937 resultados para Amino-acid Sites
Resumo:
Human respiratory syncytial virus (HRSV) is the major cause of lower respiratory tract infections in children under 5 years of age and the elderly, causing annual disease outbreaks during the fall and winter. Multiple lineages of the HRSVA and HRSVB serotypes co-circulate within a single outbreak and display a strongly temporal pattern of genetic variation, with a replacement of dominant genotypes occurring during consecutive years. In the present study we utilized phylogenetic methods to detect and map sites subject to adaptive evolution in the G protein of HRSVA and HRSVB. A total of 29 and 23 amino acid sites were found to be putatively positively selected in HRSVA and HRSVB, respectively. Several of these sites defined genotypes and lineages within genotypes in both groups, and correlated well with epitopes previously described in group A. Remarkably, 18 of these positively selected tended to revert in time to a previous codon state, producing a flipflop phylogenetic pattern. Such frequent evolutionary reversals in HRSV are indicative of a combination of frequent positive selection, reflecting the changing immune status of the human population, and a limited repertoire of functionally viable amino acids at specific amino acid sites.
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Among various groups of fishes, a shift in peak wavelength sensitivity has been correlated with changes in their photic environments. The genus Sebastes is a radiation of marine fish species that inhabit a wide range of depths from intertidal to over 600 m. We examined 32 species of Sebastes for evidence of adaptive amino acid substitution at the rhodopsin gene. Fourteen amino acid positions were variable among these species. Maximum likelihood analyses identify several of these to be targets of positive selection. None of these correspond to previously identified critical amino acid sites, yet they may in fact be functionally important. The occurrence of independent parallel changes at certain amino acid positions reinforces this idea. Reconstruction of habitat depths of ancestral nodes in the phylogeny suggests that shallow habitats have been colonized independently in different lineages. The evolution of rhodopsin appears to be associated with changes in depth, with accelerated evolution in lineages that have had large changes in depth.
Resumo:
Background Designing novel proteins with site-directed recombination has enormous prospects. By locating effective recombination sites for swapping sequence parts, the probability that hybrid sequences have the desired properties is increased dramatically. The prohibitive requirements for applying current tools led us to investigate machine learning to assist in finding useful recombination sites from amino acid sequence alone. Results We present STAR, Site Targeted Amino acid Recombination predictor, which produces a score indicating the structural disruption caused by recombination, for each position in an amino acid sequence. Example predictions contrasted with those of alternative tools, illustrate STAR'S utility to assist in determining useful recombination sites. Overall, the correlation coefficient between the output of the experimentally validated protein design algorithm SCHEMA and the prediction of STAR is very high (0.89). Conclusion STAR allows the user to explore useful recombination sites in amino acid sequences with unknown structure and unknown evolutionary origin. The predictor service is available from http://pprowler.itee.uq.edu.au/star.
Resumo:
Biogenic calcareous and siliceous sediments were drilled at ODP Sites 689 and 690 on the Maud Rise, Antarctic Ocean. We analyzed dissolved combined amino acids (DCAA) and dissolved free amino acids (DFAA) in interstitial waters in order to characterize the amino acids in dissolved organic matter. The DFAA was predominant over the DCAA in interstitial waters at Sites 689 and 690, which contradicted the previous results from interstitial water and seawater studies. The DCAA in the interstitial waters probably originated from calcareous biogenic debris with less amounts of siliceous debris. Although glutamic acid constituted 41% of the total concentration of DCAA, it accounted for only 1% of the total concentration of DFAA due to the adsorption and/or reaction with biogenic carbonate. Ornithine, a nonprotein amino acid, is a decomposed product of arginine and made up 17 mol% of the total DFAA and. The total hydrolyzable amino acids (=DCAA + DFAA) accounted for 5 to 28% of the dissolved organic carbon (DOC) concentration, which implied that high molecular weight organic matter was a major contributor for the DOM (dissolved organic matter) in interstitial waters. Fairly positive correlation between the dissolved manganese and the total DCAA values suggested that the redox condition plays a significant role in controlling the total DCAA content. A small decrease in the sulfate concentration in the interstitial waters from both sites suggested fairly low microbial activity by sulfate-reducing bacteria.
Resumo:
Sequence-specific interactions between aminoacyl-tRNA synthetases and their cognate tRNAs both ensure accurate RNA recognition and prevent the binding of noncognate substrates. Here we show for Escherichia coli glutaminyl-tRNA synthetase (GlnRS; EC 6.1.1.18) that the accuracy of tRNA recognition also determines the efficiency of cognate amino acid recognition. Steady-state kinetics revealed that interactions between tRNA identity nucleotides and their recognition sites in the enzyme modulate the amino acid affinity of GlnRS. Perturbation of any of the protein-RNA interactions through mutation of either component led to considerable changes in glutamine affinity with the most marked effects seen at the discriminator base, the 10:25 base pair, and the anticodon. Reexamination of the identity set of tRNA(Gln) in the light of these results indicates that its constituents can be differentiated based upon biochemical function and their contribution to the apparent Gibbs' free energy of tRNA binding. Interactions with the acceptor stem act as strong determinants of tRNA specificity, with the discriminator base positioning the 3' end. The 10:25 base pair and U35 are apparently the major binding sites to GlnRS, with G36 contributing both to binding and recognition. Furthermore, we show that E. coli tryptophanyl-tRNA synthetase also displays tRNA-dependent changes in tryptophan affinity when charging a noncognate tRNA. The ability of tRNA to optimize amino acid recognition reveals a novel mechanism for maintaining translational fidelity and also provides a strong basis for the coevolution of tRNAs and their cognate synthetases.
