacterial cells, after addition of sodium hydroxide, showed a pink colour under a visible light microscope. This phenomenon is suggested as a test for sulphate-reducing bacteria.     

A microchemical method for detecting antifungal substances

Summary A microchemical method for detecting inhibitors of fungal grwoth has been devised. The procedure involves the determination of mycelium production by use of acidified potassium dichromate. The method is rapid, reproducible and is sensitive to the antifungal antibiotic, actidione, in concentrations of less than 0.10 g./ml. when Fusarium oxysporum f. cubense is used as the test organism.Agronomy Paper No. 450. This work was supported in part by a grant from the United Fruit Company, Boston, Massachusetts.     

A simple method for detecting heparinase-producing bacteria

A simple method for detecting heparinase-producing bacteria is described. The method is based on the metachromatic reaction between heparin and toluidine blue. Though developed primarily for Bacteroides spp., the method should find application in the detection of other aerobic and anaerobic heparinase-producing bacteria, without the need for large amounts of media and expensive spectrophotometric equipment.     

A new method for detecting neural interconnectivity

We propose a class of counting process models for analyzing firing times of an ensemble of neurons. We allow the counting process intensities to be unspecified, unknown functions of the times passed since the most recent firings. Under this assumption we derive a class of statistics with their respective thresholds as well as graphical methods for detecting neural connectivity. We introduce a model under which detection is shown to be certain for long series of observations. We suggest ways to classify interactions as inhibition or excitation and to estimate their strengths. The power of the proposed methods is compared by simulating observations from artificial networks. By analyzing empirically obtained series we obtain results which are consistent with those obtained from cross-correlation-based methods but in addition obtain new insights on further aspects of the interactions. Received: 7 February 1996 / Accepted in revised form: 5 March 1997     

A rapid method for detecting fungi-toxic substances

A simple and rapid technique is reported for the preliminary screening of fungi-toxic extracts/samples by direct spotting onto silica gel plates and subsequent over-spraying with a fungal spore suspension. After incubation fungi-toxicity is indicated by a growth inhibition zone, the area of which is related to the concentration of the sample.B.K. Rana and V. Taneja are with the Department of Biochemistry. Faculty of Science, Banaras Hindu University, Varanasi 221005, India; U.P. Singh is with the Department of Mycology and Plant Pathology, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi 221005, India.