Structural Annotation Research Articles

An eco friendly approach for the development of a dipeptide based anti-TB drug nanocomposites: A greener approach in drug delivery system for pulmonary delivery

The conventional anti tubercular (anti-TB) treatment strategies constitute challenges in terms of patient compliance and treatment outcomes. Nano-therapeutics is an emerging field with increasing demand for the therapeutic management of tuberculosis (TB) and the challenges over acquired drug toxicity and poor availability. Nevertheless, studies based on nanopeptide drug carrier for the delivery of anti-TB drugs are scanty. The present work emphasizes on the development of a nanocarrier system through hydrothermal process for encapsulating anti-TB drugs (rifampicin, isoniazid, pyrazinamide, ethambutol) using carnosine dipeptide for the potential therapeutic application. The carnosine-anti-TB drug nanocomposites were synthesized by treating native carnosine and anti-TB drugs at an equal ratio (1:1) incubated at 65°C for 30 min (pH 5.3). The hybrid clusters were freeze dried and used further for characterization (physiochemical, biological, morphology and in silico methods). The structural and functional annotations of carnosine and anti-TB drug nanocomposites were confirmed from its terminal amine absorption stretching’s and its amino group fingerprinting regions. The homogenous nature of carnosine-anti-TB drug complexes in solutions was demonstrated with the particle size (>1 μm), that is suitable for macrophage uptake. SEM analysis demonstrated the interactions and functional group orientation between carnosine and anti-TB drugs during the self-assembly process. The drug release profile indicated that the carnosine-drug conjugation promoted the sustained release compared to free drugs. The quantum mechanical calculations define the structural modelling of drugs with carnosine to obtain a stable energy-minimized conformation. To conclude, the developed carnosine- anti-TB drug nanoclusters with enhanced stability and uniformity in size makes them suitable for macrophage uptake and targeted delivery approaches during TB treatment.

Giants' cooperation: a draft genome of the giant ciliate Muniziella cunhai suggests its ecological role in the capybara's digestive metabolism.

Several hundred ciliate species live in animals' guts as a part of their microbiome. Among them, Muniziella cunhai (Trichostomatia, Pycnotrichidae), the largest described ciliate, is found exclusively associated with Hydrochoerus hydrochaeris (capybara), the largest known rodent reaching up to 90 kg. Here, we present the sequence, structural and functional annotation of this giant microeukaryote macronuclear genome and discuss its phylogenetic placement. The 85 Mb genome is highly AT rich (GC content 25.71 %) and encodes a total of 11 397 protein-coding genes, of which 2793 could have their functions predicted with automated functional assignments. Functional annotation showed that M. cunhai can digest recalcitrant structural carbohydrates, non-structural carbohydrates, and microbial cell walls, suggesting a role in diet metabolization and in microbial population control in the capybara's intestine. Moreover, the phylogenetic placement of M. cunhai provides insights on the origins of gigantism in the subclass Trichostomatia.

Predicting glycan structure from tandem mass spectrometry via deep learning

Glycans constitute the most complicated post-translational modification, modulating protein activity in health and disease. However, structural annotation from tandem mass spectrometry (MS/MS) data is a bottleneck in glycomics, preventing high-throughput endeavors and relegating glycomics to a few experts. Trained on a newly curated set of 500,000 annotated MS/MS spectra, here we present CandyCrunch, a dilated residual neural network predicting glycan structure from raw liquid chromatography–MS/MS data in seconds (top-1 accuracy: 90.3%). We developed an open-access Python-based workflow of raw data conversion and prediction, followed by automated curation and fragment annotation, with predictions recapitulating and extending expert annotation. We demonstrate that this can be used for de novo annotation, diagnostic fragment identification and high-throughput glycomics. For maximum impact, this entire pipeline is tightly interlaced with our glycowork platform and can be easily tested at https://colab.research.google.com/github/BojarLab/CandyCrunch/blob/main/CandyCrunch.ipynb. We envision CandyCrunch to democratize structural glycomics and the elucidation of biological roles of glycans.

FURNA: A database for functional annotations of RNA structures.