Resumo:
Proteins and their amino acid building blocks form a major group of biomolecules in all organisms. In the sedimentary environment, proteins and amino acids have two sources: (1) soft tissues and detritus and (2) biotic skeletal structures, dominantly from calcium carbonate-secreting organisms. The focus of this report is on D/L ratios and concentrations of selected amino acids in interstitial waters collected during ODP Leg 201. The Peru margin sites are generally low in carbonates, whereas the open-ocean sites are more carbonate rich. Seifert et al. (1990, doi:10.2973/odp.proc.sr.112.152.1990) reported amino acid concentrations in interstitial waters from Site 681 (ODP Leg 112) comparable to Leg 201 Site 1229.
Resumo:
Background: Designing novel proteins with site-directed recombination has enormous prospects. By locating effective recombination sites for swapping sequence parts, the probability that hybrid sequences have the desired properties is increased dramatically. The prohibitive requirements for applying current tools led us to investigate machine learning to assist in finding useful recombination sites from amino acid sequence alone. Results: We present STAR, Site Targeted Amino acid Recombination predictor, which produces a score indicating the structural disruption caused by recombination, for each position in an amino acid sequence. Example predictions contrasted with those of alternative tools, illustrate STAR'S utility to assist in determining useful recombination sites. Overall, the correlation coefficient between the output of the experimentally validated protein design algorithm SCHEMA and the prediction of STAR is very high (0.89). Conclusion: STAR allows the user to explore useful recombination sites in amino acid sequences with unknown structure and unknown evolutionary origin. The predictor service is available from http://pprowler.itee.uq.edu.au/star.
Resumo:
Ubiquitination involves the attachment of ubiquitin to lysine residues on substrate proteins or itself, which can result in protein monoubiquitination or polyubiquitination. Ubiquitin attachment to different lysine residues can generate diverse substrate-ubiquitin structures, targeting proteins to different fates. The mechanisms of lysine selection are not well understood. Ubiquitination by the largest group of E3 ligases, the RING-family E3 s, is catalyzed through co-operation between the non-catalytic ubiquitin-ligase (E3) and the ubiquitin-conjugating enzyme (E2), where the RING E3 binds the substrate and the E2 catalyzes ubiquitin transfer. Previous studies suggest that ubiquitination sites are selected by E3-mediated positioning of the lysine toward the E2 active site. Ultimately, at a catalytic level, ubiquitination of lysine residues within the substrate or ubiquitin occurs by nucleophilic attack of the lysine residue on the thioester bond linking the E2 catalytic cysteine to ubiquitin. One of the best studied RING E3/ E2 complexes is the Skp1/Cul1/F box protein complex, SCFCdc4, and its cognate E2, Cdc34, which target the CDK inhibitor Sic1 for K48-linked polyubiquitination, leading to its proteasomal degradation. Our recent studies of this model system demonstrated that residues surrounding Sic1 lysines or lysine 48 in ubiquitin are critical for ubiquitination. This sequence-dependence is linked to evolutionarily conserved key residues in the catalytic region of Cdc34 and can determine if Sic1 is mono- or poly-ubiquitinated. Our studies indicate that amino acid determinants in the Cdc34 catalytic region and their compatibility to those surrounding acceptor lysine residues play important roles in lysine selection. This may represent a general mechanism in directing the mode of ubiquitination in E2 s.
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Sequence specific resonance assignment constitutes an important step towards high-resolution structure determination of proteins by NMR and is aided by selective identification and assignment of amino acid types. The traditional approach to selective labeling yields only the chemical shifts of the particular amino acid being selected and does not help in establishing a link between adjacent residues along the polypeptide chain, which is important for sequential assignments. An alternative approach is the method of amino acid selective `unlabeling' or reverse labeling, which involves selective unlabeling of specific amino acid types against a uniformly C-13/N-15 labeled background. Based on this method, we present a novel approach for sequential assignments in proteins. The method involves a new NMR experiment named, {(CO)-C-12 (i) -N-15 (i+1)}-filtered HSQC, which aids in linking the H-1(N)/N-15 resonances of the selectively unlabeled residue, i, and its C-terminal neighbor, i + 1, in HN-detected double and triple resonance spectra. This leads to the assignment of a tri-peptide segment from the knowledge of the amino acid types of residues: i - 1, i and i + 1, thereby speeding up the sequential assignment process. The method has the advantage of being relatively inexpensive, applicable to H-2 labeled protein and can be coupled with cell-free synthesis and/or automated assignment approaches. A detailed survey involving unlabeling of different amino acid types individually or in pairs reveals that the proposed approach is also robust to misincorporation of N-14 at undesired sites. Taken together, this study represents the first application of selective unlabeling for sequence specific resonance assignments and opens up new avenues to using this methodology in protein structural studies.
