Protein Functional Regions Research Articles

Post-Translational Modifications to Cysteine Residues in Plant Proteins and Their Impact on the Regulation of Metabolism and Signal Transduction.

Cys is one of the least abundant amino acids in proteins. However, it is often highly conserved and is usually found in important structural and functional regions of proteins. Its unique chemical properties allow it to undergo several post-translational modifications, many of which are mediated by reactive oxygen, nitrogen, sulfur, or carbonyl species. Thus, in addition to their role in catalysis, protein stability, and metal binding, Cys residues are crucial for the redox regulation of metabolism and signal transduction. In this review, we discuss Cys post-translational modifications (PTMs) and their role in plant metabolism and signal transduction. These modifications include the oxidation of the thiol group (S-sulfenylation, S-sulfinylation and S-sulfonylation), the formation of disulfide bridges, S-glutathionylation, persulfidation, S-cyanylation S-nitrosation, S-carbonylation, S-acylation, prenylation, CoAlation, and the formation of thiohemiacetal. For each of these PTMs, we discuss the origin of the modifier, the mechanisms involved in PTM, and their reversibility. Examples of the involvement of Cys PTMs in the modulation of protein structure, function, stability, and localization are presented to highlight their importance in the regulation of plant metabolic and signaling pathways.

ATLAS: protein flexibility description from atomistic molecular dynamics simulations.

Dynamical behaviour is one of the most crucial protein characteristics. Despite the advances in the field of protein structure resolution and prediction, analysis and prediction of protein dynamic properties remains a major challenge, mostly due to the low accessibility of data and its diversity and heterogeneity. To address this issue, we present ATLAS, a database of standardised all-atom molecular dynamics simulations, accompanied by their analysis in the form of interactive diagrams and trajectory visualisation. ATLAS offers a large-scale view and valuable insights on protein dynamics for a large and representative set of proteins, by combining data obtained through molecular dynamics simulations with information extracted from experimental structures. Users can easily analyse dynamic properties of functional protein regions, such as domain limits (hinge positions) and residues involved in interaction with other biological molecules. Additionally, the database enables exploration of proteins with uncommon dynamic properties conditioned by their environment such as chameleon subsequences and Dual Personality Fragments. The ATLAS database is freely available at https://www.dsimb.inserm.fr/ATLAS.

Identification of Evolutionary Trajectories Shared across Human Betacoronaviruses.

Comparing the evolution of distantly related viruses can provide insights into common adaptive processes related to shared ecological niches. Phylogenetic approaches, coupled with other molecular evolution tools, can help identify mutations informative on adaptation, although the structural contextualization of these to functional sites of proteins may help gain insight into their biological properties. Two zoonotic betacoronaviruses capable of sustained human-to-human transmission have caused pandemics in recent times (SARS-CoV-1 and SARS-CoV-2), although a third virus (MERS-CoV) is responsible for sporadic outbreaks linked to animal infections. Moreover, two other betacoronaviruses have circulated endemically in humans for decades (HKU1 and OC43). To search for evidence of adaptive convergence between established and emerging betacoronaviruses capable of sustained human-to-human transmission (HKU1, OC43, SARS-CoV-1, and SARS-CoV-2), we developed a methodological pipeline to classify shared nonsynonymous mutations as putatively denoting homoplasy (repeated mutations that do not share direct common ancestry) or stepwise evolution (sequential mutations leading towards a novel genotype). In parallel, we look for evidence of positive selection and draw upon protein structure data to identify potential biological implications. We find 30 candidate mutations, from which 4 (codon sites 18121 [nsp14/residue 28], 21623 [spike/21], 21635 [spike/25], and 23948 [spike/796]; SARS-CoV-2 genome numbering) further display evolution under positive selection and proximity to functional protein regions. Our findings shed light on potential mechanisms underlying betacoronavirus adaptation to the human host and pinpoint common mutational pathways that may occur during establishment of human endemicity.