Despite the increasing number of 3D RNA structures in the Protein Data Bank, the majority of experimental RNA structures lack thorough functional annotations. As the significance of the functional roles played by noncoding RNAs becomes increasingly apparent, comprehensive annotation of RNA function is becoming a pressing concern. In response to this need, we have developed FURNA (Functions of RNAs), the first database for experimental RNA structures that aims to provide a comprehensive repository of high-quality functional annotations. These include Gene Ontology terms, Enzyme Commission numbers, ligand-binding sites, RNA families, protein-binding motifs, and cross-references to related databases. FURNA is available at https://seq2fun.dcmb.med.umich.edu/furna/ to enable quick discovery of RNA functions from their structures and sequences.

Melodia: A Python Library for Protein Structure Analysis.

Analysing protein structure similarities is an important step in protein engineering and drug discovery. Methodologies that are more advanced than simple RMSD are available but often require extensive mathematical or computational knowledge for implementation. Grouping and optimising such tools in an efficient open-source library increases accessibility and encourages the adoption of more advanced metrics. Melodia is a Python library with a complete set of components devised for describing, comparing and analysing the shape of protein structures using differential geometry of three-dimensional curves and knot theory. It can generate robust geometric descriptors for thousands of shapes in just a few minutes. Those descriptors are more sensitive to structural feature variation than RMSD deviation. Melodia also incorporates sequence structural annotation and three-dimensional visualisations. Melodia is an open-source Python library freely available on https://github.com/rwmontalvao/Melodia_py, along with interactive Jupyter Notebook tutorials. Supplementary data are available at Bioinformatics online.

Describing and Sharing Molecular Visualizations Using the MolViewSpec Toolkit.

With the ever-expanding toolkit of molecular viewers, the ability to visualize macromolecular structures has never been more accessible. Yet, the idiosyncratic technical intricacies across tools and the integration complexities associated with handling structure annotation data present significant barriers to seamless interoperability and steep learning curves for many users. The necessity for reproducible data visualizations is at the forefront of the current challenges. Recently, we introduced MolViewSpec (homepage: https://molstar.org/mol-view-spec/, GitHub project: https://github.com/molstar/mol-view-spec), a specification approach that defines molecular visualizations, decoupling them from the varying implementation details of different molecular viewers. Through the protocols presented herein, we demonstrate how to use MolViewSpec and its 3D view-building Python library for creating sophisticated, customized 3D views covering all standard molecular visualizations. MolViewSpec supports representations like cartoon and ball-and-stick with coloring, labeling, and applying complex transformations such as superposition to any macromolecular structure file in mmCIF, BinaryCIF, and PDB formats. These examples showcase progress towards reusability and interoperability of molecular 3D visualization in an era when handling molecular structures at scale is a timely and pressing matter in structural bioinformatics as well as research and education across the life sciences. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Creating a MolViewSpec view using the MolViewSpec Python package Basic Protocol 2: Creating a MolViewSpec view with reference to MolViewSpec annotation files Basic Protocol 3: Creating a MolViewSpec view with labels and other advanced features Support Protocol 1: Computing rotation and translation vectors Support Protocol 2: Creating a MolViewSpec annotation file.

SrpELTeC: A Serbian Literary Corpus for Distant Reading

The article presents SrpELTeC, a corpus developed within the COST action Distant Reading for European Literary History (CA16204). All novels in SrpELTeC were selected, prepared, and annotated using the common principles established for all language collections in the European Literary Text Collection (ELTeC). The challenges and solutions in preparing SrpELTeC from scratch are outlined. All novels were manually encoded in TEI with rich metadata and structural annotation. The automatic annotation included POS-tagging, lemmatization, and named entities, relying on Natural Language Processing resources developed and maintained by the JeRTeh Language Resources and Technologies Society. The integration of SrpELTeC with Wikidata was supported with a set of SPARQL queries for the retrieval of metadata with different visualization options. Recent activities within the COST Action NexusLinguarum—European Network for Web-centred Linguistic Data Science (CA18209) are related to the linked data version of SrpELTeC using the NLP Interchange Format. All versions of SrpELTeC are freely available under the CC-BY license.

