Common Structural Motif Research Articles

Putative staphylococcal enterotoxin possesses two common structural motifs for MHC-II binding

Staphylococcus aureus has become a significant cause of health risks in humankind. Staphylococcal superantigens (SAgs) or enterotoxins are the key virulent factors that can exhibit acute diseases to severe life-threatening conditions. Recent literature reports S. aureus has steadily gained new enterotoxin genes over the past few decades. In spite of current knowledge of the established SAgs, several questions on putative enterotoxins are still remaining unanswered. Keeping that in mind, this study sheds light on a putative enterotoxin SEl26 to characterize its structural and functional properties. In-silico analyses indicate its close relation with the conventional SAgs, especially the zinc-binding SAgs. Additionally, important residues that are vital for the T-cell receptor (TcR) and major histocompatibility complex class II (MHC-II) interaction were predicted and compared with established SAgs. Besides, our biochemical analyses exhibited the binding of this putative enterotoxin with MHC-II, followed by regulating pro-inflammatory and anti-inflammatory cytokines.

Spatially embedded recurrent neural networks reveal widespread links between structural and functional neuroscience findings

Brain networks exist within the confines of resource limitations. As a result, a brain network must overcome the metabolic costs of growing and sustaining the network within its physical space, while simultaneously implementing its required information processing. Here, to observe the effect of these processes, we introduce the spatially embedded recurrent neural network (seRNN). seRNNs learn basic task-related inferences while existing within a three-dimensional Euclidean space, where the communication of constituent neurons is constrained by a sparse connectome. We find that seRNNs converge on structural and functional features that are also commonly found in primate cerebral cortices. Specifically, they converge on solving inferences using modular small-world networks, in which functionally similar units spatially configure themselves to utilize an energetically efficient mixed-selective code. Because these features emerge in unison, seRNNs reveal how many common structural and functional brain motifs are strongly intertwined and can be attributed to basic biological optimization processes. seRNNs incorporate biophysical constraints within a fully artificial system and can serve as a bridge between structural and functional research communities to move neuroscientific understanding forwards.

Medicinal-Chemistry-Driven Approach to 2-Substituted Benzoxazole-Estradiol Chimeras: Synthesis, Anticancer Activity, and Early ADME Profile.

The efficient synthesis of novel estradiol-based A-ring-fused oxazole derivatives, which can be considered as benzoxazole-steroid domain-integrated hybrids containing a common benzene structural motif, is described. The target compounds were prepared from steroidal 2-aminophenol precursors by heterocycle formation or functional group interconversion (FGI) strategies. According to 2D projection-based t-distributed stochastic neighbor embedding (t-SNE), the novel molecules were proved to represent a new chemical space among steroid drugs. They were characterized based on critical physicochemical parameters using in silico and experimental data. The performance of the compounds to inhibit cell proliferation was tested on four human cancer cell lines and non-cancerous cells. Further examinations were performed to reveal IC50 and lipophilic ligand efficiency (LLE) values, cancer cell selectivity, and apoptosis-triggering features. Pharmacological tests and LLE metric revealed that some derivatives, especially the 2-(4-ethylpiperazin-1-yl)oxazole derivative exhibit strong anticancer activity and trigger the apoptosis of cancer cells with relatively low promiscuity risk similarly to the structurally most closely-related and intensively studied anticancer agent, 2-methoxy-estradiol.

Infectious Bronchitis Virus (Gammacoronavirus) in Poultry: Genomic Architecture, Post-Translational Modifications, and Structural Motifs

