UniProt genomic mapping for deciphering functional effects of missense variants

Antiemetic activity of abietic acid possibly through the 5HT3 and muscarinic receptors interaction pathways

The present study was designed to evaluate the antiemetic activity of abietic acid (AA) using in vivo and in silico studies. To assess the effect, doses of 50 mg/kg b.w. copper sulfate (CuSO4⋅5H2O) were given orally to 2-day-old chicks. The test compound (AA) was given orally at two doses of 20 and 40 mg/kg b.w. On the other hand, aprepitant (16 mg/kg), domperidone (6 mg/kg), diphenhydramine (10 mg/kg), hyoscine (21 mg/kg), and ondansetron (5 mg/kg) were administered orally as positive controls (PCs). The vehicle was used as a control group. Combination therapies with the referral drugs were also given to three separate groups of animals to see the synergistic and antagonizing activity of the test compound. Molecular docking and visualization of ligand-receptor interaction were performed using different computational tools against various emesis-inducing receptors (D2, D3, 5HT3, H1, and M1-M5). Furthermore, the pharmacokinetics and toxicity properties of the selected ligands were predicted by using the SwissADME and Protox-II online servers. Findings indicated that AA dose-dependently enhances the latency of emetic retching and reduces the number of retching compared to the vehicle group. Among the different treatments, animals treated with AA (40 mg/kg) exhibited the highest latency (98 ± 2.44 s) and reduced the number of retching (11.66 ± 2.52 times) compared to the control groups. Additionally, the molecular docking study indicated that AA exhibits the highest binding affinity (- 10.2 kcal/mol) toward the M4 receptors and an elevated binding affinity toward the receptors 5HT3 (- 8.1 kcal/mol), M1 (- 7.7 kcal/mol), M2 (- 8.7 kcal/mol), and H1 (- 8.5 kcal/mol) than the referral ligands. Taken together, our study suggests that AA has potent antiemetic effects by interacting with the 5TH3 and muscarinic receptor interaction pathways. However, additional extensive pre-clinical and clinical studies are required to evaluate the efficacy and toxicity of AA.

Mapping Structural Distribution and Gating-Property Impacts of Disease-Associated Missense Mutations in Voltage-Gated Sodium Channels

Thousands of voltage-gated sodium (Nav) channel variants contribute to a variety of disorders, including epilepsy, autism, cardiac arrhythmia, and pain disorders. Yet variant effects of more mutations remain unclear. The conventional gain-of-function (GoF) or loss-of-function (LoF) classifications is frequently employed to interpret of variant effects on function and guide precision therapy for sodium channelopathies. Our study challenges this binary classification by analyzing 525 mutations associated with 34 diseases across 366 electrophysiology studies, revealing that diseases with similar phenotypic effects can stem from unique molecular mechanisms. Our results show a high biophysical agreement (86%) between homologous disease-associated variants in different Nav genes, significantly surpassing the 60% phenotype (GoFo/LoFo) agreement among homologous mutants, suggesting the need for more nuanced disease categorization and treatment based on specific gating-property changes. Using UniProt data, we mapped over 2,400 disease-associated missense variants across nine human Nav channels and identified three clusters of mutation hotspots. Our findings indicate that mutations near the selectivity filter generally diminish the maximal current amplitude, while those in the fast inactivation region lean towards a depolarizing shift in half-inactivation voltage in steady-state activation, and mutations in the activation gate commonly enhance persistent current. In contrast to mutations in the PD, those within the VSD exhibit diverse impacts and subtle preferences on channel activity. This study shows great potential to enhance prediction accuracy for variant effects based on the structural context, laying the groundwork for targeted drug design in precision medicine.

ASCARIS: Positional feature annotation and protein structure-based representation of single amino acid variations

Background

Genomic variations may cause deleterious effects on protein functionality and perturb biological processes. Elucidating the effects of variations is critical for developing novel treatment strategies for diseases of genetic origin. Computational approaches have been aiding the work in this field by modeling and analyzing the mutational landscape. However, new approaches are required, especially for accurate representation and data-centric analysis of sequence variations.