First Chromosome-Level Genome Assembly of a Ribbon Worm from the Hoplonemertea Clade, Emplectonema gracile, and Its Structural Annotation.

Genome-wide information has so far been unavailable for ribbon worms of the clade Hoplonemertea, the most species-rich class within the phylum Nemertea. While species within Pilidiophora, the sister clade of Hoplonemertea, possess a pilidium larval stage and lack stylets on their proboscis, Hoplonemertea species have a planuliform larva and are armed with stylets employed for the injection of toxins into their prey. To further compare these developmental, physiological, and behavioral differences from a genomic perspective, the availability of a reference genome for a Hoplonemertea species is crucial. Such data will be highly useful for future investigations toward a better understanding of molecular ecology, venom evolution, and regeneration not only in Nemertea but also in other marine invertebrate phyla. To this end, we herein present the annotated chromosome-level genome assembly for Emplectonema gracile (Nemertea; Hoplonemertea; Monostilifera; Emplectonematidae), an easily collected nemertean well suited for laboratory experimentation. The genome has an assembly size of 157.9 Mb. Hi-C scaffolding yielded chromosome-level scaffolds, with a scaffold N50 of 10.0 Mb and a score of 95.1% for complete BUSCO genes found as a single copy. Annotation predicted 20,684 protein-coding genes. The high-quality reference genome reaches an Earth BioGenome standard level of 7.C.Q50.

Identification of genes associated with color characteristics of meat and fat tissue of aberdeen-angus cattle

Currently, full genome association studies and identification of candidate genes for economically useful traits in farm animals are topical, scientifically sound and practice-oriented, and fulfill one of the objectives of the Strategy for Scientific and Technical Development of the Russian Federation. This article presents the results of GWAS on color spectral values of meat and fat tissue of Aberdeen-Angus cattle, known for its meat characteristics of high grade. The animals were genotyped on high-density BovineHD Genotyping BeadChip chips containing ≈53,000 SNPs. After quality control, 39,928 remained. By analysis and structural annotation, 25 and 26 candidate genes for meat and fat color were identified, respectively. According to functional annotation, the genes were categorized into 6 groups: nervous system functions, organ development, vascular, joints, metabolic processes and biosynthesis, cellular processes, muscle, tissue and bone, reproduction and embryonic development. The obtained genes were checked through the Animal QTL database, as a result of which 13 genes were confirmed, of which 3 were localized SNPs, in connection with which the LRP2, SCIN and ANTXR1 genes have advantages for their further application in the molecular diagnostics of cattle not only meat, but also dairy productivity.

Updated Gene Prediction of the Cucumber (9930) Genome through Manual Annotation.

Thorough and precise gene structure annotations are essential for maximizing the benefits of genomic data and unveiling valuable genetic insights. The cucumber genome was first released in 2009 and updated in 2019. To increase the accuracy of the predicted gene models, 64 published RNA-seq data and 9 new strand-specific RNA-seq data from multiple tissues were used for manual comparison with the gene models. The updated annotation file (V3.1) contains an increased number (24,145) of predicted genes compared to the previous version (24,317 genes), with a higher BUSCO value of 96.9%. A total of 6231 and 1490 transcripts were adjusted and newly added, respectively, accounting for 31.99% of the overall gene tally. These newly added and adjusted genes were renamed (CsaV3.1_XGXXXXX), while genes remaining unaltered preserved their original designations. A random selection of 21 modified/added genes were validated using RT-PCR analyses. Additionally, tissue-specific patterns of gene expression were examined using the newly obtained transcriptome data with the revised gene prediction model. This improved annotation of the cucumber genome will provide essential and accurate resources for studies in cucumber.

The Kavaratamides: Discovery of Linear Lipodepsipeptides from the Marine Cyanobacterium Moorena bouillonii Using a Comparative Chemogeographic Analysis.

