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Background: Recent advances on high-throughput technologies have produced a vast amount of protein sequences, while the number of high-resolution structures has seen a limited increase. This has impelled the production of many strategies to built protein structures from its sequence, generating a considerable amount of alternative models. The selection of the closest model to the native conformation has thus become crucial for structure prediction. Several methods have been developed to score protein models by energies, knowledge-based potentials and combination of both. Results: Here, we present and demonstrate a theory to split the knowledge-based potentials in scoring terms biologically meaningful and to combine them in new scores to predict near-native structures. Our strategy allows circumventing the problem of defining the reference state. In this approach we give the proof for a simple and linear application that can be further improved by optimizing the combination of Zscores. Using the simplest composite score (ZECbeta) we obtained predictions similar to state-of-the-art methods. Besides, our approach has the advantage of identifying the most relevant terms involved in the stability of the protein structure. Finally, we also use the composite Zscores to assess the conformation of models and to detect local errors. Conclusions: We have introduced a method to split knowledge-based potentials and to solve the problem of defining a reference state. The new scores have detected near-native structures as accurately as state-of-art methods and have been successful to identify wrongly modeled regions of many near-native conformations.

BMC Bioinformatics - Latest Articles

2009-11-23T00:00:00Z Iterative Pruning PCA Improves Resolution of Highly Structured Populations

Background: Non-random patterns of genetic variation exist among individuals in a population owing to a variety of evolutionary factors. Therefore, populations are structured into genetically distinct subpopulations. As genotypic datasets become ever larger, it is increasingly difficult to correctly estimate the number of subpopulations and assigning individuals to them. The computationally efficient non-parametric, chiefly Principal Components Analysis (PCA)-based methods are thus becoming increasingly relied upon for population structure analysis. Current PCA-based methods can accurately detect structure; however, the accuracy in resolving subpopulations and assigning individuals to them is wanting. When subpopulations are closely related to one another, they overlap in PCA space and appear as a conglomerate. This problem is exacerbated when some subpopulations in the dataset are genetically far removed from others. We propose a novel PCA-based framework which addresses this shortcoming. Results: A novel population clustering program called iterative pruning PCA (ipPCA) was developed which assigns individuals to subpopulations and infers the total number of subpopulations present. Genotypic data from simulated and real population datasets with different degrees of structure were analyzed by the proposed method. For datasets with simple structures, the subpopulation assignments of individuals made by ipPCA were consistent with the STRUCTURE and AWclust algorithms. On the other hand, highly structured populations containing many closely related subpopulations could be accurately resolved only by ipPCA, and not by other methods. Conclusions: The algorithm is computationally efficient and not constrained by the dataset complexity. This systematic clustering approach removes the need for prior population labels, which could be advantageous when cryptic stratification is encountered in datasets of individuals otherwise assumed to be homogenous.

BMC Genomics - Latest Articles

2009-11-22T00:00:00Z Genome reannotation of Escherichia coli CFT073 with new insights into virulence

Background: As one of human pathogens, the genome of Uropathogenic Escherichia coli strain CFT073 was sequenced and published in 2002, which was significant in pathogenetic bacterial genomics research. However, the current RefSeq annotation of this pathogen is now outdated to some degree, due to missing or misannotation of some essential genes associated with its virulence. We carried out a systematic reannotation by combining automated annotation tools with manual efforts to provide a comprehensive understanding of virulence for the CFT073 genome. Results: The reannotation excluded 608 coding sequences from the RefSeq annotation. Meanwhile, a total of 299 coding sequences were newly added, about one third of them are found in genomic island (GI) regions while more than one fifth of them are located in virulence related regions pathogenicity islands (PAIs). Furthermore, there are totally 341 genes were relocated with their translational initiation sites (TISs), which resulted in a high quality of gene start annotation. In addition, 94 pseudogenes annotated in RefSeq were thoroughly inspected and updated. The number of miscellaneous genes (sRNAs) has been updated from 6 in RefSeq to 46 in the reannotation. Based on the adjustment in the reannotation, subsequent analysis were conducted by both general and case studies on new virulence factors or new virulence-associated genes that are crucial during the urinary tract infections (UTIs) process, including invasion, colonization, nutrition uptaking and population density control. Furthermore, miscellaneous RNAs collected in the reannotation are believed to contribute to the virulence of strain CFT073. The reannotation including the nucleotide data, the original RefSeq annotation, and all reannotated results is freely available via http://mech.ctb.pku.edu.cn/CFT073/. Conclusions: As a result, the reannotation presents a more comprehensive picture of mechanisms of uropathogenicity of UPEC strain CFT073. The new genes change the view of its uropathogenicity in many respects, particularly by new genes in GI regions and new virulence-associated factors. The reannotation thus functions as an important source by providing new information about genomic structure and organization, and gene function. Moreover, we expect that the detailed analysis will facilitate the studies for exploration of novel virulence mechanisms and help guide experimental design.

BMC Biochemistry - Latest Articles

2009-11-17T00:00:00Z Purification and characterization of cysteine protease from germinating cotyledons of horse gram

Background: Proteolytic enzymes play central role in the biochemical mechanism of germination and intricately involved in many aspects of plant physiology and development. To study the mechanism of protein mobilization, undertaken the task of purifying and characterizing proteases,which occur transiently in germinating seeds of horse gram. Results: Cysteine protease (CPRHG) was purified to homogeneity with 118 fold by four step procedure comprising Crude extract, (NH4)2SO4 fractionation, DEAE-Cellulose and CM-sephacel chromatography from the 2 day germinating cotyledons of horse gram (Macrotyloma uniflorum (Lam.) Verdc.). CPRHG is a monomer with molecular mass of 30 k Da, was determined by SDS-PAGE and gel filtration. The purified enzyme on IEF showed two isoforms having pI values of 5.85 and 6.1. CPRHG composed of high content of aspartic acid, glutamic acid and serine. The enzyme activity was completely inhibited by pCMB, iodoacetate and DEPC indicating cysteine and histidine residues at the active site. However, on addition of sulfhydryl reagents (cysteine, dithiothreitol, glutathione and beta-ME) reverse the strong inhibition by pCMB. The enzyme is fairly stable toward pH and temperature. Immunoblot analysis shows that the enzyme synthesized as zymogen (preproenzyme with 81 kDa) and processed to a 40 kDa proenzyme which was further degraded to give 30 kDa active enzyme. Conclusions: It appears that the newly synthesized protease is inactive, and activation takes place during germination. CPRHG has a broad substrate specificity and stability in pH, temperature, etc. therefore, this protease may turn out to be an efficient choice for the pharmaceutical, medicinal, food, and biotechnology industry.

Nature

2005-01-19 Einstein is dead

Until its next revolution, much of the glory of physics will be in engineering. It is a shame that the physicists who do so much of it keep so quiet about it.

Einstein is dead

Nature 433, 179 (2005). doi:10.1038/433179a

Until its next revolution, much of the glory of physics will be in engineering. It is a shame that the physicists who do so much of it keep so quiet about it.

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