Method

In this study, we propose ASCARIS (Annotation and StruCture-bAsed RepresentatIon of Single amino acid variations), a method for the featurization (i.e., quantitative representation) of single amino acid variations (SAVs), which could be used for a variety of purposes, such as predicting their functional effects or building multi-omics-based integrative models. ASCARIS utilizes the direct and spatial correspondence between the location of the SAV on the sequence/structure and 30 different types of positional feature annotations (e.g., active/lipidation/glycosylation sites; calcium/metal/DNA binding, inter/transmembrane regions, etc.), along with structural features and physicochemical properties. The main novelty of this method lies in constructing reusable numerical representations of SAVs via functional annotations.

Results

We statistically analyzed the relationship between these features and the consequences of variations and found that each carries information in this regard. To investigate potential applications of ASCARIS, we trained variant effect prediction models that utilize our SAV representations as input. We carried out an ablation study and a comparison against the state-of-the-art methods and observed that ASCARIS has a competing and complementary performance against widely-used predictors. ASCARIS can be used alone or in combination with other approaches to represent SAVs from a functional perspective. ASCARIS is available as a programmatic tool at https://github.com/HUBioDataLab/ASCARIS and as a web-service at https://huggingface.co/spaces/HUBioDataLab/ASCARIS.

Quercetin Antagonizes the Sedative Effects of Linalool, Possibly through the GABAergic Interaction Pathway

Sedatives promote calmness or sleepiness during surgery or severely stressful events. In addition, depression is a mental health issue that negatively affects emotional well-being. A group of drugs called anti-depressants is used to treat major depressive illnesses. The aim of the present work was to evaluate the effects of quercetin (QUR) and linalool (LIN) on thiopental sodium (TS)-induced sleeping mice and to investigate the combined effects of these compounds using a conventional co-treatment strategy and in silico studies. For this, the TS-induced sleeping mice were monitored to compare the occurrence, latency, and duration of the sleep-in response to QUR (10, 25, 50 mg/kg), LIN (10, 25, 50 mg/kg), and diazepam (DZP, 3 mg/kg, i.p.). Moreover, an in silico investigation was undertaken to assess this study's putative modulatory sedation mechanism. For this, we observed the ability of test and standard medications to interact with various gamma-aminobutyric acid A receptor (GABA_A) subunits. Results revealed that QUR and LIN cause dose-dependent antidepressant-like and sedative-like effects in animals, respectively. In addition, QUR-50 mg/kg and LIN-50 mg/kg and/or DZP-3 mg/kg combined were associated with an increased latency period and reduced sleeping times in animals. Results of the in silico studies demonstrated that QUR has better binding interaction with GABA_A α3, β1, and γ2 subunits when compared with DZP, whereas LIN showed moderate affinity with the GABA_A receptor. Taken together, the sleep duration of LIN and DZP is opposed by QUR in TS-induced sleeping mice, suggesting that QUR may be responsible for providing sedation-antagonizing effects through the GABAergic interaction pathway.

Plasmodium Topoisomerase VIB and Spo11 Constitute Functional Type IIB Topoisomerase in Malaria Parasite: Its Possible Role in Mitochondrial DNA Segregation

The human malaria parasite undergoes a noncanonical cell division, namely, endoreduplication, where several rounds of nuclear, mitochondrial, and apicoplast replication occur without cytoplasmic division. Despite its importance in Plasmodium biology, the topoisomerases essential for decatenation of replicated chromosome during endoreduplication remain elusive. We hypothesize that the topoisomerase VI complex, containing Plasmodium falciparum topiosomerase VIB (PfTopoVIB) and catalytic P. falciparum Spo11 (PfSpo11), might be involved in the segregation of the Plasmodium mitochondrial genome. Here, we demonstrate that the putative PfSpo11 is the functional ortholog of yeast Spo11 that can complement the sporulation defects of the yeast Δspo11 strain, and the catalytic mutant Pfspo11Y65F cannot complement such defects. PfTopoVIB and PfSpo11 display a distinct expression pattern compared to the other type II topoisomerases of Plasmodium and are induced specifically at the late schizont stage of the parasite, when the mitochondrial genome segregation occurs. Furthermore, PfTopoVIB and PfSpo11 are physically associated with each other at the late schizont stage, and both subunits are localized in the mitochondria. Using PfTopoVIB- and PfSpo11-specific antibodies, we immunoprecipitated the chromatin of tightly synchronous early, mid-, and late schizont stage-specific parasites and found that both the subunits are associated with the mitochondrial genome during the late schizont stage of the parasite. Furthermore, PfTopoVIB inhibitor radicicol and atovaquone show synergistic interaction. Accordingly, atovaquone-mediated disruption of mitochondrial membrane potential reduces the import and recruitment of both subunits of PfTopoVI to mitochondrial DNA (mtDNA) in a dose-dependent manner. The structural differences between PfTopoVIB and human TopoVIB-like protein could be exploited for development of a novel antimalarial agent. IMPORTANCE This study demonstrates a likely role of topoisomerase VI in the mitochondrial genome segregation of Plasmodium falciparum during endoreduplication. We show that PfTopoVIB and PfSpo11 remain associated and form the functional holoenzyme within the parasite. The spatiotemporal expression of both subunits of PfTopoVI correlates well with their recruitment to the mitochondrial DNA at the late schizont stage of the parasite. Additionally, the synergistic interaction between PfTopoVI inhibitor and the disruptor of mitochondrial membrane potential, atovaquone, supports that topoisomerase VI is the mitochondrial topoisomerase of the malaria parasite. We propose that topoisomerase VI may act as a novel target against malaria.

