Protein structure, amino acid composition and sequence determine proteome vulnerability to oxidation-induced damage.
Ontology highlight
ABSTRACT:
SUBMITTER: Chang RL
PROVIDER: S-EPMC7705453 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Amino acid composition is a sequence feature that has been extensively used to characterize proteomes of many species and protein families. Yet the analysis of amino acid composition of protein domains and the linkers connecting them has received less attention. Here, we perform both a comprehensive full-proteome amino acid composition analysis and a similar analysis focusing on domains and linkers, to uncover domain- or linker-specific differential amino acid usage patterns.The amino acid composition in the 38 proteomes studied showcase the greater variability found in archaea and bacteria species compared to eukaryotes. When focusing on domains and linkers, we describe the preferential use of polar residues in linkers and hydrophobic residues in domains. To let any user perform this analysis on a given domain (or set of them), we developed a dedicated R script called RACCOON, which can be easily used and can provide interesting insights into the compositional differences between a domain and its surrounding linkers.
| S-EPMC5807739 | biostudies-literature
Project description:Proteins with low-complexity domains continue to emerge as key players in both normal and pathological cellular processes. Although low-complexity domains are often grouped into a single class, individual low-complexity domains can differ substantially with respect to amino acid composition. These differences may strongly influence the physical properties, cellular regulation, and molecular functions of low-complexity domains. Therefore, we developed a bioinformatic approach to explore relationships between amino acid composition, protein metabolism, and protein function. We find that local compositional enrichment within protein sequences is associated with differences in translation efficiency, abundance, half-life, protein-protein interaction promiscuity, subcellular localization, and molecular functions of proteins on a proteome-wide scale. However, local enrichment of related amino acids is sometimes associated with opposite effects on protein regulation and function, highlighting the importance of distinguishing between different types of low-complexity domains. Furthermore, many of these effects are discernible at amino acid compositions below those required for classification as low-complexity or statistically-biased by traditional methods and in the absence of homopolymeric amino acid repeats, indicating that thresholds employed by classical methods may not reflect biologically relevant criteria. Application of our analyses to composition-driven processes, such as the formation of membraneless organelles, reveals distinct composition profiles even for closely related organelles. Collectively, these results provide a unique perspective and detailed insights into relationships between amino acid composition, protein metabolism, and protein functions.
| S-EPMC6171957 | biostudies-literature
Project description:The effect of random reshuffling of amino acids on the properties of dimers formed by Aβ peptides is studied using replica exchange molecular dynamics and united atom implicit solvent model. We show that thermodynamics of dimer assembly and the dimer globule-like state are not affected by sequence permutation. Furthermore, sequence reshuffling does not change the distributions of non-local interactions and, to a large extent, amino acids in the dimer volume. To rationalize these results, we demonstrate that Gaussian statistics applies surprisingly well to the end-to-end distances of the peptides in the dimer implying that non-bonded interactions between distant along the chain amino acids are effectively screened. This observation suggests that peptides in the dimer behave as ideal chains in polymer melt, in which amino acids lose their "identity" and therefore the memory of sequence position. As a result large-scale properties of the dimer become universal or sequence independent. Comparison of our simulations with the prior theoretical studies and their implications for experiments are discussed.
| S-EPMC3155579 | biostudies-other
Project description:The analysis of the secretome provides important information on cellular communication and on the recruitment and behavior of cells in specific tissues. Especially in the context of tumors, knowledge on the composition of the secretome plays an important role for diagnosis and therapy. Mass spectrometry-based analysis of cell-conditioned media is widely used for the unbiased characterization of cancer secretomes in vitro. Azide-containing amino acid labeling in combination with click chemistry now facilitates this type of analysis without serum starvation. The modified amino acids, however, are less efficiently incorporated into newly synthesized proteins. Utilizing transcriptome and proteome analysis, we describe here in detail the effects of labeling cells with the methionine analog azidohomoalanin (AHA) on the modulation of gene expression and protein composition. We observe that 11% – 34% of the proteins detected in the secretome were affected by AHA labeling regarding their expression levels in the transcriptome and/or proteome. Performing gene ontology analyses, our results provide a detailed view on the AHA-based induction of cellular stress and apoptosis-related pathways and provide first insights on how this might affect the composition of the secretome on a global scale.