Determination of the bands of four common animal collagens by SDS-PAGE electrophoresis and the comparative study of their protein functional regions

Determination of the bands of four common animal collagens by SDS-PAGE electrophoresis and the comparative study of their protein functional regions

CysModDB: a comprehensive platform with the integration of manually curated resources and analysis tools for cysteine posttranslational modifications.

The unique chemical reactivity of cysteine residues results in various posttranslational modifications (PTMs), which are implicated in regulating a range of fundamental biological processes. With the advent of chemical proteomics technology, thousands of cysteine PTM (CysPTM) sites have been identified from multiple species. A few CysPTM-based databases have been developed, but they mainly focus on data collection rather than various annotations and analytical integration. Here, we present a platform-dubbed CysModDB, integrated with the comprehensive CysPTM resources and analysis tools. CysModDB contains five parts: (1) 70536 experimentally verified CysPTM sites with annotations of sample origin and enrichment techniques, (2) 21654 modified proteins annotated with functional regions and structure information, (3) cross-references to external databases such as the protein-protein interactions database, (4) online computational tools for predicting CysPTM sites and (5) integrated analysis tools such as gene enrichment and investigation of sequence features. These parts are integrated using a customized graphic browser and a Basket. The browser uses graphs to represent the distribution of modified sites with different CysPTM types on protein sequences and mapping these sites to the protein structures and functional regions, which assists in exploring cross-talks between the modified sites and their potential effect on protein functions. The Basket connects proteins and CysPTM sites to the analysis tools. In summary, CysModDB is an integrated platform to facilitate the CysPTM research, freely accessible via https://cysmoddb.bioinfogo.org/.

Molecular characterization and tissue distribution of nine selenoprotein genes in grass carp Ctenopharyngodon idella and their mRNA expressions in response to high-fat diet and high-fat diet supplemented with selenium

Our previous study has found that selenium (Se) can alleviate lipid accumulation caused by high-fat diet (HFD) in fish. This study aims to explore the selenoproteins (SePs) in grass carp Ctenopharyngodon idella by characterizing cDNAs of nine SeP genes (SELENOF, SELENOM, SELENOS, SELENOP1, SELENOP2, SELENOE, SELENOL, SELENOU1a and SELENOU1b) and measuring their transcriptional activity in response to HFD and HFD supplemented with 0.3mg/Kg and 0.6mg/Kg of Se (HSe 0.3 and HSe 0.6). Firstly, the nine SeP genes in grass carp encoded proteins with conserved functional protein regions in fish and other vertebrates. Secondly, the nine SeP genes except SELENOS showed high expression levels in the hepatopancreas, but in the adipose tissue, only SELENOS, SELENOE and SELENOU1b showed high expression levels. Further, HFD significantly up-regulated the expressions of SELENOF and SELENOS in the hepatopancreas and SELENOM in the adipose tissue of grass carp (P<0.05), but significantly down-regulated the expressions of SELENOU1b in the hepatopancreas, SELENOP2, SELENOE, SELENOL and SELENOU1a in the adipose tissue and SELENOM in the muscle of grass carp (P<0.05). In addition, for the hepatopancreas, the expressions of SELENOS in the HSe 0.3 group and SELENOF, SELENOM and SELENOP2 in the HSe 0.6 group significantly decreased compared with the HFD group (P<0.05). For the adipose tissue, the expressions of SELENOF, SELENOP2, SELENOL, SELENOU1a and SELENOU1b in the HSe 0.3 group and SELENOP2, SELENOE, SELENOU1a and SELENOU1b in the HSe 0.6 group significantly increased compared with the HFD group (P<0.05). In summary, the transcriptional activities of the nine SeP genes were regulated by the HFD and HFD supplemented with Se, indicating the potential role of these genes in the Se regulated lipid metabolism processes in grass carp, which is worthy of in-depth study.

Construction of point mutation rabbits using CRISPR/Cas9.