Sequence and structure alignments in post-AlphaFold era

Sequence alignment is fundamental for analyzing protein structure and function. For all but closely-related proteins, alignments based on structures are more accurate than alignments based purely on amino-acid sequences. However, the disparity between the large amount of sequence data and the relative paucity of experimentally-determined structures has precluded the general applicability of structure alignment. Based on the success of AlphaFold (and its likes) in producing high-quality structure predictions, we suggest that when aligning homologous proteins, lacking experimental structures, better results can be obtained by a structural alignment of predicted structures than by an alignment based only on amino-acid sequences. We present a quantitative evaluation, based on pairwise alignments of sequences and structures (both predicted and experimental) to support this hypothesis.

UniProt: the Universal Protein Knowledgebase in 2023

The aim of the UniProt Knowledgebase is to provide users with a comprehensive, high-quality and freely accessible set of protein sequences annotated with functional information. In this publication we describe enhancements made to our data processing pipeline and to our website to adapt to an ever-increasing information content. The number of sequences in UniProtKB has risen to over 227 million and we are working towards including a reference proteome for each taxonomic group. We continue to extract detailed annotations from the literature to update or create reviewed entries, while unreviewed entries are supplemented with annotations provided by automated systems using a variety of machine-learning techniques. In addition, the scientific community continues their contributions of publications and annotations to UniProt entries of their interest. Finally, we describe our new website (https://www.uniprot.org/), designed to enhance our users' experience and make our data easily accessible to the research community. This interface includes access to AlphaFold structures for more than 85% of all entries as well as improved visualisations for subcellular localisation of proteins.

Twelve exonic variants in the SLC12A1 and CLCNKB genes alter RNA splicing in a minigene assay

Background: Bartter syndrome (BS) is a rare renal tubular disease caused by gene variants in SLC12A1, KCNJ1, CLCNKA, CLCNKB, BSND or MAGED2 genes. There is growing evidence that many exonic mutations can affect the pre-mRNA normal splicing and induce exon skipping by altering various splicing regulatory signals. Therefore, the aim of this study was to gain new insights into the consequences of exonic mutations associated with BS on pre-mRNA splicing.

Methods: We analyzed all the missense, nonsense and synonymous variants described in six pathogenic genes by bioinformatics programs and identified candidate mutations that may promote exon skipping through a minigene system.

Results: Results of the study showed that 12 of 14 candidate variants distributed in SLC12A1 (c.728G>A, C.735C>G, c.904C>T, c.905G>A, c.1304C>T, c.1493C>T, c.2221A>T) and CLCNKB (c.226C>T, c.228A>C, c.229G>A, c.229G>C, c.1979C>A) were identified to induce splicing alterations. These variants may not only disrupt exonic splicing enhancers (ESEs) but also generate new exonic splicing silencers (ESSs), or disturb the classic splicing sites.

Conclusion: To our knowledge, this is a comprehensive study regarding alterations in pre-mRNA of exonic variants in BS pathogenic genes. Our results reinforce the necessity of assessing the consequences of exonic variants at the mRNA level.

