CodLncScape Provides a Self-Enriching Framework for the Systematic Collection and Exploration of Coding LncRNAs.

Recent studies have revealed that numerous lncRNAs can translate proteins under specific conditions, performing diverse biological functions, thus termed coding lncRNAs. Their comprehensive landscape, however, remains elusive due to this field's preliminary and dispersed nature. This study introduces codLncScape, a framework for coding lncRNA exploration consisting of codLncDB, codLncFlow, codLncWeb, and codLncNLP. Specifically, it contains a manually compiled knowledge base, codLncDB, encompassing 353 coding lncRNA entries validated by experiments. Building upon codLncDB, codLncFlow investigates the expression characteristics of these lncRNAs and their diagnostic potential in the pan-cancer context, alongside their association with spermatogenesis. Furthermore, codLncWeb emerges as a platform for storing, browsing, and accessing knowledge concerning coding lncRNAs within various programming environments. Finally, codLncNLP serves as a knowledge-mining tool to enhance the timely content inclusion and updates within codLncDB. In summary, this study offers a well-functioning, content-rich ecosystem for coding lncRNA research, aiming to accelerate systematic studies in this field.

MCSdb, a database of proteins residing in membrane contact sites.

Organelles do not act as autonomous discrete units but rather as interconnected hubs that engage in extensive communication by forming close contacts called "membrane contact sites (MCSs)". And many proteins have been identified as residing in MCS and playing important roles in maintaining and fulfilling specific functions within these microdomains. However, a comprehensive compilation of these MCS proteins is still lacking. Therefore, we developed MCSdb, a manually curated resource of MCS proteins and complexes from publications. MCSdb documents 7010 MCS protein entries and 263 complexes, involving 24 organelles and 44 MCSs across 11 species. Additionally, MCSdb orchestrates all data into different categories with multitudinous information for presenting MCS proteins. In summary, MCSdb provides a valuable resource for accelerating MCS functional interpretation and interorganelle communication deciphering.

P450Rdb: a manually curated database of reactions catalyzed by cytochrome P450 enzymes.

INTRODUCTION: Cytochrome P450 enzymes (P450s) are recognized as the most versatile catalysts worldwide, playing vital roles in numerous biological metabolism and biosynthesis processes across all kingdoms of life. Despite the vast number of P450 genes available in databases (over 300,000), only a small fraction of them (less than 0.2%) have undergone functional characterization. OBJECTIVES: To provide a convenient platform with abundant information on P450s and their corresponding reactions, we introduce the P450Rdb database, a manually curated resource compiles literature-supported reactions catalyzed by P450s. METHODS: All the P450s and Reactions were manually curated from the literature and known databases. Subsequently, the P450 reactions organized and categorized according to their chemical reaction type and site. The website was developed using HTML and PHP languages, with the MySQL server utilized for data storage. RESULTS: The current version of P450Rdb catalogs over 1,600 reactions, involving more than 590 P450s across a diverse range of over 200 species. Additionally, it offers a user-friendly interface with comprehensive information, enabling easy querying, browsing, and analysis of P450s and their corresponding reactions. P450Rdb is free available at http://www.cellknowledge.com.cn/p450rdb/. CONCLUSIONS: We believe that this database will significantly promote structural and functional research on P450s, thereby fostering advancements in the fields of natural product synthesis, pharmaceutical engineering, biotechnological applications, agricultural and crop improvement, and the chemical industry.

Bitter-RF: A random forest machine model for recognizing bitter peptides.

Introduction: Bitter peptides are short peptides with potential medical applications. The huge potential behind its bitter taste remains to be tapped. To better explore the value of bitter peptides in practice, we need a more effective classification method for identifying bitter peptides. Methods: In this study, we developed a Random forest (RF)-based model, called Bitter-RF, using sequence information of the bitter peptide. Bitter-RF covers more comprehensive and extensive information by integrating 10 features extracted from the bitter peptides and achieves better results than the latest generation model on independent validation set. Results: The proposed model can improve the accurate classification of bitter peptides (AUROC = 0.98 on independent set test) and enrich the practical application of RF method in protein classification tasks which has not been used to build a prediction model for bitter peptides. Discussion: We hope the Bitter-RF could provide more conveniences to scholars for bitter peptide research.

Construction of a Combined Hypoxia-related Genes Model for Hepatocellular Carcinoma Prognosis.

BACKGROUND: Hepatocellular carcinoma (HCC) is the most common liver malignancy where tumorigenesis and metastasis are believed to be tied to the hallmarks of hypoxia and tumor microenvironment (TME). METHODS: In this study, to investigate the relationships among hypoxia, TME, and HCC prognosis, we collected two independent datasets from a public database (TCGA-LIHC for identification, GSE14520 for validation) and identified the hypoxia-related differentially expressed genes (DEGs) from the TCGA data, and the univariable Cox regression and lasso regression analyses were performed to construct the prognosis model. An HCC prognosis model with 4 hypoxiarelated DEGs ("NDRG1", "ENO1", "SERPINE1", "ANXA2") was constructed, and high- and low-risk groups of HCC were established by the median of the model risk score. RESULTS: The survival analysis revealed significant differences between the two groups in both datasets, with the results of the AUC of the ROC curve of 1, 3, and 5 years in two datasets indicating the robustness of the prognosis model. Meanwhile, for the TCGA-LIHC data, the immune characteristics between the two groups revealed that the low-risk group presented higher levels of activated NK cells, monocytes, and M2 macrophages, and 7 immune checkpoint genes were found upregulated in the high-risk group. Additionally, the two groups have no difference in molecular characteristics (tumor mutational burden, TMB). The proportion of recurrence was higher in the high-risk group, and the correlation between the recurrence month and risk score was negative, indicating high-risk correlates with a short recurrence month. CONCLUSION: In summary, this study shows the association among hypoxic signals, TME, and HCC prognosis and may help reveal potential regulatory mechanisms between hypoxia, tumorigenesis, and metastasis in HCC. The hypoxia-related model demonstrated the potential to be a predictor and drug target of prognosis.

TCM2COVID: A resource of anti-COVID-19 traditional Chinese medicine with effects and mechanisms.

In China, traditional Chinese medicine (TCM) has been widely used for coronavirus infectious disease 2019 (COVID-19) prevention, treatment, and recovery and has played a part in the battle against the disease. A variety of TCM treatments have been recommended for different stages of COVID-19. But, to the best of our knowledge, a comprehensive database for storing and organizing anti-COVID TCM treatments is still lacking. Herein, we developed TCM2COVID, a manually curated resource of anti-COVID TCM formulas, natural products (NPs), and herbs. The current version of TCM2COVID (1) documents over 280 TCM formulas (including over 300 herbs) with detailed clinical evidence and therapeutic mechanism information; (2) records over 80 NPs with detailed potential therapeutic mechanisms; and (3) launches a useful web server for querying, analyzing and visualizing documented formulas similar to those supplied by the user (formula similarity analysis). In summary, TCM2COVD provides a user-friendly and practical platform for documenting, querying, and browsing anti-COVID TCM treatments, and will help in the development and elucidation of the mechanisms of action of new anti-COVID TCM therapies to support the fight against the COVID-19 epidemic. TCM2COVID is freely available at http://zhangy-lab.cn/tcm2covid/.