A hierarchical Bayesian model for predicting the functional consequences of amino-acid polymorphisms
Resumo:
Genetic polymorphisms in deoxyribonucleic acid coding regions may have a phenotypic effect on the carrier, e.g. by influencing susceptibility to disease. Detection of deleterious mutations via association studies is hampered by the large number of candidate sites; therefore methods are needed to narrow down the search to the most promising sites. For this, a possible approach is to use structural and sequence-based information of the encoded protein to predict whether a mutation at a particular site is likely to disrupt the functionality of the protein itself. We propose a hierarchical Bayesian multivariate adaptive regression spline (BMARS) model for supervised learning in this context and assess its predictive performance by using data from mutagenesis experiments on lac repressor and lysozyme proteins. In these experiments, about 12 amino-acid substitutions were performed at each native amino-acid position and the effect on protein functionality was assessed. The training data thus consist of repeated observations at each position, which the hierarchical framework is needed to account for. The model is trained on the lac repressor data and tested on the lysozyme mutations and vice versa. In particular, we show that the hierarchical BMARS model, by allowing for the clustered nature of the data, yields lower out-of-sample misclassification rates compared with both a BMARS and a frequen-tist MARS model, a support vector machine classifier and an optimally pruned classification tree.
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Breast cancer is the most common malignancy among women in the world. Its 5-year survival rate ranges from 23.4% in patients with stage IV to 98% in stage I disease, highlighting the importance of early detection and diagnosis. 18F-2-Fluoro-2-deoxy-glucose (18F-FDG), using positron emission tomography (PET), is the most common functional imaging tool for breast cancer diagnosis currently. Unfortunately, 18F-FDG-PET has several limitations such as poorly differentiating tumor tissues from inflammatory and normal brain tissues. Therefore, 18F-labeled amino acid-based radiotracers have been reported as an alternative, which is based on the fact that tumor cells uptake and consume more amino acids to sustain their uncontrolled growth. Among those radiotracers, 18F-labeled tyrosine and its derivatives have shown high tumor uptake and great ability to differentiate tumor tissue from inflammatory sites in brain tumors and squamous cell carcinoma. They enter the tumor cells via L-type amino acid transporters (LAT), which were reported to be highly expressed in many cancer cell lines and correlate positively with tumor growth. Nevertheless, the low radiosynthesis yield and demand of an on-site cyclotron limit the use of 18F-labeled tyrosine analogues. In this study, four Technetium-99m (99mTc) labeled tyrosine/ AMT (α-methyl tyrosine)-based radiotracers were successfully synthesized and evaluated for their potentials in breast cancer imaging. In order to radiolabel tyrosine and AMT, the chelators N,N’-ethylene-di-L-cysteine (EC) and 1,4,8,11-tetra-azacyclotetradecane (N4 cyclam) were selected to coordinate 99mTc. These chelators have been reported to provide stable chelation ability with 99mTc. By using the chelator technology, the same target ligand could be labeled with different radioisotopes for various imaging modalities for tumor diagnosis, or for internal radionuclide therapy in future. Based on the in vitro and in vivo evaluation using the rat mammary tumor models, 99mTc-EC-AMT is considered as the most suitable radiotracer for breast cancer imaging overall, however, 99mTc-EC-Tyrosine will be more preferred for differential diagnosis of tumor from inflammation.
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In this study, we demonstrate the utility of amino acid geochronology based on single-foraminiferal tests in Quaternary sediment cores from the Queensland margin, Australia. The large planktonic foraminifer Pulleniatina obliquiloculata is ubiquitous in shelf, slope, and basin sediments of north Queensland as well as pantropical oceans. Fossil tests are resistant to dissolution, and retain substantial concentrations of amino acids (2-4 nmol/mg of shell) over hundreds of thousands of years. Amino acid D and L isomers of aspartic acid (Asp) and glutamic acid (Glu) were separated using reverse phase chromatography, which is sensitive enough to analyze individual foraminifera tests. In all, 462 Pulleniatina tests from 80 horizons in 11 cores exhibit a systematic increase in D/L ratios down core. D/L ratios were determined in 32 samples whose ages are known from AMS 14C analyses. In all cases, the Asp and Glu D/L ratios are concordant with 14C age. D/L ratios of equal-age samples are slightly lower for cores taken from deeper water sites, reflecting the sensitivity of the rate of racemization to bottom water temperature. Beyond the range of 14C dating, previously identified marine oxygen-isotope stage boundaries provide approximate ages of the sediments up to about 500,000 years. For this longer time frame, D/L ratios also vary systematically with isotope-correlated ages. The rate of racemization for Glu and Asp was modeled using power functions. These equations can be used to estimate ages of samples from the Queensland margin extending back at least 500,000 years. This analytical approach provides new opportunities for geochronological control necessary to understand fundamental sedimentary processes affecting a wide range of marine environments.