A Sporothrix spp enolase derived multi-epitope vaccine confers protective response in BALB/c mice challenged with Sporothrix brasiliensis

Sporotrichosis is a cosmopolitan mycosis caused by pathogenic species of Sporothrix genus, that in Brazil is often acquired by zoonotic transmission involved infected cats with S. brasiliensis. Previous studies showed that the Sporothrix spp. recombinant enolase (rSsEno), a multifunctional protein with immunogenic properties, could be a promising target for vaccination against sporotrichosis in cats. Nevertheless, the considerable sequence identity (62%) of SsEno with its feline counterpart is a great concern. Here, we report the identification in silico, chemical synthesis and biological validation of six peptides of SsEno with low sequence identity to its cat orthologue. All synthesized peptides exhibit B-cell epitopes on the molecular surface of SsEno and proved to be highly reactive with the serum of infected mice with S. brasiliensis and sera of cats with sporotrichosis. Interestingly, our study revealed that anti-peptide sera did not react with the recombinant enolase from Felis catus (cats, rFcEno), thus, may not trigger autoimmune response in these felines if used as a vaccine antigen. The immunization with peptide mixture (PeptMix) formulated with Freund adjuvant (FA), induced high levels of antigen-specific IgG, IgG1 and IgG2b antibodies that conferred protection upon passive transference in infected BALB/c mice with S. brasiliensis. We also observed, that the FA + PeptMix formulation induced a Th1/Th2/Th17 cytokine profile ex vivo, associated with protecting effect against the experimental sporotrichosis. Our results suggest that the six SsEno-derived peptides here evaluated, could be used as safe antigens for the development of vaccine strategies against feline sporotrichosis, whether prophylactic or therapeutic.

Integrative OMICS Data-Driven Procedure Using a Derivatized Meta-Analysis Approach

The wealth of high-throughput data has opened up new opportunities to analyze and describe biological processes at higher resolution, ultimately leading to a significant acceleration of scientific output using high-throughput data from the different omics layers and the generation of databases to store and report raw datasets. The great variability among the techniques and the heterogeneous methodologies used to produce this data have placed meta-analysis methods as one of the approaches of choice to correlate the resultant large-scale datasets from different research groups. Through multi-study meta-analyses, it is possible to generate results with greater statistical power compared to individual analyses. Gene signatures, biomarkers and pathways that provide new insights of a phenotype of interest have been identified by the analysis of large-scale datasets in several fields of science. However, despite all the efforts, a standardized regulation to report large-scale data and to identify the molecular targets and signaling networks is still lacking. Integrative analyses have also been introduced as complementation and augmentation for meta-analysis methodologies to generate novel hypotheses. Currently, there is no universal method established and the different methods available follow different purposes. Herein we describe a new unifying, scalable and straightforward methodology to meta-analyze different omics outputs, but also to integrate the significant outcomes into novel pathways describing biological processes of interest. The significance of using proper molecular identifiers is highlighted as well as the potential to further correlate molecules from different regulatory levels. To show the methodology’s potential, a set of transcriptomic datasets are meta-analyzed as an example.

Characterization of protein isoform diversity in human umbilical vein endothelial cells via long-read proteogenomics

Endothelial cells (ECs) comprise the lumenal lining of all blood vessels and are critical for the functioning of the cardiovascular system. Their phenotypes can be modulated by alternative splicing of RNA to produce distinct protein isoforms. To characterize the RNA and protein isoform landscape within ECs, we applied a long read proteogenomics approach to analyse human umbilical vein endothelial cells (HUVECs). Transcripts delineated from PacBio sequencing serve as the basis for a sample-specific protein database used for downstream mass-spectrometry (MS) analysis to infer protein isoform expression. We detected 53,863 transcript isoforms from 10,426 genes, with 22,195 of those transcripts being novel. Furthermore, the predominant isoform in HUVECs does not correspond with the accepted "reference isoform" 25% of the time, with vascular pathway-related genes among this group. We found 2,597 protein isoforms supported through unique peptides, with an additional 2,280 isoforms nominated upon incorporation of long-read transcript evidence. We characterized a novel alternative acceptor for endothelial-related gene CDH5, suggesting potential changes in its associated signalling pathways. Finally, we identified novel protein isoforms arising from a diversity of RNA splicing mechanisms supported by uniquely mapped novel peptides. Our results represent a high-resolution atlas of known and novel isoforms of potential relevance to endothelial phenotypes and function.[Figure: see text].

