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1.
Background
Intrinsically disordered proteins (IDPs) and regions (IDRs) perform a variety of crucial biological functions despite lacking stable tertiary structure under physiological conditions in vitro. State-of-the-art sequence-based predictors of intrinsic disorder are achieving per-residue accuracies over 80%. In a genome-wide study of intrinsic disorder in human genome we observed a big difference in predicted disorder content between confirmed and putative human proteins. We investigated a hypothesis that this discrepancy is not correct, and that it is due to incorrectly annotated parts of the putative protein sequences that exhibit some similarities to confirmed IDRs, which lead to high predicted disorder content.Methods
To test this hypothesis we trained a predictor to discriminate sequences of real proteins from synthetic sequences that mimic errors of gene finding algorithms. We developed a procedure to create synthetic peptide sequences by translation of non-coding regions of genomic sequences and translation of coding regions with incorrect codon alignment.Results
Application of the developed predictor to putative human protein sequences showed that they contain a substantial fraction of incorrectly assigned regions. These regions are predicted to have higher levels of disorder content than correctly assigned regions. This partially, albeit not completely, explains the observed discrepancy in predicted disorder content between confirmed and putative human proteins.Conclusions
Our findings provide the first evidence that current practice of predicting disorder content in putative sequences should be reconsidered, as such estimates may be biased.2.
Background
Studies of intrinsically disordered proteins that lack a stable tertiary structure but still have important biological functions critically rely on computational methods that predict this property based on sequence information. Although a number of fairly successful models for prediction of protein disorder have been developed over the last decade, the quality of their predictions is limited by available cases of confirmed disorders.Results
To more reliably estimate protein disorder from protein sequences, an iterative algorithm is proposed that integrates predictions of multiple disorder models without relying on any protein sequences with confirmed disorder annotation. The iterative method alternately provides the maximum a posterior (MAP) estimation of disorder prediction and the maximum-likelihood (ML) estimation of quality of multiple disorder predictors. Experiments on data used at CASP7, CASP8, and CASP9 have shown the effectiveness of the proposed algorithm.Conclusions
The proposed algorithm can potentially be used to predict protein disorder and provide helpful suggestions on choosing suitable disorder predictors for unknown protein sequences.3.
Objectives
The effect of different formulations variables on protein integrity were investigated using lysozyme as a model protein for the development of biotherapeutic protein formulations for use in the clinic.Results
Buffer composition/concentration was the key variable of formulation reagents investigated in determining lysozyme stability and authenticity independent of protein concentration whilst the storage temperature and time, not surprisingly, were also key variables. Tryptic peptide mapping of the protein showed that the modifications occurred when formulated under specific conditions but not others. A model peptide system was developed that reflected the same behavior under formulation conditions as intact lysozyme.Conclusions
Peptide models may mirror the stability of proteins, or regions of proteins, in the same formulations and be used to help develop a rapid screen of formulations for stabilisation of biotherapeutic proteins.4.
Background
The protein encoded by the gene ybgI was chosen as a target for a structural genomics project emphasizing the relation of protein structure to function.Results
The structure of the ybgI protein is a toroid composed of six polypeptide chains forming a trimer of dimers. Each polypeptide chain binds two metal ions on the inside of the toroid.Conclusion
The toroidal structure is comparable to that of some proteins that are involved in DNA metabolism. The di-nuclear metal site could imply that the specific function of this protein is as a hydrolase-oxidase enzyme.5.
Ronesh Sharma Shiu Kumar Tatsuhiko Tsunoda Ashwini Patil Alok Sharma 《BMC bioinformatics》2016,17(19):504
Background
Intrinsically Disordered Proteins (IDPs) lack an ordered three-dimensional structure and are enriched in various biological processes. The Molecular Recognition Features (MoRFs) are functional regions within IDPs that undergo a disorder-to-order transition on binding to a partner protein. Identifying MoRFs in IDPs using computational methods is a challenging task.Methods
In this study, we introduce hidden Markov model (HMM) profiles to accurately identify the location of MoRFs in disordered protein sequences. Using windowing technique, HMM profiles are utilised to extract features from protein sequences and support vector machines (SVM) are used to calculate a propensity score for each residue. Two different SVM kernels with high noise tolerance are evaluated with a varying window size and the scores of the SVM models are combined to generate the final propensity score to predict MoRF residues. The SVM models are designed to extract maximal information between MoRF residues, its neighboring regions (Flanks) and the remainder of the sequence (Others).Results
To evaluate the proposed method, its performance was compared to that of other MoRF predictors; MoRFpred and ANCHOR. The results show that the proposed method outperforms these two predictors.Conclusions
Using HMM profile as a source of feature extraction, the proposed method indicates improvement in predicting MoRFs in disordered protein sequences.6.
7.