To establish a rabbit model of proprotein convertase subtilisin/kexin type9 () point mutation with CRISPR/Cas9 gene editing technique. According to the PubMed gene protein data, the PCSK9 protein functional regions of human and rabbit were analyzed by Blast. The 386S (Ser) amino acid functional region of human gene was homologous to the 485S of rabbit gene. Three small guide RNAs and one single-stranded donor oligonucleotide were designed according to the 485S base substitution position and sequence analysis of rabbit gene. The synthetic small guide RNAs, Cas9 mRNA and single-stranded donor oligonucleotide were co-injected into the cytoplasm of rabbit fertilized eggs and the embryos were transferred into the pregnant rabbits. PCR, TA cloning and off-target analysis were performed on the F0 rabbits to identify whether the PCSK9 mutation was successful. Fifteen F0 rabbits were obtained. The sequencing results showed that one of them was PCSK9 point mutation homozygote and two of them were PCSK9 point mutation heterozygotes, and the mutation could be stably inherited. The rabbit model of PCSK9 point mutation was successfully constructed by CRISPR/Cas9 technique, which provides an animal model for exploring the molecular mechanism of impaired PCSK9 function and developing reliable and effective diagnosis and treatment measures.

The Burden of Post-Translational Modification (PTM)-Disrupting Mutations in the Tumor Matrisome.

Simple SummaryMutations are the driving force of the oncogenic process, altering regulatory pathways and leading to uncontrolled cell proliferation. Understanding the occurrence and patterns of mutations is necessary to identify the sequence of events enabling tumor growth and diffusion. Yet, while much is known about mutations in proteins whose actions are exerted inside the cells, much less is known about the extracellular matrix (ECM) and ECM-associated proteins (collectively known as the “matrisome”) whose actions are exerted outside the cells. In particular, while post-translational modifications (PTMs) are critical for the functions of many proteins, both intracellular and in the matrisome, there are no studies evaluating the mutations impacting known PTM sites within matrisome proteins. Here we report on a large Pan-Cancer cohort spanning 32 tumor types and demonstrate the specificities of matrisome PTM-affecting mutations over the rest of the genome, also evidencing features and findings that might be relevant for prognostication and mechanistic understanding of the supportive role of the tumor microenvironment in the tumorigenic process.Background: To evaluate the occurrence of mutations affecting post-translational modification (PTM) sites in matrisome genes across different tumor types, in light of their genomic and functional contexts and in comparison with the rest of the genome. Methods: This study spans 9075 tumor samples and 32 tumor types from The Cancer Genome Atlas (TCGA) Pan-Cancer cohort and identifies 151,088 non-silent mutations in the coding regions of the matrisome, of which 1811 affecting known sites of hydroxylation, phosphorylation, N- and O-glycosylation, acetylation, ubiquitylation, sumoylation and methylation PTM. Results: PTM-disruptive mutations (PTMmut) in the matrisome are less frequent than in the rest of the genome, seem independent of cell-of-origin patterns but show dependence on the nature of the matrisome protein affected and the background PTM types it generally harbors. Also, matrisome PTMmut are often found among structural and functional protein regions and in proteins involved in homo- and heterotypic interactions, suggesting potential disruption of matrisome functions. Conclusions: Though quantitatively minoritarian in the spectrum of matrisome mutations, PTMmut show distinctive features and damaging potential which might concur to deregulated structural, functional, and signaling networks in the tumor microenvironment.

Structural insights into the inhibition of bacterial RecA by naphthalene polysulfonated compounds.

SummaryAs a promising target for alternative antimicrobials, bacterial recombinase A (RecA) protein has attracted much attention for its roles in antibiotic-driven SOS response and mutagenesis. Naphthalene polysulfonated compounds (NPS) such as suramin have previously been explored as antibiotic adjuvants targeting RecA, although the underlying structural bases for RecA-ligand interactions remain obscure. Based on our in silico predictions and documented activity of NPS in vitro, we conclude that the analyzed NPS likely interact with Tyr103 (Y103) and other key residues in the ATPase activity center (pocket A). For validation, we generated recombinant RecA proteins (wild-type versus Y103 mutant) to determine the binding affinities for RecA protein interactions with suramin and underexamined NPS in isothermal titration calorimetry. The corresponding dissociation constants (Kd) ranged from 11.5 to 18.8 μM, and Y103 was experimentally shown to be critical to RecA-NPS interactions.