TMSNP: a web server to predict pathogenesis of missense mutations in the transmembrane region of membrane proteins

The massive amount of data generated from genome sequencing brings tons of newly identified mutations, whose pathogenic/non-pathogenic effects need to be evaluated. This has given rise to several mutation predictor tools that, in general, do not consider the specificities of the various protein groups. We aimed to develop a predictor tool dedicated to membrane proteins, under the premise that their specific structural features and environment would give different responses to mutations compared to globular proteins. For this purpose, we created TMSNP, a database that currently contains information from 2624 pathogenic and 196 705 non-pathogenic reported mutations located in the transmembrane region of membrane proteins. By computing various conservation parameters on these mutations in combination with annotations, we trained a machine-learning model able to classify mutations as pathogenic or not. TMSNP (freely available at http://lmc.uab.es/tmsnp/) improves considerably the prediction power of commonly used mutation predictors trained with globular proteins.

From chemoproteomic-detected amino acids to genomic coordinates: insights into precise multi-omic data integration

The integration of proteomic, transcriptomic, and genetic variant annotation data will improve our understanding of genotype-phenotype associations. Due, in part, to challenges associated with accurate inter-database mapping, such multi-omic studies have not extended to chemoproteomics, a method that measures the intrinsic reactivity and potential "druggability" of nucleophilic amino acid side chains. Here, we evaluated mapping approaches to match chemoproteomic-detected cysteine and lysine residues with their genetic coordinates. Our analysis revealed that database update cycles and reliance on stable identifiers can lead to pervasive misidentification of labeled residues. Enabled by this examination of mapping strategies, we then integrated our chemoproteomics data with computational methods for predicting genetic variant pathogenicity, which revealed that codons of highly reactive cysteines are enriched for genetic variants that are predicted to be more deleterious and allowed us to identify and functionally characterize a new damaging residue in the cysteine protease caspase-8. Our study provides a roadmap for more precise inter-database mapping and points to untapped opportunities to improve the predictive power of pathogenicity scores and to advance prioritization of putative druggable sites.

UniProt: the universal protein knowledgebase in 2021

The aim of the UniProt Knowledgebase is to provide users with a comprehensive, high-quality and freely accessible set of protein sequences annotated with functional information. In this article, we describe significant updates that we have made over the last two years to the resource. The number of sequences in UniProtKB has risen to approximately 190 million, despite continued work to reduce sequence redundancy at the proteome level. We have adopted new methods of assessing proteome completeness and quality. We continue to extract detailed annotations from the literature to add to reviewed entries and supplement these in unreviewed entries with annotations provided by automated systems such as the newly implemented Association-Rule-Based Annotator (ARBA). We have developed a credit-based publication submission interface to allow the community to contribute publications and annotations to UniProt entries. We describe how UniProtKB responded to the COVID-19 pandemic through expert curation of relevant entries that were rapidly made available to the research community through a dedicated portal. UniProt resources are available under a CC-BY (4.0) license via the web at https://www.uniprot.org/.

UniProt: the universal protein knowledgebase in 2021

The aim of the UniProt Knowledgebase is to provide users with a comprehensive, high-quality and freely accessible set of protein sequences annotated with functional information. In this article, we describe significant updates that we have made over the last two years to the resource. The number of sequences in UniProtKB has risen to approximately 190 million, despite continued work to reduce sequence redundancy at the proteome level. We have adopted new methods of assessing proteome completeness and quality. We continue to extract detailed annotations from the literature to add to reviewed entries and supplement these in unreviewed entries with annotations provided by automated systems such as the newly implemented Association-Rule-Based Annotator (ARBA). We have developed a credit-based publication submission interface to allow the community to contribute publications and annotations to UniProt entries. We describe how UniProtKB responded to the COVID-19 pandemic through expert curation of relevant entries that were rapidly made available to the research community through a dedicated portal. UniProt resources are available under a CC-BY (4.0) license via the web at https://www.uniprot.org/.

Genomic signatures of globally enhanced gene duplicate accumulation in the megadiverse higher Diptera fueling intralocus sexual conflict resolution

Gene duplication is an important source of evolutionary innovation. To explore the relative impact of gene duplication during the diversification of major insect model system lineages, we performed a comparative analysis of lineage-specific gene duplications in the fruit fly Drosophila melanogaster (Diptera: Brachycera), the mosquito Anopheles gambiae (Diptera: Culicomorpha), the red flour beetle Tribolium castaneum (Coleoptera), and the honeybee Apis mellifera (Hymenoptera). Focusing on close to 6,000 insect core gene families containing maximally six paralogs, we detected a conspicuously higher number of lineage-specific duplications in Drosophila (689) compared to Anopheles (315), Tribolium (386), and Apis (223). Based on analyses of sequence divergence, phylogenetic distribution, and gene ontology information, we present evidence that an increased background rate of gene duplicate accumulation played an exceptional role during the diversification of the higher Diptera (Brachycera), in part by providing enriched opportunities for intralocus sexual conflict resolution, which may have boosted speciation rates during the early radiation of the megadiverse brachyceran subclade Schizophora.

