Results 1 - 10 of 8316
Results 1 - 10 of 8316. Search took: 0.031 seconds
|Sort by: date | relevance|
[en] Protein sequences as special heterogeneous sequences are rare in the amino acid sequence space. The specific sequential order of amino acids of a protein is essential to its 3D structure. On the whole, the correlation between sequence and structure of a protein is not so strong. How well would a protein sequence contain its structural information? How does a sequence determine its native structure? Keeping the globular proteins in mind, we discuss several problems from sequence to structure. (topical review - statistical physics and complex systems)
[en] The V protein of SV41 targets STAT1, while a specific loss of STAT2 is induced by the hPIV2 V protein. We established HeLa cells constitutively expressing various chimeric proteins between the hPIV2 and SV41 V proteins, and which STAT (STAT1 or 2) was expressed in these cells was analyzed. Both the P-V common domain and the V specific domain of hPIV2 V protein are necessary for STAT2 lowering. The internal domain (aa145-173) containing a large number of nonidentical amino acids between hPIV2 and SV41 does not direct STAT tropism, and the regions necessary for STAT2 lowering are discontinuous. The N-terminal domain (aa1-104) and the internal domain (aa126-196) of the hPIV2 V protein do not determine STAT tropism. HeLa cells expressing A105E or H108P show distinct expression of STAT2, but do show low expression or a loss of STAT1, indicating that the amino acid residues 105 and 108 of the hPIV2 V protein are essential for STAT2 lowering. Interestingly, there is an important amino acid(s) in the region (aa121-125) for STAT2 lowering, and the presence of either amino acid residue 123 or 125 of the hPIV2 V protein is necessary for lowering of STAT2. In addition, HeLa cells expressing S216D or 1217R expressed STAT2, but no STAT1, indicating that the amino acid residues 216 and 217 of the hPIV2 V protein are indispensable for STAT2 lowering. HeLa/hPIV2V cells and HeLa/S104/P are resistant to IFN-β, while they are sensitive to IFN-γ. On the other hand, HeLa/SV41V, HeLa/S216D, and HeLa1217R cells are resistant to both IFNs. Intriguingly, HeLa/A105E and HeLa/H108P cells were found to be sensitive to IFN-γ
[en] To efficiently elucidate the biological roles of phosphatidylserine (PS), we developed open-reading-frame (ORF) phage display to identify PS-binding proteins. The procedure of phage panning was optimized with a phage clone expressing MFG-E8, a well-known PS-binding protein. Three rounds of phage panning with ORF phage display cDNA library resulted in ∼300-fold enrichment in PS-binding activity. A total of 17 PS-binding phage clones were identified. Unlike phage display with conventional cDNA libraries, all 17 PS-binding clones were ORFs encoding 13 real proteins. Sequence analysis revealed that all identified PS-specific phage clones had dimeric basic amino acid residues. GST fusion proteins were expressed for 3 PS-binding proteins and verified for their binding activity to PS liposomes, but not phosphatidylcholine liposomes. These results elucidated previously unknown PS-binding proteins and demonstrated that ORF phage display is a versatile technology capable of efficiently identifying binding proteins for non-protein molecules like PS.
[en] Proteins are vital in all biological systems as they constitute the main structural and functional components of cells. Recent advances in mass spectrometry have brought the promise of complete proteomics by helping draft the human proteome. Yet, this commonly used protein sequencing technique has fundamental limitations in sensitivity. Here we propose a method for single-molecule (SM) protein sequencing. A major challenge lies in the fact that proteins are composed of 20 different amino acids, which demands 20 molecular reporters. We computationally demonstrate that it suffices to measure only two types of amino acids to identify proteins and suggest an experimental scheme using SM fluorescence. When achieved, this highly sensitive approach will result in a paradigm shift in proteomics, with major impact in the biological and medical sciences. (paper)
[en] We report the discovery of a new virus from the red imported fire ant, Solenopsis invicta. Solenopsis invicta virus 3 (SINV-3) represents the third virus discovered from this ant species using the metagenomics approach. The single (positive)-strand RNA, monopartite, bicistronic genome of SINV-3 was sequenced in entirety (GenBank accession number (FJ528584)), comprised of 10,386 nucleotides, and polyadenylated at the 3' terminus. This genome size was confirmed by Northern analysis. The genome revealed 2 large open reading frames (ORFs) in the sense orientation with an untranslated region (UTR) at each end and between the two ORFs. The 5' proximal ORF (ORF 1) encoded a predicted protein of 299.1 kDa (2580 amino acids). The 3' proximal ORF (ORF 2) encoded a predicted protein of 73.2 kDa (651 amino acids). RNA-dependent RNA polymerase (RdRp), helicase, and protease domains were recognized in ORF 1. SDS-PAGE separation of purified SINV-3 particles yielded 2 bands (ostensibly capsid proteins) with a combined molecular mass of 77.3 kDa which was similar to the mass predicted by ORF 2 (73.2 kDa). Phylogenetic analysis of the conserved amino acid sequences containing domains I to VIII of the RdRp from dicistroviruses, iflaviruses, plant small RNA viruses, picornaviruses, and 4 unassigned positive-strand RNA viruses revealed a trichotomous phenogram with SINV-3 and Kelp fly virus comprising a unique cluster. Electron microscopic examination of negatively stained samples of SINV-3 revealed isometric particles with apparent projections and a diameter of 27.3 ± 1.3 nm. SINV-3 was successfully transmitted to uninfected workers by feeding. The minus (replicative) strand of SINV-3 was detected in worker ants indicating replication of the virus. The possibility of using SINV-3 as a microbial control agent for fire ants is discussed.