Kavaratamide A (1), a new linear lipodepsipeptide possessing an unusual isopropyl-O-methylpyrrolinone moiety, was discovered from the tropical marine filamentous cyanobacterium Moorena bouillonii collected from Kavaratti, India. A comparative chemogeographic analysis of M. bouillonii collected from six different geographical regions led to the prioritized isolation of this metabolite from India as distinctive among our data sets. AI-based structure annotation tools, including SMART 2.1 and DeepSAT, accelerated the structure elucidation by providing useful structural clues, and the full planar structure was elucidated based on comprehensive HRMS, MS/MS fragmentation, and NMR data interpretation. Subsequently, the absolute configuration of 1 was determined using advanced Marfey's analysis, modified Mosher's ester derivatization, and chiral-phase HPLC. The structures of kavaratamides B (2) and C (3) are proposed based on a detailed analysis of their MS/MS fragmentations. The biological activity of kavaratamide A was also investigated and found to show moderate cytotoxicity to the D283-medullablastoma cell line.

A multi-tissue de novo transcriptome assembly and relative gene expression of the vulnerable freshwater salmonid Thymallus ligericus

Freshwater ecosystems are among the most endangered ecosystems worldwide. While numerous taxa are on the verge of extinction as a result of global changes and direct or indirect anthropogenic activity, genomic and transcriptomic resources represent a key tool for comprehending species' adaptability and serve as the foundation for conservation initiatives. The Loire grayling, Thymallus ligericus, is a freshwater European salmonid endemic to the upper Loire River basin. The species is comprised of fragmented populations that are dispersed over a small area and it has been identified as a vulnerable species. Here, we provide a multi-tissue de novo transcriptome assembly of T. ligericus. The completeness and integrity of the transcriptome were assessed before and after redundancy removal with lineage-specific libraries from Eukaryota, Metazoa, Vertebrata, and Actinopterygii. Relative gene expression was assessed for each of the analyzed tissues, using the de novo assembled transcriptome and a genome-based analysis using the available T. thymallus genome as a reference. The final assembly, with a contig N50 of 1221 and Benchmarking Universal Single-Copy Orthologs (BUSCO) scores above 94%, is made accessible along with structural and functional annotations and relative gene expression of the five tissues (NCBI SRA and FigShare databases). This is the first transcriptomic resource for this species, which provides a foundation for future research on this and other salmonid species that are increasingly exposed to environmental stressors.

Protein family annotation for the Unified Human Gastrointestinal Proteome by DPCfam clustering

Technological advances in massively parallel sequencing have led to an exponential growth in the number of known protein sequences. Much of this growth originates from metagenomic projects producing new sequences from environmental and clinical samples. The Unified Human Gastrointestinal Proteome (UHGP) catalogue is one of the most relevant metagenomic datasets with applications ranging from medicine to biology. However, the low levels of sequence annotation may impair its usability. This work aims to produce a family classification of UHGP sequences to facilitate downstream structural and functional annotation. This is achieved through the release of the DPCfam-UHGP50 dataset containing 10,778 putative protein families generated using DPCfam clustering, an unsupervised pipeline grouping sequences into single or multi-domain architectures. DPCfam-UHGP50 considerably improves family coverage at protein and residue levels compared to the manually curated repository Pfam. In the hope that DPCfam-UHGP50 will foster future discoveries in the field of metagenomics of the human gut, we release a FAIR-compliant database of our results that is easily accessible via a searchable web server and Zenodo repository.

Structure-guided Evolutionary Analysis of Interactome Network Rewiring at Single Residue Resolution in Yeasts