A Distinct Contractile Injection System Gene Cluster Found in a Majority of Healthy Adult Human Microbiomes

Many commensal bacteria antagonize each other or their host by producing syringe-like secretion systems called contractile injection systems (CIS). Members of the Bacteroidales family have been shown to produce only one type of CIS-a contact-dependent type 6 secretion system that mediates bacterium-bacterium interactions. Here, we show that a second distinct cluster of genes from Bacteroidales bacteria from the human microbiome may encode yet-uncharacterized injection systems that we term Bacteroidales injection systems (BIS). We found that BIS genes are present in the gut microbiomes of 99% of individuals from the United States and Europe and that BIS genes are more prevalent in the gut microbiomes of healthy individuals than in those individuals suffering from inflammatory bowel disease. Gene clusters similar to that of the BIS mediate interactions between bacteria and diverse eukaryotes, like amoeba, insects, and tubeworms. Our findings highlight the ubiquity of the BIS gene cluster in the human gut and emphasize the relevance of the gut microbiome to the human host. These results warrant investigations into the structure and function of the BIS and how they might mediate interactions between Bacteroidales bacteria and the human host or microbiome.IMPORTANCE To engage with host cells, diverse pathogenic bacteria produce syringe-like structures called contractile injection systems (CIS). CIS are evolutionarily related to the contractile tails of bacteriophages and are specialized to puncture membranes, often delivering effectors to target cells. Although CIS are key for pathogens to cause disease, paradoxically, similar injection systems have been identified within healthy human microbiome bacteria. Here, we show that gene clusters encoding a predicted CIS, which we term Bacteroidales injection systems (BIS), are present in the microbiomes of nearly all adult humans tested from Western countries. BIS genes are enriched within human gut microbiomes and are expressed both in vitro and in vivo Further, a greater abundance of BIS genes is present within healthy gut microbiomes than in those humans with with inflammatory bowel disease (IBD). Our discovery provides a potentially distinct means by which our microbiome interacts with the human host or its microbiome.

Unified inference of missense variant effects and gene constraints in the human genome

A challenge in medical genomics is to identify variants and genes associated with severe genetic disorders. Based on the premise that severe, early-onset disorders often result in a reduction of evolutionary fitness, several statistical methods have been developed to predict pathogenic variants or constrained genes based on the signatures of negative selection in human populations. However, we currently lack a statistical framework to jointly predict deleterious variants and constrained genes from both variant-level features and gene-level selective constraints. Here we present such a unified approach, UNEECON, based on deep learning and population genetics. UNEECON treats the contributions of variant-level features and gene-level constraints as a variant-level fixed effect and a gene-level random effect, respectively. The sum of the fixed and random effects is then combined with an evolutionary model to infer the strength of negative selection at both variant and gene levels. Compared with previously published methods, UNEECON shows improved performance in predicting missense variants and protein-coding genes associated with autosomal dominant disorders, and feature importance analysis suggests that both gene-level selective constraints and variant-level predictors are important for accurate variant prioritization. Furthermore, based on UNEECON, we observe a low correlation between gene-level intolerance to missense mutations and that to loss-of-function mutations, which can be partially explained by the prevalence of disordered protein regions that are highly tolerant to missense mutations. Finally, we show that genes intolerant to both missense and loss-of-function mutations play key roles in the central nervous system and the autism spectrum disorders. Overall, UNEECON is a promising framework for both variant and gene prioritization.

Numerous statistical methods have been developed to predict deleterious missense variants or constrained genes in the human genome, but unified prioritization methods that utilize both variant- and gene-level information are underdeveloped. Here we present UNEECON, an evolution-based deep learning framework for unified variant and gene prioritization. By integrating variant-level predictors and gene-level selective constraints, UNEECON outperforms existing methods in predicting missense variants and protein-coding genes associated with dominant disorders. Based on UNEECON, we show that disordered proteins are tolerant to missense mutations but not to loss-of-function mutations. In addition, we find that genes under strong selective constraints at both missense and loss-of-function levels are strongly associated with the central nervous system and the autism spectrum disorders, highlighting the need to investigate the function of these highly constrained genes in future studies.