2023-07-05 | GSE211231 | GEO
Project description:BackgroundThe evolution of the full repertoire of proteins encoded in a given genome is mostly driven by gene duplications, deletions, and sequence modifications of existing proteins. Indirect information about relative rates and other intrinsic parameters of these three basic processes is contained in the proteome-wide distribution of sequence identities of pairs of paralogous proteins.ResultsWe introduce a simple mathematical framework based on a stochastic birth-and-death model that allows one to extract some of this information and apply it to the set of all pairs of paralogous proteins in H. pylori, E. coli, S. cerevisiae, C. elegans, D. melanogaster, and H. sapiens. It was found that the histogram of sequence identities p generated by an all-to-all alignment of all protein sequences encoded in a genome is well fitted with a power-law form approximately p-gamma with the value of the exponent gamma around 4 for the majority of organisms used in this study. This implies that the intra-protein variability of substitution rates is best described by the Gamma-distribution with the exponent alpha approximately 0.33. Different features of the shape of such histograms allow us to quantify the ratio between the genome-wide average deletion/duplication rates and the amino-acid substitution rate.ConclusionWe separately measure the short-term ("raw") duplication and deletion rates , which include gene copies that will be removed soon after the duplication event and their dramatically reduced long-term counterparts r(*)dup, r(*)del. High deletion rate among recently duplicated proteins is consistent with a scenario in which they didn't have enough time to significantly change their functional roles and thus are to a large degree disposable. Systematic trends of each of the four duplication/deletion rates with the total number of genes in the genome were analyzed. All but the deletion rate of recent duplicates r(*)del were shown to systematically increase with Ngenes. Abnormally flat shapes of sequence identity histograms observed for yeast and human are consistent with lineages leading to these organisms undergoing one or more whole-genome duplications. This interpretation is corroborated by our analysis of the genome of Paramecium tetraurelia where the p-4 profile of the histogram is gradually restored by the successive removal of paralogs generated in its four known whole-genome duplication events.
| S-EPMC2246104 | biostudies-literature
Project description:Bioinformatic analysis of Escherichia coli proteomes revealed that all possible amino acid triplet sequences occur at their expected frequencies, with four exceptions. Two of the four underrepresented sequences (URSs) were shown to interfere with translation in vivo and in vitro. Enlarging the URS by a single amino acid resulted in increased translational inhibition. Single-molecule methods revealed stalling of translation at the entrance of the peptide exit tunnel of the ribosome, adjacent to ribosomal nucleotides A2062 and U2585. Interaction with these same ribosomal residues is involved in regulation of translation by longer, naturally occurring protein sequences. The E. coli exit tunnel has evidently evolved to minimize interaction with the exit tunnel and maximize the sequence diversity of the proteome, although allowing some interactions for regulatory purposes. Bioinformatic analysis of the human proteome revealed no underrepresented triplet sequences, possibly reflecting an absence of regulation by interaction with the exit tunnel.