Protein-protein interactions (PPIs) are known to rewire extensively during evolution leading to lineage-specific and species-specific changes in molecular processes. However, the detailed molecular evolutionary mechanisms underlying interactome network rewiring are not well-understood. Here, we combine high-confidence PPI data, high-resolution three-dimensional structures of protein complexes, and homology-based structural annotation transfer to construct structurally-resolved interactome networks for the two yeasts S. cerevisiae and S. pombe. We then classify PPIs according to whether they are preserved or different between the two yeast species and compare site-specific evolutionary rates of interfacial versus non-interfacial residues for these different categories of PPIs. We find that residues in PPI interfaces evolve significantly more slowly than non-interfacial residues when using lineage-specific measures of evolutionary rate, but not when using non-lineage-specific measures. Furthermore, both lineage-specific and non-lineage-specific evolutionary rate measures can distinguish interfacial residues from non-interfacial residues for preserved PPIs between the two yeasts, but only the lineage-specific measure is appropriate for rewired PPIs. Finally, both lineage-specific and non-lineage-specific evolutionary rate measures are appropriate for elucidating structural determinants of protein evolution for residues outside of PPI interfaces. Overall, our results demonstrate that unlike tertiary structures of single proteins, PPIs and PPI interfaces can be highly volatile in their evolution, thus requiring the use of lineage-specific measures when studying their evolution. These results yield insight into the evolutionary design principles of PPIs and the mechanisms by which interactions are preserved or rewired between species, improving our understanding of the molecular evolution of PPIs and PPI interfaces at the residue level.

SapBase: A central portal for functional and comparative genomics of Sapindaceae species.

The Sapindaceae family, encompassing a wide range of plant forms such as herbs, vines, shrubs, and trees, is widely distributed across tropical and subtropical regions. This family includes economically important crops like litchi, longan, rambutan, and ackee. With the wide application of genomic technologies in recent years, several Sapindaceae plant genomes have been decoded, leading to an accumulation of substantial omics data in this field. This surge in data highlights the pressing need for a unified genomic data center capable of storing, sharing, and analyzing these data. Here, we introduced SapBase, that is, the Sapindaceae Genome Database. SapBase houses seven published plant genomes alongside their corresponding gene structure and functional annotations, small RNA annotations, gene expression profiles, gene pathways, and synteny block information. It offers user-friendly features for gene information mining, co-expression analysis, and inter-species comparative genomic analysis. Furthermore, we showcased SapBase's extensive capacities through a detailed bioinformatic analysis of a MYB gene in litchi. Thus, SapBase could serve as an integrative genomic resource and analysis platform for the scientific exploration of Sapinaceae species and their comparative studies with other plants.

PDB NextGen Archive: centralizing access to integrated annotations and enriched structural information by the Worldwide Protein Data Bank.

The Protein Data Bank (PDB) is the global repository for public-domain experimentally determined 3D biomolecular structural information. The archival nature of the PDB presents certain challenges pertaining to updating or adding associated annotations from trusted external biodata resources. While each Worldwide PDB (wwPDB) partner has made best efforts to provide up-to-date external annotations, accessing and integrating information from disparate wwPDB data centers can be an involved process. To address this issue, the wwPDB has established the PDB Next Generation (or NextGen) Archive, developed to centralize and streamline access to enriched structural annotations from wwPDB partners and trusted external sources. At present, the NextGen Archive provides mappings between experimentally determined 3D structures of proteins and UniProt amino acid sequences, domain annotations from Pfam, SCOP2 and CATH databases and intra-molecular connectivity information. Since launch, the PDB NextGen Archive has seen substantial user engagement with over 3.5 million data file downloads, ensuring researchers have access to accurate, up-to-date and easily accessible structural annotations. Database URL: http://www.wwpdb.org/ftp/pdb-nextgen-archive-site.

Coinfection of cotton plants with cotton leafroll dwarf virus‐atypical and a novel cotton begomovirus

AbstractCotton is a commercial crop of global importance whose versatile fibre is widely used in the textile industry. Cotton is vulnerable to infectious pathogens, including viruses, that are a major threat to cotton production. Cotton blue disease is caused by cotton leafroll dwarf virus (CLRDV), a polerovirus transmitted by aphids. This virus is controlled by sowing cotton varieties resistant to CLRDV, although, in recent years an atypical variant (CLRDV‐at), that breaks the resistance, has been identified. An outbreak of a disease occurred in cotton fields of the province of Chaco, in the north‐west of Argentina, in the 2014–2015 growing season. NuOpal cotton plants (a variety resistant to CLRDV and susceptible to CLRDV‐at) showed mosaic symptoms and had virus‐transmitting insect vectors, such as aphids and whiteflies (Bemisia tabaci). The symptoms were common for virus infections but different from those caused by CLRDV or CLRDV‐at. According to a reverse transcription‐PCR analysis with polerovirus primers and sequencing, the plants contained CLRDV‐at. To identify the complete virome of these plants, we performed a massive RNA‐based deep sequencing assay using Illumina technology. As a result, a new begomovirus that infects cotton in Argentina was identified. Structural and functional annotation indicated that its sequences corresponded to complete DNA components A and B of a novel New World bipartite begomovirus. Genetic distance and evolutionary analyses support that the detected sequences correspond to a new virus, which we propose to name cotton mosaic virus (CoMV). In addition, we report the first begomovirus and polerovirus coinfection in cotton.

