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181.
Cloning and Expression of Catalytic Subunit of MLIII, the Ribosome-Inactivating Protein from Viscum album 总被引:1,自引:0,他引:1
Tonevitsky AG Agapov II Pevzner IB Malyuchenko NV Moisenovich MM Pfueller U Kirpichnikov MP 《Biochemistry. Biokhimii?a》2004,69(6):642-650
We have cloned the gene encoding a precursor of mistletoe (Viscum album) toxin MLIII. Analyses of nucleotide and deduced amino acid sequences of this gene revealed significant differences between MLI and MLIII preprotoxin genes. Immunochemical properties of recombinant A-subunit expressed in Escherichia coli and renatured were investigated using a panel of monoclonal antibodies raised against three mistletoe toxins (MLI, MLII, and MLIII). Ribosome-inactivating activity of recombinant MLIII A-subunit was detected in cell-free lysate of rabbit reticulocytes. 相似文献
182.
Fragment assembly with short reads 总被引:5,自引:0,他引:5
MOTIVATION: Current DNA sequencing technology produces reads of about 500-750 bp, with typical coverage under 10x. New sequencing technologies are emerging that produce shorter reads (length 80-200 bp) but allow one to generate significantly higher coverage (30x and higher) at low cost. Modern assembly programs and error correction routines have been tuned to work well with current read technology but were not designed for assembly of short reads. RESULTS: We analyze the limitations of assembling reads generated by these new technologies and present a routine for base-calling in reads prior to their assembly. We demonstrate that while it is feasible to assemble such short reads, the resulting contigs will require significant (if not prohibitive) finishing efforts. AVAILABILITY: Available from the web at http://www.cse.ucsd.edu/groups/bioinformatics/software.html 相似文献
183.
DB Zorov EY Plotnikov SS Jankauskas NK Isaev DN Silachev LD Zorova IB Pevzner NV Pulkova SD Zorov MA Morosanova 《Biochemistry. Biokhimii?a》2012,77(7):742-753
Programmed execution of various cells and intracellular structures is hypothesized to be not the only example of elimination of biological systems — the general mechanism can also involve programmed execution of organs and organisms. Modern rating of programmed cell death mechanisms includes 13 mechanistic types. As for some types, the mechanism of actuation and manifestation of cell execution has been basically elucidated, while the causes and intermediate steps of the process of fatal failure of organs and organisms remain unknown. The analysis of deaths resulting from a sudden heart arrest or multiple organ failure and other acute and chronic pathologies leads to the conclusion of a special role of mitochondria and oxidative stress activating the immune system. Possible mechanisms of mitochondria-mediated induction of the signaling cascades involved in organ failure and death of the organism are discussed. These mechanisms include generation of reactive oxygen species and damage-associated molecular patterns in mitochondria. Some examples of renal failure-induced deaths are presented with mechanisms and settings determined by some hypothetical super system rather than by the kidneys themselves. This system plays the key role in the process of physiological senescence and termination of an organism. The facts presented suggest that it is the immune system involved in mitochondrial signaling that can act as the system responsible for the organism’s death. 相似文献
184.
Xiaowen Liu Yakov Sirotkin Yufeng Shen Gordon Anderson Yihsuan S. Tsai Ying S. Ting David R. Goodlett Richard D. Smith Vineet Bafna Pavel A. Pevzner 《Molecular & cellular proteomics : MCP》2012,11(6)
In the last two years, because of advances in protein separation and mass spectrometry, top-down mass spectrometry moved from analyzing single proteins to analyzing complex samples and identifying hundreds and even thousands of proteins. However, computational tools for database search of top-down spectra against protein databases are still in their infancy. We describe MS-Align+, a fast algorithm for top-down protein identification based on spectral alignment that enables searches for unexpected post-translational modifications. We also propose a method for evaluating statistical significance of top-down protein identifications and further benchmark various software tools on two top-down data sets from Saccharomyces cerevisiae and Salmonella typhimurium. We demonstrate that MS-Align+ significantly increases the number of identified spectra as compared with MASCOT and OMSSA on both data sets. Although MS-Align+ and ProSightPC have similar performance on the Salmonella typhimurium data set, MS-Align+ outperforms ProSightPC on the (more complex) Saccharomyces cerevisiae data set.In the past two decades, proteomics was dominated by bottom-up mass spectrometry that analyzes digested peptides rather than intact proteins. Bottom-up approaches, although powerful, do have limitations in analyzing protein species, e.g. various proteolytic forms of the same protein or various protein isoforms resulting from alternative splicing. Top-down mass spectrometry focuses on analyzing intact proteins and large peptides (1–10) and has advantages in localizing multiple post-translational modifications (PTMs)1 in a coordinated fashion (e.g. combinatorial PTM code) and identifying multiple protein species (e.g. proteolytically processed protein species) (11). Until recently, most top-down studies were limited to single purified proteins (12–15). Top-down studies of protein mixtures were restricted by difficulties in separating and fragmenting intact proteins and a shortage of robust computational tools.In the last two years, because of advances in protein separation and top-down instrumentation, top-down mass spectrometry moved from analyzing single proteins to analyzing complex samples containing hundreds and even thousands of proteins (16–21). Because algorithms for interpreting top-down spectra are still in their infancy, many recent developments include computational innovations in protein identification.Because top-down spectra are complex, the first step in top-down spectral interpretation is usually spectral deconvolution, which converts a complex top-down spectrum to a list of monoisotopic masses (a deconvolved spectrum). Every protein (possibly with modifications) can be scored against a top-down deconvoluted spectrum, resulting in a Protein-Spectrum-Match (PrSM). The top-down protein identification problem is finding a protein in a database with the highest scoring PrSM for a top-down spectrum and further output the PrSM if it is statistically significant. There are several software tools for top-down protein identification (Software Identification of unexpected modifications Proteogenomics search against 6-frame translation Speed Estimation of statistical significance ProSightPC +/−a + Fast/Slowb + PIITA +/− − Fast − UStag + + Fast − MS-TopDown + − Slow − MS-Align+ + + Fast +