Potential Pathogenicity Determinants Identified from Structural Proteomics of SARS-CoV and SARS-CoV-2.

Despite SARS-CoV and SARS-CoV-2 being equipped with highly similar protein arsenals, the corresponding zoonoses have spread among humans at extremely different rates. The specific characteristics of these viruses that led to such distinct outcomes remain unclear. Here, we apply proteome-wide comparative structural analysis aiming to identify the unique molecular elements in the SARS-CoV-2 proteome that may explain the differing consequences. By combining protein modeling and molecular dynamics simulations, we suggest nonconservative substitutions in functional regions of the spike glycoprotein (S), nsp1, and nsp3 that are contributing to differences in virulence. Particularly, we explain why the substitutions at the receptor-binding domain of S affect the structure–dynamics behavior in complexes with putative host receptors. Conservation of functional protein regions within the two taxa is also noteworthy. We suggest that the highly conserved main protease, nsp5, of SARS-CoV and SARS-CoV-2 is part of their mechanism of circumventing the host interferon antiviral response. Overall, most substitutions occur on the protein surfaces and may be modulating their antigenic properties and interactions with other macromolecules. Our results imply that the striking difference in the pervasiveness of SARS-CoV-2 and SARS-CoV among humans seems to significantly derive from molecular features that modulate the efficiency of viral particles in entering the host cells and blocking the host immune response.

Identifying Ligand Binding Sites of Proteins using Crystallographic Bfactors and Relative Pocket Sizes

The long-term goal of this project is to develop methods to predict the functional regions of proteins of unknown function. The results of previous studies have suggested that one of the largest pockets on a protein surface is most likely to be the ligand binding site. We tested if adding a measure related to local flexibility would make this prediction more accurate. We tested the hypothesis that considering the relative X-ray crystallographic B-factors (temperature factors) of atoms in a protein structure in addition to the relative sizes of surface pockets can help in identifying the functional regions of proteins.

Identification of Protein Functional Regions.

Protein sequence stores the information relative to both functionality and stability, thus making it difficult to disentangle the two contributions. However, the identification of critical residues for function and stability has important implications for the mapping of the proteome interactions, as well as for many pharmaceutical applications, e. g. the identification of ligand binding regions for targeted pharmaceutical protein design. In this work, we propose a computational method to identify critical residues for protein functionality and stability and to further categorise them in strictly functional, structural and intermediate. We evaluate single site conservation and use Direct Coupling Analysis (DCA) to identify co-evolved residues both in natural and artificial evolution processes. We reproduce artificial evolution using protein design and base our approach on the hypothesis that artificial evolution in the absence of any functional constraint would exclusively lead to site conservation and co-evolution events of the structural type. Conversely, natural evolution intrinsically embeds both functional and structural information. By comparing the lists of conserved and co-evolved residues, outcomes of the analysis on natural and artificial evolution, we identify the functional residues without the need of any a priori knowledge of the biological role of the analysed protein.

Glutamine-walking: Creating reactive substrates for transglutaminase-mediated protein labeling.

Chemically modified proteins are increasingly being tested and approved as therapeutic products. Batch-to-batch homogeneity is crucial to ensure safety and quality of therapeutic products. Highly selective protein modification may be achieved using enzymatic routes. Microbial transglutaminase (mTG) is a robust, easy to use and well-established enzyme that is used at a very large scale in the food industry such that its efficacy and its safety for human consumption are well established. In the context of therapeutic protein modification, mTG should crosslink one or more glutamines on the target protein with an aminated moiety such as a solubilizer, a tracer or a cytotoxic moiety. mTG has the advantage of being unreactive toward the majority of surface-exposed glutamines on most proteins, reducing sample heterogeneity. The caveat is that there may be no reactive glutamine on the target protein, or else a reactive glutamine may be found in a location where its modification compromises function of the target protein. Here we describe the glutamine-walk (Gln-walk), a straightforward method to create a glutamine-substrate site that is reactive to mTG in a target protein. Iterative substitution of single amino acids to a glutamine is followed by facile identification of reactivity with mTG, where covalent labeling of the target with an aminated fluorophore allows visualization of the most reactive modified targets. The approach is empirical; knowledge of the target protein structure and functional regions facilitates application of the method.