Infectious bronchitis virus (IBV) is an avian coronavirus (CoV) that belongs to the genus Gammacoronavirus and has been listed as an important disease by the World Organization for Animal Health (WOAH). It causes highly contagious respiratory, reproductive, and renal diseases in commercial poultry farms. Multiple IBV serotypes and genotypes have been identified in many countries and many detected variants do not provide cross-protection against infection, resulting in repeated outbreaks and significant economic losses worldwide. In addition, the high genetic mutations and recombination events in the prominent genomic regions of IBV, particularly in the spike glycoprotein (S) and nucleocapsid (N) proteins, are directly involved in the evolutionary processes of IBV and lead to increased pathogenicity and tissue tropism. The characterization of the different genotypes and the relationship between the structure, function, post-translational modifications (PTMs), and structural motifs will elucidate the mechanisms that promote replication and pathogenicity and affect the host’s immune response during infection. In this review, we discuss the molecular features of various IBV genes and proteins that contribute to the infection process. We also highlight the common PTMs and structural motifs that occur during protein synthesis and are essential components of IBV ecology.

Creation of a milk oligosaccharide database, MilkOligoDB, reveals common structural motifs and extensive diversity across mammals

The carbohydrate fraction of most mammalian milks contains a variety of oligosaccharides that encompass a range of structures and monosaccharide compositions. Human milk oligosaccharides have received considerable attention due to their biological roles in neonatal gut microbiota, immunomodulation, and brain development. However, a major challenge in understanding the biology of milk oligosaccharides across other mammals is that reports span more than 5 decades of publications with varying data reporting methods. In the present study, publications on milk oligosaccharide profiles were identified and harmonized into a standardized format to create a comprehensive, machine-readable database of milk oligosaccharides across mammalian species. The resulting database, MilkOligoDB, includes 3193 entries for 783 unique oligosaccharide structures from the milk of 77 different species harvested from 113 publications. Cross-species and cross-publication comparisons of milk oligosaccharide profiles reveal common structural motifs within mammalian orders. Of the species studied, only chimpanzees, bonobos, and Asian elephants share the specific combination of fucosylation, sialylation, and core structures that are characteristic of human milk oligosaccharides. However, agriculturally important species do produce diverse oligosaccharides that may be valuable for human supplementation. Overall, MilkOligoDB facilitates cross-species and cross-publication comparisons of milk oligosaccharide profiles and the generation of new data-driven hypotheses for future research.

Triplex-Forming Peptide Nucleic Acid Controls Dynamic Conformations of RNA Bulges.

RNA folding is driven by the formation of double-helical segments interspaced by loops of unpaired nucleotides. Among the latter, bulges formed by one or several unpaired nucleotides are one of the most common structural motifs that play an important role in stabilizing RNA-RNA, RNA-protein, and RNA-small molecule interactions. Single-nucleotide bulges can fold in alternative structures where the unpaired nucleobase is either looped-out (flexible) in a solvent or stacked-in (intercalated) between the base pairs. In the present study, we discovered that triplex-forming peptide nucleic acids (PNAs) had unusually high affinity for single-purine-nucleotide bulges in double-helical RNA. Depending on the PNA's sequence, the triplex formation shifted the equilibrium between looped-out and stacked-in conformations. The ability to control the dynamic equilibria of RNA's structure will be an important tool for studying structure-function relationships in RNA biology and may have potential in novel therapeutic approaches targeting disease-related RNAs.

Triplet Pairing Mechanisms from Hund's-Kondo Models: Applications to UTe_{2} and CeRh_{2}As_{2}.

Observing that several U and Ce based candidate triplet superconductors share a common structural motif, with pairs of magnetic atoms separated by an inversion center, we hypothesize a triplet pairing mechanism based on an interplay of Hund's and Kondo interactions that is unique to this structure. In the presence of Hund's interactions, valence fluctuations generate a triplet superexchange between electrons and local moments. The offset from the center of symmetry allows spin-triplet pairs formed by the resulting Kondo effect to delocalize onto the Fermi surface, precipitating superconductivity. We demonstrate this mechanism within a minimal two-channel Kondo lattice model and present support for this pairing mechanism from existing experiments.

