Comprehensive survey of target prediction web servers for Traditional Chinese Medicine.

Traditional Chinese medicine (TCM) is characterized by multi-components, multiple targets, and complex mechanisms of action and therefore has significant advantages in treating diseases. However, the clinical application of TCM prescriptions is limited due to the difficulty in elucidating the effective substances and the lack of current scientific evidence on the mechanisms of action. In recent years, the development of network pharmacology based on drug systems research has provided a new approach for understanding the complex systems represented by TCM. The determination of drug targets is the core of TCM network pharmacology research. Over the past years, many web tools for drug targets with various features have been developed to facilitate target prediction, significantly promoting drug discovery. Therefore, this review introduces the widely used web tools for compound-target interaction prediction databases and web resources in TCM pharmacology research, and it compares and analyzes each web tool based on their basic properties, including the underlying theory, algorithms, datasets, and search results. Finally, we present the remaining challenges for the promising future of compound-target interaction prediction in TCM pharmacology research. This work may guide researchers in choosing web tools for target prediction and may also help develop more TCM tools based on these existing resources.

Vitex rotundifolia L. f. and Vitex trifolia L.: A review on their traditional medicine, phytochemistry, pharmacology.

ETHNOPHARMACOLOGICAL RELEVANCE: Vitex rotundifolia L. f. and Vitex trifolia L. belong to the genus Vitex, and Vitex rotundifolia L. f. evolved from Vitex trifolia L. Both are essential ethnic medicinal plants with a long history, commonly used to treat headaches, fever, diarrhea, hair loss, wound recovery, and other diseases. AIM OF THE REVIEW: The research status of Vitex trifolia L. and its relative species Vitex rotundifolia L. f. were reviewed from the aspects of traditional medicinal use, phytochemistry, and pharmacological activities, to provide a reference for the further development and utilization of Vitex rotundifolia L. f. and Vitex trifolia L. MATERIALS AND METHODS: In this paper, a comprehensive search of published literature was conducted through various books and online databases to obtain relevant information on Vitex rotundifolia L. f. and Vitex trifolia L. The search terms "(Vitex rotundifolia) OR (Vitex trifolia) OR (Fructus viticis)" were entered in PubMed, Web of Science, China national knowledge infrastructure (CNKI), Wanfang Data, Baidu Scholar, respectively. In addition to setting the year threshold of "2018-2022" on Baidu Scholar, other databases searched all fields and found 889, 283, 1263, 1023, and 147 articles, respectively. Among them, review, repetition, overlapping data, and other reasons were excluded, and finally, a total of 164 articles were included in the review study. RESULTS: A total of 369 compounds have been identified, including 159 terpenoids, 51 flavonoids, 83 phenylpropanoids, and 76 other compounds. Pharmacological studies have shown that Vitex rotundifolia L. f. and Vitex trifolia L. have a variety of pharmacological activities, such as anti-tumor, analgesic, antipyretic, anti-inflammatory, antioxidant, antibacterial, and estrogen-like activity. Modern clinical use for treating cold headaches, diarrhea dysentery, irregular menstruation, and other diseases. CONCLUSIONS: As traditional medicinal plants, Vitex rotundifolia L. f. and Vitex trifolia L. have wealthy chemical constituents and extensive pharmacological activities and are widely used in clinical practice from traditional to modern times. However, the research on the pharmacological activities of Vitex rotundifolia L. f. and Vitex trifolia L. is not in-depth, and the potential active components still need to be explored.

Auxotrophs compromise cell growth and fatty acid production in Saccharomyces cerevisiae.

Auxotrophic marker genes have been widely used for genetic engineering in yeast. However, the effects of amino acids or nucleotides deficiency in auxotrophic strains on cell growth and product synthesis were rarely reported. In this study, a total of eight auxotrophic strains of Saccharomyces cerevisiae with single knockout of selection markers were obtained. Cell growth and free fatty acid (FFA) production of these auxotrophic strains were evaluated with supplementation of different concentrations of amino acids or nucleotides. Generally, except ade2Δ mutants, most auxotrophic strains showed decreased cell growth and FFA production, which could be recovered by adding higher concentrations of supplements. LEU2 deletion (leu2Δ) damaged both cell growth and FFA production even with supplementation of 1000 mg L-1 leucine. This study shows that growth and product biosynthesis of auxotrophs could be limited by insufficient supplementation of amino acids or nucleotides, and provides guidance on supplementation of these nutrients during fermentation to maximize cell growth and product biosynthesis.

Antibacterial Activity Prediction Model of Traditional Chinese Medicine Based on Combined Data-Driven Approach and Machine Learning Algorithm: Constructed and Validated.

Traditional Chinese medicines (TCMs), as a unique natural medicine resource, were used to prevent and treat bacterial diseases in China with a long history. To provide a prediction model of screening antibacterial TCMs for the design and discovery of novel antibacterial agents, the literature about antibacterial TCMs in the China National Knowledge Infrastructure (CNKI) and Web of Science database was retrieved. The data were extracted and standardized. A total of 28,786 pieces of data from 904 antibacterial TCMs were collected. The data of plant medicine were the most numerous. The result of association rules mining showed a high correlation between antibacterial activity with cold nature, bitter and sour tastes, hemostatic, and purging fire efficacies. Moreover, TCMs with antibacterial activity showed a specific aggregation in the phylogenetic tree; 92% of them came from Tracheophyta, of which 74% were mainly concentrated in rosids, asterids, Liliopsida, and Ranunculales. The prediction models of anti-Escherichia coli and anti-Staphylococcus aureus activity, with AUC values (the area under the ROC curve) of 77.5 and 80.0%, respectively, were constructed by the Neural Networks (NN) algorithm after Bagged Classification and Regression Tree (Bagged CART) and Linear Discriminant Analysis (LDA) selection. The in vitro experimental results showed the prediction accuracy of these two models was 75 and 60%, respectively. Four TCMs (Cirsii Japonici Herba Carbonisata, Changii Radix, Swertiae Herba, Callicarpae Formosanae Folium) were proposed for the first time to show antibacterial activity against E. coli and/or S. aureus. The results implied that the prediction model of antibacterial activity of TCMs based on properties and families showed certain prediction ability, which was of great significance to the screening of antibacterial TCMs and can be used to discover novel antibacterial agents.

Improvement of the performance of simultaneous nitrification denitrification and phosphorus removal (SNDPR) system by nitrite stress.

This study investigated a new way to improve the performance of simultaneous nitrification denitrification and phosphorus removal (SNDPR) system by regularly changing the anaerobic/micro-aerobic/anoxic mode to the anaerobic/anoxic mode with 30 mg/L of nitrite dosing. The results indicated that the removal efficiency of total inorganic nitrogen and PO43--P was improved from 75.44% and 85.14% to 98.89% and 98.17%, respectively. And the good performance of the SNDPR showed a long-time sustainability when the C/N ratio was 5. The results of microbial community illustrated that the abundance of the main nitrite-oxidizing bacteria (NOB), Nitrospira sp., dropped from 5.71% to 0.85% and the abundance of denitrifying polyphosphate-accumulating organisms (DPAOs), Pseudomonas sp. and Acinetobacter sp., increased by 5 times after nitrite stress. The high level of nitric oxide (NO) and free nitrite acid produced by addition of nitrite strongly suppressed the undesired organisms NOB and ordinary heterotrophic denitrifying organisms, and promoted the enrichment of DPAOs. The NO accumulated in the nitrite denitrification process could inhibit NOB and promote AOB. This study revealed that NO plays an important role in regulating the microbial community in the SNDPR system.