Identification of pathogenic variant enriched regions across genes and gene families.

Missense variant interpretation is challenging. Essential regions for protein function are conserved among gene-family members, and genetic variants within these regions are potentially more likely to confer risk to disease. Here, we generated 2871 gene-family protein sequence alignments involving 9990 genes and performed missense variant burden analyses to identify novel essential protein regions. We mapped 2,219,811 variants from the general population into these alignments and compared their distribution with 76,153 missense variants from patients. With this gene-family approach, we identified 465 regions enriched for patient variants spanning 41,463 amino acids in 1252 genes. As a comparison, by testing the same genes individually, we identified fewer patient variant enriched regions, involving only 2639 amino acids and 215 genes. Next, we selected de novo variants from 6753 patients with neurodevelopmental disorders and 1911 unaffected siblings and observed an 8.33-fold enrichment of patient variants in our identified regions (95% C.I. = 3.90-Inf, P-value = 2.72 × 10−11). By using the complete ClinVar variant set, we found that missense variants inside the identified regions are 106-fold more likely to be classified as pathogenic in comparison to benign classification (OR = 106.15, 95% C.I = 70.66-Inf, P-value < 2.2 × 10−16). All pathogenic variant enriched regions (PERs) identified are available online through “PER viewer,” a user-friendly online platform for interactive data mining, visualization, and download. In summary, our gene-family burden analysis approach identified novel PERs in protein sequences. This annotation can empower variant interpretation.

Identification of Functional Protein Regions Through Chimeric Protein Construction.

The goal of this protocol encompasses the design of chimeric proteins in which distinct regions of a protein are replaced by their corresponding sequences in a structurally similar protein, in order to determine the functional importance of these regions. Such chimeras are generated by means of a nested PCR protocol using overlapping DNA fragments and adequately designed primers, followed by their expression within a mammalian system to ensure native secondary structure and post-translational modifications. The functional role of a distinct region is then indicated by a loss of activity of the chimera in an appropriate readout assay. In consequence, regions harboring a set of critical amino acids are identified, which can be further screened by complementary techniques (e.g. site-directed mutagenesis) to increase molecular resolution. Although limited to cases in which a structurally related protein with differing functions can be found, chimeric proteins have been successfully employed to identify critical binding regions in proteins such as cytokines and cytokine receptors. This method is particularly suitable in cases in which the protein's functional regions are not well defined, and constitutes a valuable first step in directed evolution approaches to narrow down the regions of interest and reduce the screening effort involved.

Identification of Functional Protein Regions Through Chimeric Protein Construction

Identification of Functional Protein Regions Through Chimeric Protein Construction

ProteinExplorer: A Repository-Scale Resource for Exploration of Protein Detection in Public Mass Spectrometry Data Sets.

High-throughput tandem mass spectrometry has enabled the detection and identification of over 75% of all proteins predicted to result in translated gene products in the human genome. In fact, the galloping rate of data acquisition and sharing of mass spectrometry data has led to the current availability of many tens of terabytes of public data in thousands of human data sets. The systematic reanalysis of these public data sets has been used to build a community-scale spectral library of 2.1 million precursors for over 1 million unique sequences from over 19,000 proteins (including spectra of synthetic peptides). However, it has remained challenging to find and inspect spectra of peptides covering functional protein regions or matching novel proteins. ProteinExplorer addresses these challenges with an intuitive interface mapping tens of millions of identifications to functional sites on nearly all human proteins while maintaining provenance for every identification back to the original data set and data file. Additionally, ProteinExplorer facilitates the selection and inspection of HPP-compliant peptides whose spectra can be matched to spectra of synthetic peptides and already includes HPP-compliant evidence for 107 missing (PE2, PE3, and PE4) and 23 dubious (PE5) proteins. Finally, ProteinExplorer allows users to rate spectra and to contribute to a community library of peptides entitled PrEdict (Protein Existance dictionary) mapping to novel proteins but whose preliminary identities have not yet been fully established with community-scale false discovery rates and synthetic peptide spectra. ProteinExplorer can be now be accessed at https://massive.ucsd.edu/ProteoSAFe/protein_explorer_splash.jsp .