| S-EPMC4932979 | biostudies-literature
Project description:Rationale: Myocardial vulnerability to ischemia/reperfusion (I/R) injury is strictly regulated by energy substrate metabolism. Branched chain amino acids (BCAA), consisting of valine, leucine and isoleucine, are a group of essential amino acids that are highly oxidized in the heart. Elevated levels of BCAA have been implicated in the development of cardiovascular diseases; however, the role of BCAA in I/R process is not fully understood. The present study aims to determine how BCAA influence myocardial energy substrate metabolism and to further clarify the pathophysiological significance during cardiac I/R injury. Methods: Parameters of glucose and fatty acid metabolism were measured by seahorse metabolic flux analyzer in adult mouse cardiac myocytes with or without BCAA incubation. Chronic accumulation of BCAA was induced in mice receiving oral BCAA administration. A genetic mouse model with defective BCAA catabolism was also utilized. Mice were subjected to MI/R and the injury was assessed extensively at the whole-heart, cardiomyocyte, and molecular levels. Results: We confirmed that chronic accumulation of BCAA enhanced glycolysis and fatty acid oxidation (FAO) but suppressed glucose oxidation in adult mouse ventricular cardiomyocytes. Oral gavage of BCAA enhanced FAO in cardiac tissues, exacerbated lipid peroxidation toxicity and worsened myocardial vulnerability to I/R injury. Etomoxir, a specific inhibitor of FAO, rescued the deleterious effects of BCAA on I/R injury. Mechanistically, valine, leucine and their corresponding branched chain ?-keto acid (BCKA) derivatives, but not isoleucine and its BCKA derivative, transcriptionally upregulated peroxisome proliferation-activated receptor alpha (PPAR-?). BCAA/BCKA induced PPAR-? upregulation through the general control nonderepresible-2 (GCN2)/ activating transcription factor-6 (ATF6) pathway. Finally, in a genetic mouse model with BCAA catabolic defects, chronic accumulation of BCAA increased FAO in myocardial tissues and sensitized the heart to I/R injury, which could be reversed by adenovirus-mediated PPAR-? silencing. Conclusions: We identify BCAA as an important nutrition regulator of myocardial fatty acid metabolism through transcriptional upregulation of PPAR-?. Chronic accumulation of BCAA, caused by either dietary or genetic factors, renders the heart vulnerable to I/R injury via exacerbating lipid peroxidation toxicity. These data support the notion that BCAA lowering methods might be potentially effective cardioprotective strategies, especially among patients with diseases characterized by elevated levels of BCAA, such as obesity and diabetes.
| S-EPMC7196282 | biostudies-literature
Project description:Relating a protein's sequence to its conformation is a central challenge for both structure prediction and sequence design. Statistical contact potentials, as well as their more descriptive versions that account for side-chain orientation and other geometric descriptors, have served as simplistic but useful means of representing second-order contributions in sequence-structure relationships. Here we ask what happens when a pairwise potential is conditioned on the fully defined geometry of interacting backbones fragments. We show that the resulting structure-conditioned coupling energies more accurately reflect pair preferences as a function of structural contexts. These structure-conditioned energies more reliably encode native sequence information and more highly correlate with experimentally determined coupling energies. Clustering a database of interaction motifs by structure results in ensembles of similar energies and clustering them by energy results in ensembles of similar structures. By comparing many pairs of interaction motifs and showing that structural similarity and energetic similarity go hand-in-hand, we provide a tangible link between modular sequence and structure elements. This link is applicable to structural modeling, and we show that scoring CASP models with structured-conditioned energies results in substantially higher correlation with structural quality than scoring the same models with a contact potential. We conclude that structure-conditioned coupling energies are a good way to model the impact of interaction geometry on second-order sequence preferences.
| S-EPMC8927866 | biostudies-literature
Project description:The amino acid sequence of cystatin, the protein from chicken egg-white that is a tight-binding inhibitor of many cysteine proteinases, is reported. Cystatin is composed of 116 amino acid residues, and the Mr is calculated to be 13 143. No striking similarity to any other known sequence has been detected. The results of computer analysis of the sequence and c.d. spectrometry indicate that the secondary structure includes relatively little alpha-helix (about 20%) and that the remainder is mainly beta-structure.
| S-EPMC1153285 | biostudies-other
Project description:Many prion-forming proteins contain glutamine/asparagine (Q/N) rich domains, and there are conflicting opinions as to the role of primary sequence in their conversion to the prion form: is this phenomenon driven primarily by amino acid composition, or, as a recent computational analysis suggested, dependent on the presence of short sequence elements with high amyloid-forming potential. The argument for the importance of short sequence elements hinged on the relatively-high accuracy obtained using a method that utilizes a collection of length-six sequence elements with known amyloid-forming potential. We weigh in on this question and demonstrate that when those sequence elements are permuted, even higher accuracy is obtained; we also propose a novel multiple-instance machine learning method that uses sequence composition alone, and achieves better accuracy than all existing prion prediction approaches. While we expect there to be elements of primary sequence that affect the process, our experiments suggest that sequence composition alone is sufficient for predicting protein sequences that are likely to form prions. A web-server for the proposed method is available at http://faculty.pieas.edu.pk/fayyaz/prank.html, and the code for reproducing our experiments is available at http://doi.org/10.5281/zenodo.167136.
| S-EPMC5402983 | biostudies-literature