The last 18 months, or more, have seen a profound shift in our global experience, with many of us navigating a once-in-100-year pandemic. To date, COVID-19 remains a life-threatening pandemic with little to no targeted therapeutic recourse. The discovery of novel antiviral agents, such as vaccines and drugs, can provide therapeutic solutions to save human beings from severe infections; however, there is no specifically effective antiviral treatment confirmed for now. Thus, great attention has been paid to the use of natural or artificial antimicrobial peptides (AMPs) as these compounds are widely regarded as promising solutions for the treatment of harmful microorganisms. Given the biological significance of AMPs, it was obvious that there was a significant need for a single platform for identifying and engaging with AMP data. This led to the creation of the dbAMP platform that provides comprehensive information about AMPs and facilitates their investigation and analysis. To date, the dbAMP has accumulated 26 447 AMPs and 2262 antimicrobial proteins from 3044 organisms using both database integration and manual curation of >4579 articles. In addition, dbAMP facilitates the evaluation of AMP structures using I-TASSER for automated protein structure prediction and structure-based functional annotation, providing predictive structure information for clinical drug development. Next-generation sequencing (NGS) and third-generation sequencing have been applied to generate large-scale sequencing reads from various environments, enabling greatly improved analysis of genome structure. In this update, we launch an efficient online tool that can effectively identify AMPs from genome/metagenome and proteome data of all species in a short period. In conclusion, these improvements promote the dbAMP as one of the most abundant and comprehensively annotated resources for AMPs. The updated dbAMP is now freely accessible at http://awi.cuhk.edu.cn/dbAMP.

Antiviral peptide (AVP) is a kind of antimicrobial peptide (AMP) that has the potential ability to fight against virus infection. Machine learning-based prediction with a computational biology approach can facilitate the development of the novel therapeutic agents. In this study, we proposed a double-stage classification scheme, named AVPIden, for predicting the AVPs and their functional activities against different viruses. The first stage is to distinguish the AVP from a broad-spectrum peptide collection, including not only the regular peptides (non-AMP) but also the AMPs without antiviral functions (non-AVP). The second stage is responsible for characterizing one or more virus families or species that the AVP targets. Imbalanced learning is utilized to improve the performance of prediction. The AVPIden uses multiple descriptors to precisely demonstrate the peptide properties and adopts explainable machine learning strategies based on Shapley value to exploit how the descriptors impact the antiviral activities. Finally, the evaluation performance of the proposed model suggests its ability to predict the antivirus activities and their potential functions against six virus families (Coronaviridae, Retroviridae, Herpesviridae, Paramyxoviridae, Orthomyxoviridae, Flaviviridae) and eight kinds of virus (FIV, HCV, HIV, HPIV3, HSV1, INFVA, RSV, SARS-CoV). The AVPIden gives an option for reinforcing the development of AVPs with the computer-aided method and has been deployed at http://awi.cuhk.edu.cn/AVPIden/.

Circular RNAs (circRNAs), which are single-stranded RNA molecules that have individually formed into a covalently closed continuous loop, act as sponges of microRNAs to regulate transcription and translation. CircRNAs are important molecules in the field of cancer diagnosis, as growing evidence suggests that they are closely related to pathological cancer features. Therefore, they have high potential for clinical use as novel cancer biomarkers. In this article, we present our updates to CircNet (version 2.0), into which circRNAs from circAtlas and MiOncoCirc, and novel circRNAs from The Cancer Genome Atlas database have been integrated. In total, 2732 samples from 37 types of cancers were integrated into CircNet 2.0 and analyzed using several of the most reliable circRNA detection algorithms. Furthermore, target miRNAs were predicted from the full-length circRNA sequence using three reliable tools (PITA, miRanda and TargetScan). Additionally, 384 897 experimentally verified miRNA–target interactions from miRTarBase were integrated into our database to facilitate the construction of high-quality circRNA–miRNA–gene regulatory networks. These improvements, along with the user-friendly interactive web interface for data presentation, search, and visualization, showcase the updated CircNet database as a powerful, experimentally validated resource, for providing strong data support in the biomedical fields. CircNet 2.0 is currently accessible at https://awi.cuhk.edu.cn/∼CircNet.

Ubiquitination is an important post-translational modification, which controls protein turnover by labeling malfunctional and redundant proteins for proteasomal degradation, and also serves intriguing non-proteolytic regulatory functions. E3 ubiquitin ligases, whose substrate specificity determines the recognition of target proteins of ubiquitination, play crucial roles in ubiquitin–proteasome system. UbiNet 2.0 is an updated version of the database UbiNet. It contains 3332 experimentally verified E3–substrate interactions (ESIs) in 54 organisms and rich annotations useful for investigating the regulation of ubiquitination and the substrate specificity of E3 ligases. Based on the accumulated ESIs data, the recognition motifs in substrates for each E3 were also identified and a functional enrichment analysis was conducted on the collected substrates. To facilitate the research on ESIs with different categories of E3 ligases, UbiNet 2.0 performed strictly evidence-based classification of the E3 ligases in the database based on their mechanisms of ubiquitin transfer and substrate specificity. The platform also provides users with an interactive tool that can visualize the ubiquitination network of a group of self-defined proteins, displaying ESIs and protein–protein interactions in a graphical manner. The tool can facilitate the exploration of inner regulatory relationships mediated by ubiquitination among proteins of interest. In summary, UbiNet 2.0 is a user-friendly web-based platform that provides comprehensive as well as updated information about experimentally validated ESIs and a visualized tool for the construction of ubiquitination regulatory networks available at http://awi.cuhk.edu.cn/~ubinet/index.php.

Background: Probiotics may facilitate the clinical management of allergic diseases. However, their effects on allergic rhinitis (AR) remain unclear. We examined the efficacy and safety of Lacticaseibacillus paracasei GM-080 in a mouse model of airway hyper-responsiveness (AHR) and in children with perennial AR (PAR) by using a double-blind, prospective, randomized, placebo-controlled design. Methods: The production of interferon (IFN)-γ and interleukin (IL)-12 was measured by using an enzyme-linked immunosorbent assay. GM-080 safety was evaluated via the whole-genome sequencing (WGS) of virulence genes. An ovalbumin (OVA)-induced AHR mouse model was constructed, and lung inflammation was evaluated by measuring the infiltrating leukocyte content of bronchoalveolar lavage fluid. A clinical trial was conducted with 122 children with PAR who were randomized to receive different doses of GM-080 or the placebo for 3 months, and their AHR symptom severity scores, total nasal symptom scores (TNSSs), and Investigator Global Assessment Scale scores were examined. Results: Among the tested L. paracasei strains, GM-080 induced the highest IFN-γ and IL-12 levels in mouse splenocytes. WGS analysis revealed the absence of virulence factors or antibiotic-resistance genes in GM-080. The oral administration of GM-080 at 1 × 10⁷ colony forming units (CFU)/mouse/day for 8 weeks alleviated OVA-induced AHR and reduced airway inflammation in mice. In children with PAR, the oral consumption of GM-080 at 2 × 10⁹ CFU/day for 3 months ameliorated sneezing and improved Investigator Global Assessment Scale scores significantly. GM-080 consumption led to a nonsignificant decrease in TNSS and also nonsignificantly reduced IgE but increased INF-γ levels. Conclusion: GM-080 may be used as a nutrient supplement to alleviate airway allergic inflammation.