Interaction between piperine and genes associated with sciatica and its mechanism based on molecular docking technology and network pharmacology

Abstract

Piperine is the main active component of Piper longum L., which is also the main component of anti-sciatica Mongolian medicine Naru Sanwei pill. It has many pharmacological activities such as anti-inflammatory and immune regulation. This paper aims to preliminarily explore the potential mechanism of piperine in the treatment of sciatica through network pharmacology and molecular docking. TCMSP, ETCM database and literature mining were used to collect the active compounds of Piper longum L. Swiss TargetPrediction and SuperPred server were used to find the targets of compounds. At the same time, CTD database was used to collect the targets of sciatica. Then the above targets were compared and analyzed to select the targets of anti-sciatica in Piper longum L. The Go (gene ontology) annotation and KEGG pathway of the targets were enriched and analyzed by Metascape database platform. The molecular docking between the effective components and the targets was verified by Autodock. After that, the sciatica model of rats was established and treated with piperine. The expression level of inflammatory factors and proteins in the serum and tissues of rat sciatic nerve were detected by ELISA and Western blot. HE staining and immunohistochemistry were carried out on the sciatica tissues of rats. The results showed that Piper longum L. can regulate the development of sciatica and affect the expressions of PPARG and NF-kB1 through its active ingredient piperine, and there is endogenous interaction between PPARG and NF-kB1.

Graphic abstract

A Coordinated Approach by Public Domain Bioinformatics Resources to Aid the Fight Against Alzheimer's Disease Through Expert Curation of Key Protein Targets

BACKGROUND

The analysis and interpretation of data generated from patient-derived clinical samples relies on access to high-quality bioinformatics resources. These are maintained and updated by expert curators extracting knowledge from unstructured biological data described in free-text journal articles and converting this into more structured, computationally-accessible forms. This enables analyses such as functional enrichment of sets of genes/proteins using the Gene Ontology, and makes the searching of data more productive by managing issues such as gene/protein name synonyms, identifier mapping, and data quality.

OBJECTIVE

To undertake a coordinated annotation update of key public-domain resources to better support Alzheimer's disease research.

METHODS

We have systematically identified target proteins critical to disease process, in part by accessing informed input from the clinical research community.

RESULTS

Data from 954 papers have been added to the UniProtKB, Gene Ontology, and the International Molecular Exchange Consortium (IMEx) databases, with 299 human proteins and 279 orthologs updated in UniProtKB. 745 binary interactions were added to the IMEx human molecular interaction dataset.

CONCLUSION

This represents a significant enhancement in the expert curated data pertinent to Alzheimer's disease available in a number of biomedical databases. Relevant protein entries have been updated in UniProtKB and concomitantly in the Gene Ontology. Molecular interaction networks have been significantly extended in the IMEx Consortium dataset and a set of reference protein complexes created. All the resources described are open-source and freely available to the research community and we provide examples of how these data could be exploited by researchers.

UniProt genomic mapping for deciphering functional effects of missense variants

Understanding the association of genetic variation with its functional consequences in proteins is essential for the interpretation of genomic data and identifying causal variants in diseases. Integration of protein function knowledge with genome annotation can assist in rapidly comprehending genetic variation within complex biological processes. Here, we describe mapping UniProtKB human sequences and positional annotations, such as active sites, binding sites, and variants to the human genome (GRCh38) and the release of a public genome track hub for genome browsers. To demonstrate the power of combining protein annotations with genome annotations for functional interpretation of variants, we present specific biological examples in disease-related genes and proteins. Computational comparisons of UniProtKB annotations and protein variants with ClinVar clinically annotated single nucleotide polymorphism (SNP) data show that 32% of UniProtKB variants colocate with 8% of ClinVar SNPs. The majority of colocated UniProtKB disease-associated variants (86%) map to 'pathogenic' ClinVar SNPs. UniProt and ClinVar are collaborating to provide a unified clinical variant annotation for genomic, protein, and clinical researchers. The genome track hubs, and related UniProtKB files, are downloadable from the UniProt FTP site and discoverable as public track hubs at the UCSC and Ensembl genome browsers.