Phytoactive Aryl Carbamates and Ureas as Cytokinin-like Analogs of EDU

Ureas, carbamates and oxamates are rather common structural motifs. They are present in both natural and synthetic compounds that exhibit a wide spectrum of biological activity. These derivatives of carbonic and oxalic acids are regularly employed as the basic structural elements in hybrid molecule synthesis, as well as in organic synthesis in general. A series of unsymmetrical hybrid compounds (E1–E4) has been synthesized, with core imidazolidin-2-one and aryl moieties as urea and carbamate derivatives. Plant growth regulatory activity of these compounds was studied with respect to their influence on germination, growth and development of wheat (Triticum aestivum L.) seeds in laboratory and field tests. Their effect on drought resistance concentrations as low as 4 × 10−7 M was established. Compounds E1 and E4 have shown higher growth-regulating activity than standard thidiazuron and CCC.

BpRNA-align: improved RNA secondary structure global alignment for comparing and clustering RNA structures.

Ribonucleic acid (RNA) is a polymeric molecule that is fundamental to biological processes, with structure being more highly conserved than primary sequence and often key to its function. Advances in RNA structure characterization have resulted in an increase in the number of accurate secondary structures. The task of uncovering common RNA structural motifs with a collective function through structural comparison, providing a level of similarity, remains challenging and could be used to improve RNA secondary structure databases and discover new RNA families. In this work, we present a novel secondary structure alignment method, bpRNA-align. bpRNA-align is a customized global structural alignment method, utilizing an inverted (gap extend costs more than gap open) and context-specific affine gap penalty along with a structural, feature-specific substitution matrix to provide similarity scores. We evaluate our similarity scores in comparison to other methods, using affinity propagation clustering, applied to a benchmarking data set of known structure types. bpRNA-align shows improvement in clustering performance over a broad range of structure types.

Squid Skin Cell-Inspired Refractive Index Mapping of Cells, Vesicles, and Nanostructures

The fascination with the optical properties of naturally occurring systems has been driven in part by nature's ability to produce a diverse palette of vibrant colors from a relatively small number of common structural motifs. Within this context, some cephalopod species have evolved skin cells called iridophores and leucophores whose constituent ultrastructures reflect light in different ways but are composed of the same high refractive index material─a protein called reflectin. Although such natural optical systems have attracted much research interest, measuring the refractive indices of biomaterial-based structures across multiple different environments and establishing theoretical frameworks for accurately describing the obtained refractive index values has proven challenging. Herein, we employ a synergistic combination of experimental and computational methodologies to systematically map the three-dimensional refractive index distributions of model self-assembled reflectin-based structures both in vivo and in vitro. When considered together, our findings may improve understanding of squid skin cell functionality, augment existing methods for characterizing protein-based optical materials, and expand the utility of emerging holotomographic microscopy techniques.

Ruthenium-catalysed α-prenylation of ketones using prenol.

Prenol and isoprenoids are common structural motifs in biological systems and possess diverse applications. An unprecedented direct catalytic prenylation of ketones using prenol is attained. This C-C bond formation reaction requires only a ruthenium pincer catalyst and a base, and H2O is the only byproduct.

Structural similarities between SAM and ATP recognition motifs and detection of ATP binding in a SAM binding DNA methyltransferase

S-adenosylmethionine (SAM) is a ubiquitous co-factor that serves as a donor for methylation reactions and additionally serves as a donor of other functional groups such as amino and ribosyl moieties in a variety of other biochemical reactions. Such versatility in function is enabled by the ability of SAM to be recognized by a wide variety of protein molecules that vary in their sequences and structural folds. To understand what gives rise to specific SAM binding in diverse proteins, we set out to study if there are any structural patterns at their binding sites. A comprehensive analysis of structures of the binding sites of SAM by all-pair comparison and clustering, indicated the presence of 4 different site-types, only one among them being well studied. For each site-type we decipher the common minimum principle involved in SAM recognition by diverse proteins and derive structural motifs that are characteristic of SAM binding. The presence of the structural motifs with precise three-dimensional arrangement of amino acids in SAM sites that appear to have evolved independently, indicates that these are winning arrangements of residues to bring about SAM recognition. Further, we find high similarity between one of the SAM site types and a well known ATP binding site type. We demonstrate using in vitro experiments that a known SAM binding protein, HpyAII.M1, a type 2 methyltransferase can bind and hydrolyse ATP. We find common structural motifs that explain this, further supported through site-directed mutagenesis. Observation of similar motifs for binding two of the most ubiquitous ligands in multiple protein families with diverse sequences and structural folds presents compelling evidence at the molecular level in favour of convergent evolution.