Jensen LJ Skovgaard M Sicheritz-Pontén T Jørgensen MK Lundegaard C Pedersen CC Petersen N Ussery D 《BMC genomics》2003,4(1):12
Background
For most sequenced prokaryotic genomes, about a third of the protein coding genes annotated are "orphan proteins", that is, they lack homology to known proteins. These hypothetical genes are typically short and randomly scattered throughout the genome. This trend is seen for most of the bacterial and archaeal genomes published to date.Results
In contrast we have found that a large fraction of the genes coding for such orphan proteins in the Methanopyrus kandleri AV19 genome occur within two large regions. These genes have no known homologs except from other M. kandleri genes. However, analysis of their lengths, codon usage, and Ribosomal Binding Site (RBS) sequences shows that they are most likely true protein coding genes and not random open reading frames.Conclusions
Although these regions can be considered as candidates for massive lateral gene transfer, our bioinformatics analysis suggests that this is not the case. We predict many of the organism specific proteins to be transmembrane and belong to protein families that are non-randomly distributed between the regions. Consistent with this, we suggest that the two regions are most likely unrelated, and that they may be integrated plasmids.8.
Expression and purification of classical swine fever virus E2 protein from Sf9 cells using a modified vector 总被引:1,自引:0,他引:1
Objective
To develop a simple method for efficient expression of classical swine fever virus (CSFV) E2 protein.Results
The pFastBac HT B vector (pFastHTB-M1) was modified by adding a melittin signal peptide sequence. The E2 gene fragment without the transmembrane region was cloned into pFastHTB-M1. The modified vector has clear advantage over the original one, as evidenced by the purified recombinant E2 protein that was detected significantly by SDS-PAGE.Conclusions
The modified vector has the potential for large-scale production and easy purification of the CSFV E2 protein or other proteins of interests.9.
D. Jacob C. Deborde M. Lefebvre M. Maucourt A. Moing 《Metabolomics : Official journal of the Metabolomic Society》2017,13(4):36
Introduction
Concerning NMR-based metabolomics, 1D spectra processing often requires an expert eye for disentangling the intertwined peaks.Objectives
The objective of NMRProcFlow is to assist the expert in this task in the best way without requirement of programming skills.Methods
NMRProcFlow was developed to be a graphical and interactive 1D NMR (1H & 13C) spectra processing tool.Results
NMRProcFlow (http://nmrprocflow.org), dedicated to metabolic fingerprinting and targeted metabolomics, covers all spectra processing steps including baseline correction, chemical shift calibration and alignment.Conclusion
Biologists and NMR spectroscopists can easily interact and develop synergies by visualizing the NMR spectra along with their corresponding experimental-factor levels, thus setting a bridge between experimental design and subsequent statistical analyses.10.
Background
Analysis of preferred binding regions of a ligand on a protein is important for detecting cryptic binding pockets and improving the ligand selectivity.Result
The enhanced sampling approach TAMD has been adapted to allow a ligand to unbind from its native binding site and explore the protein surface. This so-called re-TAMD procedure was then used to explore the interaction between the N terminal peptide of histone H3 and the YEATS domain. Depending on the length of the peptide, several regions of the protein surface were explored. The peptide conformations sampled during the re-TAMD correspond to peptide free diffusion around the protein surface.Conclusions
The re-TAMD approach permitted to get information on the relative influence of different regions of the N terminal peptide of H3 on the interaction between H3 and YEATS.11.
Background
The mouse Fv1 (friend virus) susceptibility gene inhibits the development of the murine leukaemia virus (MLV) by interacting with its capsid (CA) protein. As no structures are available for these proteins we have constructed molecular models based on distant sequence similarity to other retroviral capsid proteins.Results
Molecular models were constructed for the amino terminal domains of the probable capsid-like structure for the mouse Fv1 gene product and the capsid protein of the MLV. The models were based on sequence alignments with a variety of other retrovirus capsid proteins. As the sequence similarity of these proteins with MLV and especially Fv1 is very distant, a threading method was employed that incorporates predicted secondary structure and multiple sequence information. The resulting models were compared with equivalent models constructed using the sequences of the capsid proteins of known structure.Conclusions
These comparisons suggested that the MLV model should be accurate in the core but with significant uncertainty in the loop regions. The Fv1 model may have some additional errors in the core packing of its helices but the resulting model gave some support to the hypothesis that it adopts a capsid-like structure.12.
N. Cesbron A.-L. Royer Y. Guitton A. Sydor B. Le Bizec G. Dervilly-Pinel 《Metabolomics : Official journal of the Metabolomic Society》2017,13(8):99
Introduction
Collecting feces is easy. It offers direct outcome to endogenous and microbial metabolites.Objectives
In a context of lack of consensus about fecal sample preparation, especially in animal species, we developed a robust protocol allowing untargeted LC-HRMS fingerprinting.Methods
The conditions of extraction (quantity, preparation, solvents, dilutions) were investigated in bovine feces.Results
A rapid and simple protocol involving feces extraction with methanol (1/3, M/V) followed by centrifugation and a step filtration (10 kDa) was developed.Conclusion
The workflow generated repeatable and informative fingerprints for robust metabolome characterization.13.