Annotation and visualization of parasite, fungi and arthropod genomes with Companion.

As sequencing genomes has become increasingly popular, the need for annotation of the resulting assemblies is growing. Structural and functional annotation is still challenging as it includes finding the correct gene sequences, annotating other elements such as RNA and being able to submit those data to databases to share it with the community. Compared to de novo assembly where contiguous chromosomes are a sign of high quality, it is difficult to visualize and assess the quality of annotation. We developed the Companion web server to allow non-experts to annotate their genome using a reference-based method, enabling them to assess the output before submitting to public databases. In this update paper, we describe how we have included novel methods for gene finding and made the Companion server more efficient for annotation of genomes of up to 1 Gb in size. The reference set was increased to include genomes of interest for human and animal health from the fungi and arthropod kingdoms. We show that Companion outperforms existing comparable tools where closely related references are available.

Structural annotation of unknown molecules in a miniaturized mass spectrometer based on a transformer enabled fragment tree method

Structural annotation of small molecules in tandem mass spectrometry has always been a central challenge in mass spectrometry analysis, especially using a miniaturized mass spectrometer for on-site testing. Here, we propose the Transformer enabled Fragment Tree (TeFT) method, which combines various types of fragmentation tree models and a deep learning Transformer module. It is aimed to generate the specific structure of molecules de novo solely from mass spectrometry spectra. The evaluation results on different open-source databases indicated that the proposed model achieved remarkable results in that the majority of molecular structures of compounds in the test can be successfully recognized. Also, the TeFT has been validated on a miniaturized mass spectrometer with low-resolution spectra for 16 flavonoid alcohols, achieving complete structure prediction for 8 substances. Finally, TeFT confirmed the structure of the compound contained in a Chinese medicine substance called the Anweiyang capsule. These results indicate that the TeFT method is suitable for annotating fragmentation peaks with clear fragmentation rules, particularly when applied to on-site mass spectrometry with lower mass resolution.

NP3 MS Workflow: An Open-Source Software System to Empower Natural Product-Based Drug Discovery Using Untargeted Metabolomics.

Natural products (or specialized metabolites) are historically the main source of new drugs. However, the current drug discovery pipelines require miniaturization and speeds that are incompatible with traditional natural product research methods, especially in the early stages of the research. This article introduces the NP3 MS Workflow, a robust open-source software system for liquid chromatography-tandem mass spectrometry (LC-MS/MS) untargeted metabolomic data processing and analysis, designed to rank bioactive natural products directly from complex mixtures of compounds, such as bioactive biota samples. NP3 MS Workflow allows minimal user intervention as well as customization of each step of LC-MS/MS data processing, with diagnostic statistics to allow interpretation and optimization of LC-MS/MS data processing by the user. NP3 MS Workflow adds improved computing of the MS2 spectra in an LC-MS/MS data set and provides tools for automatic [M + H]+ ion deconvolution using fragmentation rules; chemical structural annotation against MS2 databases; and relative quantification of the precursor ions for bioactivity correlation scoring. The software will be presented with case studies and comparisons with equivalent tools currently available. NP3 MS Workflow shows a robust and useful approach to select bioactive natural products from complex mixtures, improving the set of tools available for untargeted metabolomics. It can be easily integrated into natural product-based drug-discovery pipelines and to other fields of research at the interface of chemistry and biology.