Characterizing the Conformational Free-Energy Landscape of RNA Stem-Loops Using Single-Molecule Field-Effect Transistors.

We have developed and used single-molecule field-effect transistors (smFETs) to characterize the conformational free-energy landscape of RNA stem-loops. Stem-loops are one of the most common RNA structural motifs and serve as building blocks for the formation of complex RNA structures. Given their prevalence and integral role in RNA folding, the kinetics of stem-loop (un)folding has been extensively characterized using both experimental and computational approaches. Interestingly, these studies have reported vastly disparate timescales of (un)folding, which has been interpreted as evidence that (un)folding of even simple stem-loops occurs on a highly rugged conformational energy landscape. Because smFETs do not rely on fluorophore reporters of conformation or mechanical (un)folding forces, they provide a unique approach that has allowed us to directly monitor tens of thousands of (un)folding events of individual stem-loops at a 200 μs time resolution. Our results show that under our experimental conditions, stem-loops (un)fold over a 1-200 ms timescale during which they transition between ensembles of unfolded and folded conformations, the latter of which is composed of at least two sub-populations. The 1-200 ms timescale of (un)folding we observe here indicates that smFETs report on complete (un)folding trajectories in which unfolded conformations of the RNA spend long periods of time wandering the free-energy landscape before sampling one of several misfolded conformations or the natively folded conformation. Our findings highlight the extremely rugged landscape on which even the simplest RNA structural elements fold and demonstrate that smFETs are a unique and powerful approach for characterizing the conformational free-energy of RNA.

Genome-Wide Characterization and Function Analysis of ZmERD15 Genes’ Response to Saline Stress in Zea mays L.

Early responsive dehydration (ERD) genes can be rapidly induced by dehydration. ERD15 genes have been confirmed to regulate various stress responses in plants. However, the maize ERD15 members have not been characterized. In the present study, a total of five ZmERD15 genes were identified from the maize genome and named ZmERD15a, ZmERD15b, ZmERD15c, ZmERD15d, and ZmERD15e. Subsequently, their protein properties, gene structure and duplication, chromosomal location, cis-acting elements, subcellular localization, expression pattern, and over-expression in yeast were analyzed. The results showed that the ZmERD15 proteins were characterized by a similar size (113-159 aa) and contained a common domain structure, with PAM2 and adjacent PAE1 motifs followed by an acidic region. The ZmERD15 proteins exhibited a close phylogenetic relationship with OsERD15s from rice. Five ZmERD15 genes were distributed on maize chromosomes 2, 6, 7, and 9 and showed a different exon-intron organization and were expanded by duplication. Besides, the promoter region of the ZmERD15s contained abundant cis-acting elements that are known to be responsive to stress and hormones. Subcellular localization showed that ZmERD15b and ZmERD15c were localized in the nucleus. ZmERD15a and ZmERD15e were localized in the nucleus and cytoplasm. ZmERD15d was localized in the nucleus and cell membrane. The results of the quantitative real-time PCR (qRT-PCR) showed that the expression of the ZmERD15 genes was regulated by PEG, salinity, and ABA. The heterologous expression of ZmERD15a, ZmERD15b, ZmERD15c, and ZmERD15d significantly enhanced salt tolerance in yeast. In summary, a comprehensive analysis of ZmERD15s was conducted in the study. The results will provide insights into further dissecting the biological function and molecular mechanism of ZmERD15s regulating of the stress response in maize.