Occurrence of grapevine trunk diseases affecting the native cultivar Pedro Ximénez in southern Spain

‘Pedro Ximenez’ is a native grapevine cultivar from Cordoba province (Andalusia region, southern Spain), which has been seriously affected by fungal trunk pathogens causing general decline along the last decade. However, the occurrence of grapevine trunk diseases (GTDs) in Andalusia region has not been studied yet. Therefore, the main goal of this study was to evaluate the occurrence of GTDs affecting ‘Pedro Ximenez’, and to characterize the causal agents by morphological and molecular methods. Between 2016 and 2017, 25 commercial vineyards of cv. Pedro Ximenez showing decline symptoms were surveyed. Fungal isolations were done and 23 representative isolates of the fungal trunk pathogens associated with the different GTDs (black-foot and Petri disease, Botryosphaeria and eutypa dieback, and esca) were selected according to colony colour and mycelial growth development. Colony colour, mycelial growth, and conidial characteristics were defined. The effect of temperature on mycelial growth was evaluated. Phylogenetic analyses of ribosomal genes (ITS) and functional protein regions (ACT, HIS, TEF, TUB) were preformed to confirm their identification. The especies Cadophora luteo-olivacea, Cryptovalsa ampelina, Dactylonectria alcacerensis, Da. novozelandica, Diplodia corticola, D. mutila, D. seriata, Eutypa lata, Fomitiporia mediterranea, Ilyonectria liriodendri, Neofusicoccum mediterraneum, N. parvum, Phaeoacremonium iranianum, Pm. minimum and Phaeomoniella chlamydospora were identified. Despite grapevine fungal trunk pathogens being well known in the main grape growing areas worldwide, this present study is relevant because it has been focused in the native cultivar Pedro Ximenez, improving our knowledge about aetiology of GTDs in southern Spain towards make decisions about management strategies preventing infections.

Discovering Patterns From Sequences Using Pattern-Directed Aligned Pattern Clustering.

Functional region identification is of fundamental importance for protein sequences analysis. Such knowledge provides better scientific understanding and could assist drug discovery. Up-to-date, domain annotation is one approach, but it needs to leverage existing databases. For de novo discovery, motif discovery locates and aligns locally homologous sub-sequences to obtain a position-weight matrix (PWM), which is a fixed-length representation model, whereas protein functional region size varies. It thus requires computational expensive exhaustive search to obtain a PWM with width of optimal range. This paper presents a new method known as pattern-directed aligned pattern clustering (PD-APCn) to discover and align patterns in conserved protein functional regions. It adopts aligned pattern cluster (APC) with patterns of variable length and strong support to direct the incremental APC expansion. It allows substitution and frame-shift mutations until a robust termination condition is reached. The concept of breakpoint gap is introduced to identify spots of mutations, such as substitution and frame shifts. Experiments on synthetic data sets with different sizes and noise levels showed that PD-APCn outperforms MEME with much higher recall and Fmeasure and computational speed 665 times faster that MEME. When applying to Cytochrome C and Ubiquitin families, it found all key binding sites within the APCs.

Coding and functional defect region prediction of placental protein in an embryo cell of first trimester using ANN approach

The protein coding and functional regions in DNA sequences has become an exciting task in bioinformatics. In particular, the coding region has a 3-base periodicity, which helps for exon identification. Many signal processing tools and techniques have been successfully applied to identify tasks, but still need to be improved in this direction. In our work, we employ ANN classifier to predict coding and functional region of proteinin human embryo cell protein in first trimester, and evaluate their performances according to the comparison energy levels of coding region. The obtained from the threshold energy level, results show that in a box plot finally predict the mutation.