Background
There are now several ways to generate fluorescent fusion proteins by randomly inserting DNA encoding the Green Fluorescent Protein (GFP) into another protein's coding sequence. These approaches can be used to map regions in a protein that are permissive for GFP insertion or to create novel biosensors. While remarkably useful, the current insertional strategies have two major limitations: (1) they only produce one kind, or color, of fluorescent fusion protein and (2) one half of all GFP insertions within the target coding sequence are in the wrong orientation.Results
We have overcome these limitations by incorporating two different fluorescent proteins coding sequences in a single transposon, either in tandem or antiparallel. Our initial tests targeted two mammalian integral membrane proteins: the voltage sensitive motor, Prestin, and an ER ligand gated Ca2+ channel (IP3R).Conclusions
These new designs increase the efficiency of random fusion protein generation in one of two ways: (1) by creating two different fusion proteins from each insertion or (2) by being independent of orientation.14.
Nicholas J. Bond Albert Koulman Julian L. Griffin Zoe Hall 《Metabolomics : Official journal of the Metabolomic Society》2017,13(11):128
Introduction
Mass spectrometry imaging (MSI) experiments result in complex multi-dimensional datasets, which require specialist data analysis tools.Objectives
We have developed massPix—an R package for analysing and interpreting data from MSI of lipids in tissue.Methods
massPix produces single ion images, performs multivariate statistics and provides putative lipid annotations based on accurate mass matching against generated lipid libraries.Results
Classification of tissue regions with high spectral similarly can be carried out by principal components analysis (PCA) or k-means clustering.Conclusion
massPix is an open-source tool for the analysis and statistical interpretation of MSI data, and is particularly useful for lipidomics applications.15.
Background
Long-term exposure to drugs of abuse causes an upregulation of the cAMP-signaling pathway in the nucleus accumbens and other forebrain regions, this common neuroadaptation is thought to underlie aspects of drug tolerance and dependence. Phosphodiesterase 4 (PDE4) is an enzyme that the selective hydrolyzes intracellular cAMP. It is expressed in several brain regions that regulate the reinforcing effects of drugs of abuse.Objective
Here, we review the current knowledge about central nervous system (CNS) distribution of PDE4 isoforms and the effects of systemic and brain-region specific inhibition of PDE4 on behavioral models of drug addiction.Methods
A systematic literature search was performed using the Pubmed.Results
Using behavioral sensitization, conditioned place preference and drug self-administration as behavioral models, a large number of studies have shown that local or systemic administration of PDE4 inhibitors reduce drug intake and/or drug seeking for psychostimulants, alcohol, and opioids in rats or mice.Conclusions
Preclinical studies suggest that PDE4 could be a therapeutic target for several classes of substance use disorder. We conclude by identifying opportunities for the development of subtype-selective PDE4 inhibitors that may reduce addiction liability and minimize the side effects that limit the clinical potential of non-selective PDE4 inhibitors. Several PDE4 inhibitors have been clinically approved for other diseases. There is a promising possibility to repurpose these PDE4 inhibitors for the treatment of drug addiction as they are safe and well-tolerated in patients.16.
17.
Background
Proteins play fundamental and crucial roles in nearly all biological processes, such as, enzymatic catalysis, signaling transduction, DNA and RNA synthesis, and embryonic development. It has been a long-standing goal in molecular biology to predict the tertiary structure of a protein from its primary amino acid sequence. From visual comparison, it was found that a 2D triangular lattice model can give a better structure modeling and prediction for proteins with short primary amino acid sequences.Methods
This paper proposes a hybrid of hill-climbing and genetic algorithm (HHGA) based on elite-based reproduction strategy for protein structure prediction on the 2D triangular lattice.Results
The simulation results show that the proposed HHGA can successfully deal with the protein structure prediction problems. Specifically, HHGA significantly outperforms conventional genetic algorithms and is comparable to the state-of-the-art method in terms of free energy.Conclusions
Thanks to the enhancement of local search on the global search, the proposed HHGA achieves promising results on the 2D triangular protein structure prediction problem. The satisfactory simulation results demonstrate the effectiveness of the proposed HHGA and the utility of the 2D triangular lattice model for protein structure prediction.18.
Rachel A. Spicer Christoph Steinbeck 《Metabolomics : Official journal of the Metabolomic Society》2018,14(1):16
Introduction
Data sharing is being increasingly required by journals and has been heralded as a solution to the ‘replication crisis’.Objectives
(i) Review data sharing policies of journals publishing the most metabolomics papers associated with open data and (ii) compare these journals’ policies to those that publish the most metabolomics papers.Methods
A PubMed search was used to identify metabolomics papers. Metabolomics data repositories were manually searched for linked publications.Results
Journals that support data sharing are not necessarily those with the most papers associated to open metabolomics data.Conclusion
Further efforts are required to improve data sharing in metabolomics.19.
20.
Athanasios Tragiannidis Zoe Dorothea Pana Theodotis Papageorgiou Emmanuel Hatzipantelis Maria Hatzistilianou Fani Athanassiadou 《Journal of medical case reports》2011,5(1):407