Tailoring Donor‐Acceptor Emitters to Minimise Localisation Induced Quenching of Thermally Activated Delayed Fluorescence

AbstractBy inverting the common structural motif of thermally activated delayed fluorescence (TADF) materials to a rigid donor core and multiple peripheral acceptors, it has been shown possible to achieve both a reverse intersystem crossing (rISC) rate 1×107 s−1 and a unity photoluminescence quantum yield [Dos Santos et al. Adv. Sci. 5 (2018) 1700989]. However, the rISC rate in this motif is quenched by localisation of the excited state electronic structure which causes in‐equivalence between the peripheral acceptors. In this paper, we explore a series of related molecular targets which seek to reduce the effect of localisation on the rISC rates. This includes structures that contain donors exhibiting three‐fold or four‐fold symmetry and different degrees of steric hindrance around the donor‐acceptor bond with the objective of using steric hindrance to exert finer conformational control of the excited state dynamics to enhance functional properties. We demonstrate that a triazatruxene central donor is most effective for TADF owing to the energetic position of the locally excited state, while cyano‐benzonitriles are the most effective acceptors for reducing the effect of localisation on the electronic structure. These also push the emission into the blue region of the spectrum, opening the possibilities for this to be a pathway to develop efficient blue TADF emitters.

Network Science and Group Fusion Similarity-Based Searching to Explore the Chemical Space of Antiparasitic Peptides.

Antimicrobial peptides (AMPs) have appeared as promising compounds to treat a wide range of diseases. Their clinical potentialities reside in the wide range of mechanisms they can use for both killing microbes and modulating immune responses. However, the hugeness of the AMPs' chemical space (AMPCS), represented by more than 1065 unique sequences, has represented a big challenge for the discovery of new promising therapeutic peptides and for the identification of common structural motifs. Here, we introduce network science and a similarity searching approach to discover new promising AMPs, specifically antiparasitic peptides (APPs). We exploited the network-based representation of APPs' chemical space (APPCS) to retrieve valuable information by using three network types: chemical space (CSN), half-space proximal (HSPN), and metadata (METN). Some centrality measures were applied to identify in each network the most important and nonredundant peptides. Then, these central peptides were considered as queries (Qs) in group fusion similarity-based searches against a comprehensive collection of known AMPs, stored in the graph database StarPepDB, to propose new potential APPs. The performance of the resulting multiquery similarity-based search models (mQSSMs) was evaluated in five benchmarking data sets of APP/non-APPs. The predictions performed by the best mQSSM showed a strong-to-very-strong performance since their external Matthews correlation coefficient (MCC) values ranged from 0.834 to 0.965. Outstanding MCC values (>0.85) were attained by the mQSSM with 219 Qs from both networks CSN and HSPN with 0.5 as similarity threshold in external data sets. Then, the performance of our best mQSSM was compared with the APPs prediction servers AMPDiscover and AMPFun. The proposed model showed its relevance by outperforming state-of-the-art machine learning models to predict APPs. After applying the best mQSSM and additional filters on the non-APP space from StarPepDB, 95 AMPs were repurposed as potential APP hits. Due to the high sequence diversity of these peptides, different computational approaches were applied to identify relevant motifs for searching and designing new APPs. Lastly, we identified 11 promising APP lead candidates by using our best mQSSMs together with diversity-based network analyses, and 24 web servers for activity/toxicity and drug-like properties. These results support that network-based similarity searches can be an effective and reliable strategy to identify APPs. The proposed models and pipeline are freely available through the StarPep toolbox software at http://mobiosd-hub.com/starpep.