[en] Previously it was shown that fusion proteins containing the amino terminus of an apical targeted member of the serpin family fused to the corresponding carboxyl terminus of the non-polarized secreted serpin, antithrombin, are secreted mainly to the apical side of MDCK cells. The present study shows that this is neither due to the transfer of an apical sorting signal from the apically expressed proteins, since a sequence of random amino acids acts the same, nor is it due to the deletion of a conserved signal for correct targeting from the non-polarized secreted protein. Our results suggest that the polarity of secretion is determined by conformational sensitive sorting signals
[en] Messenger RNA (mRNA) encodes a sequence of amino acids by using codons. For most amino acids, there are multiple synonymous codons that can encode the amino acid. The translation speed can vary from one codon to another, thus there is room for changing the ribosome speed while keeping the amino acid sequence and hence the resulting protein. Recently, it has been noticed that the choice of the synonymous codon, via the resulting distribution of slow- and fast-translated codons, affects not only on the average speed of one ribosome translating the mRNA but also might have an effect on nearby ribosomes by affecting the appearance of ‘traffic jams’ where multiple ribosomes collide and form queues. To test this ‘context effect’ further, we here investigate the effect of the sequence of synonymous codons on the ribosome traffic by using a ribosome traffic model with codon-dependent rates, estimated from experiments. We compare the ribosome traffic on wild-type (WT) sequences and sequences where the synonymous codons were swapped randomly. By simulating translation of 87 genes, we demonstrate that the WT sequences, especially those with a high bias in codon usage, tend to have the ability to reduce ribosome collisions, hence optimizing the cellular investment in the translation apparatus. The magnitude of such reduction of the translation time might have a significant impact on the cellular growth rate and thereby have importance for the survival of the species. (paper)
[en] We show that most isolates of influenza A induce filamentous changes in infected cells in contrast to A/WSN/33 and A/PR8/34 strains which have undergone extensive laboratory passage and are mouse-adapted. Using reverse genetics, we created recombinant viruses in the naturally filamentous genetic background of A/Victoria/3/75 and established that this property is regulated by the M1 protein sequence, but that the phenotype is complex and several residues are involved. The filamentous phenotype was lost when the amino acid at position 41 was switched from A to V, at the same time, this recombinant virus also became insensitive to the antibody 14C2. On the other hand, the filamentous phenotype could be fully transferred to a virus containing RNA segment 7 of the A/WSN/33 virus by a combination of three mutations in both the amino and carboxy regions of the M1 protein. This observation suggests that an interaction among these regions of M1 may occur during assembly
[en] The character of forming long-range contacts affects the three-dimensional structure of globular proteins deeply. As the different ability to form long-range contacts between 20 types of amino acids and 4 categories of globular proteins, the statistical properties are thoroughly discussed in this paper. Two parameters NC and ND are defined to confine the valid residues in detail. The relationship between hydrophobicity scales and valid residue percentage of each amino acid is given in the present work and the linear functions are shown in our statistical results. It is concluded that the hydrophobicity scale defined by chemical derivatives of the amino acids and nonpolar phase of large unilamellar vesicle membranes is the most effective technique to characterise the hydrophobic behavior of amino acid residues. Meanwhile, residue percentage Pi and sequential residue length Li of a certain protein i are calculated under different conditions. The statistical results show that the average value of Pi as well as Li of all-α proteins has a minimum among these 4 classes of globular proteins, indicating that all-α proteins are hardly capable of forming long-range contacts one by one along their linear amino acid sequences. All-β proteins have a higher tendency to construct long-range contacts along their primary sequences related to the secondary configurations, i.e. parallel and anti-parallel configurations of β sheets. The investigation of the interior properties of globular proteins give us the connection between the three-dimensional structure and its primary sequence data or secondary configurations, and help us to understand the structure of protein and its folding process well. (cross-disciplinary physics and related areas of science and technology)
[en] Subcellular location of protein is constructive information in determining its function, screening for drug candidates, vaccine design, annotation of gene products and in selecting relevant proteins for further studies. Computational prediction of subcellular localization deals with predicting the location of a protein from its amino acid sequence. For a computational localization prediction method to be more accurate, it should exploit all possible relevant biological features that contribute to the subcellular localization. In this work, we extracted the biological features from the full length protein sequence to incorporate more biological information. A new biological feature, distribution of atomic composition is effectively used with, multiple physiochemical properties, amino acid composition, three part amino acid composition, and sequence similarity for predicting the subcellular location of the protein. Support Vector Machines are designed for four modules and prediction is made by a weighted voting system. Our system makes prediction with an accuracy of 100, 82.47, 88.81 for self-consistency test, jackknife test and independent data test respectively. Our results provide evidence that the prediction based on the biological features derived from the full length amino acid sequence gives better accuracy than those derived from N-terminal alone. Considering the features as a distribution within the entire sequence will bring out underlying property distribution to a greater detail to enhance the prediction accuracy.