Regioselective reductive transamination of peptidic amides enabled by a dual Zr(IV)–H catalysis

<h2>Summary</h2> An amide group, which is a common structural motif of peptides and biologically active molecules, is a highly attractive target for catalytic transformations. Despite its high synthetic potential, the chemical inertness of the amide bond, owing to its resonance stabilization, has rendered this approach challenging. Existing catalytic modes essentially include metal-catalyzed carbon–nitrogen bond activation, transamidation, and catalytic amide reduction. Herein, we report an unprecedented protocol of catalytic reductive transamination of amides to amines of exchanged identities. Through the intermediacy of aminals, combinations of amides with a wide range of external amines lead to a variety of mono- and diamines in good yields with high compatibility of functional groups and retentions of chirality. Regioselective post-modifications of oligomeric peptide derivatives bearing multiple amide motifs have also been realized, and the origin of site-selectivity has been explained by both experimental studies together with DFT calculations.

Photo-triggered sustainable synthesis of quinazolinone derivatives using visible light active exfoliated g-C3N4/Cu3TiO4 as a heterogeneous photocatalyst

Quinazolinone and its heterocyclic compounds are widely used as anti-viral, anti-bacterial, anti-cancer, and other therapeutic medicines, making them common structural motifs in a variety of natural products. Using photocatalysis, it is possible to make derivatives of imidazo thiazolo quinazolinones in a sustainable way. As demonstrated in this study, Cu3TiO4 nanoparticles were successfully synthesised using Citrus Limon juice extract as a capping agent. Cu3TiO4 nanoparticles are supported on exfoliated g-C3N4 nanosheets (CNCT) nanocomposite and characterized by using XRD, UV-DRS, PL, TGA, and EDX analysis. The CNCT nanocomposite has a bandgap of 2.64 eV, indicating that the photocatalyst has been active in the visible region. The CNCT photocatalyst showed excellent activity and produced a high yield of quinazolinone derivatives. The photocatalyst was easily separated from the reaction and was utilized for the next five runs without appreciable loss in photocatalytic performance. This study offers a quick and reliable way to obtain N-heterocycles with promising uses in medicinal and photocatalytic applications.

The mouse claustrum synaptically connects cortical network motifs.

Spatially distant areas of the cerebral cortex coordinate their activity into networks that are integral to cognitive processing. A common structural motif of cortical networks is co-activation of frontal and posterior cortical regions. The neural circuit mechanisms underlying such widespread inter-areal cortical coordination are unclear. Using a discovery based functional magnetic resonance imaging (fMRI) approach in mouse, weobserve frontal and posterior cortical regions that demonstrate significant functional connectivity with the subcortical nucleus, the claustrum. Examining whether the claustrum synaptically supports such frontoposterior cortical network architecture, we observe cortico-claustro-cortical circuits reflecting the fMRI data: significant trans-claustral synaptic connectivity from frontal cortices to posteriorly lying sensory and sensory association cortices contralaterally. These data reveal discrete cortical pathways through the claustrum that are positioned to support cortical network motifs central to cognitive control functions and add to the canon of major extended cortico-subcortico-cortical systems in the mammalian brain.

The Landscape of Potential Small and Drug Substance Related Nitrosamines in Pharmaceuticals

This article reports the outcome of an in silico analysis of more than 12,000 small molecule drugs and drug impurities, identifying the nitrosatable structures, assessing their potential to form nitrosamines under relevant conditions and the challenges to determine compound-specific AIs based on data available or read-across approaches for these nitrosamines and their acceptance by health authorities. Our data indicate that the presence of nitrosamines in pharmaceuticals is likely more prevalent than originally expected. In total, 40.4 % of the analyzed APIs and 29.6 % of the API impurities are potential nitrosamine precursors. Most structures identified through our workflow could form complex API-related nitrosamines, so-called nitrosamine drug substance related impurities (NDSRIs), although we also found structures that could release the well-known small and potent nitrosamines NDMA, NDEA, and others. Due to common structural motifs including secondary or tertiary amine moieties, whole essential drug classes such as beta blockers and ACE inhibitors are at risk. To avoid the risk of drug shortages or even the complete loss of therapeutic options, it will be essential that the well-established ICH M7 principles remain applicable for nitrosamines and that that the industry and regulatory authorities keep an open communication not only about the science but also to make sure there is a good balance between risk and benefit to patients.