HORDB a comprehensive database of peptide hormones.

Peptide hormones (also known as hormone peptides and polypeptide hormones) are hormones composed of peptides and are signal transduction molecules produced by a class of multicellular organisms. It plays an important role in the physiological and behavioral regulation of animals and humans as well as in the growth of plants. In order to promote the research on peptide hormones, we constructed HORDB database. The database currently has a total of 6024 entries, including 5729 peptide hormones, 40 peptide drugs and 255 marketed pharmaceutical preparations information. Each entry provided comprehensive information related to the peptide, including general information, sequence, activity, structure, physical information and literature information. We also added information on IC50, EC50, ED50, target, and whether or not the blood-brain barrier was crossed to the activity information note. In addition, HORDB integrates search and sequence analysis to facilitate user browsing and data analysis. We believe that the peptide hormones information collected by HORDB will promote the design and discovery of peptide hormones, All data are hosted and available in figshare https://doi.org/10.6084/m9.figshare.c.5522241 .

DRAMP 3.0: an enhanced comprehensive data repository of antimicrobial peptides.

Stapled antimicrobial peptides are an emerging class of artificial cyclic peptide molecules which have antimicrobial activity and potent structure stability. We previously published the Data Repository of Antimicrobial Peptides (DRAMP) as a manually annotated and open-access database of antimicrobial peptides (AMPs). In the update of version 3.0, special emphasis was placed on the new development of stapled AMPs, and a subclass of specific AMPs was added to store information on these special chemically modified AMPs. To help design low toxicity AMPs, we also added the cytotoxicity property of AMPs, as well as the expansion of newly discovered AMP data. At present, DRAMP has been expanded and contains 22259 entries (2360 newly added), consisting of 5891 general entries, 16110 patent entries, 77 clinical entries and 181 stapled AMPs. A total of 263 entries have predicted structures, and more than 300 general entries have links to experimentally determined structures in the Protein Data Bank. The update also covers new annotations, statistics, categories, functions and download links. DRAMP is available online at http://dramp.cpu-bioinfor.org/.

Strategies to Increase the Production of Biosynthetic Riboflavin.

Riboflavin is widely regarded as an essential nutrient that is involved in biological oxidation in vivo. In addition to preventing and treating acyl-CoA dehydrogenase deficiency in patients with keratitis, stomatitis, and glossitis, riboflavin is also closely related to the treatment of radiation mucositis and cardiovascular disease. Chemical synthesis has been the dominant method for producing riboflavin for approximately 50 years. Nevertheless, due to the intricate synthesis process, relatively high cost, and high risk of pollution, alternative methods of chemical syntheses, such as the fermentation method, began to develop and eventually became the main methods for producing riboflavin. At present, there are three types of strains used in industrial riboflavin production: Ashbya gossypii, Candida famata, and Bacillus subtilis. Additionally, many recent studies have been conducted on Escherichia coli and Lactobacillus. Fermentation increases the yield of riboflavin using genetic engineering technology to modify and induce riboflavin production in the strain, as well as to regulate the metabolic flux of the purine pathway and pentose phosphate pathway (PP pathway), thereby optimizing the culture process. This article briefly introduces recent progress in the fermentation of riboflavin.

Applications of machine-learning methods for the discovery of NDM-1 inhibitors.

The emergence of New Delhi metal beta-lactamase (NDM-1)-producing bacteria and their worldwide spread pose great challenges for the treatment of drug-resistant bacterial infections. These bacteria can hydrolyze most ß-lactam antibacterials. Unfortunately, there are no clinically useful NDM-1 inhibitors. In the current work, we manually collected NDM-1 inhibitors reported in the past decade and established the first NDM-1 inhibitor database. Four machine-learning models were constructed using the structural and property characteristics of the collected compounds as input training set to discover potential NDM-1 inhibitors. In order to distinguish between high active inhibitors and putative positive drugs, a three-classification strategy was introduced in our study. In detail, the commonly used positive and negative divisions are converted into strongly active, weakly active, and inactive. The accuracy of the best prediction model designed based on this strategy reached 90.5%, compared with 69.14% achieved by the traditional docking-based virtual screening method. Consequently, the best model was used to virtually screen a natural product library. The safety of the selected compounds was analyzed by the ADMET prediction model based on machine learning. Seven novel NDM-1 inhibitors were identified, which will provide valuable clues for the discovery of NDM-1 inhibitors.

DRAMP 2.0, an updated data repository of antimicrobial peptides.

Data Repository of Antimicrobial Peptides (DRAMP, http://dramp.cpu-bioinfor.org/ ) is an open-access comprehensive database containing general, patent and clinical antimicrobial peptides (AMPs). Currently DRAMP has been updated to version 2.0, it contains a total of 19,899 entries (newly added 2,550 entries), including 5,084 general entries, 14,739 patent entries, and 76 clinical entries. The update covers new entries, structures, annotations, classifications and downloads. Compared with APD and CAMP, DRAMP contains 14,040 (70.56% in DRAMP) non-overlapping sequences. In order to facilitate users to trace original references, PubMed_ID of references have been contained in activity information. The data of DRAMP can be downloaded by dataset and activity, and the website source code is also available on dedicatedly designed download webpage. Although thousands of AMPs have been reported, only a few parts have entered clinical stage. In the paper, we described several AMPs in clinical trials, including their properties, indications and clinicaltrials.gov identifiers. Finally, we provide the applications of DRAMP in the development of AMPs.

Placental trophoblasts shifted Th1/Th2 balance toward Th2 and inhibited Th17 immunity at fetomaternal interface.

The aims were to clarify the effect of placental trophoblasts on T lymphocytes by assessing production of cytokines and expression of transcription factors regulating Th1, Th2, and Th17 immunity in T lymphocytes. Placental trophoblasts were isolated and conditioned medium was made after trophoblast cultivation for 72 h. T lymphocytes were cultured in presence or absence of conditioned medium. ELISA was used to detect concentration of IL-2, TNF-α, IFN-γ, IL-4, IL-10, and IL-17 in supernatants of T cell and real-time PCR was used to detect the status of Th1 (T-bet, STAT-4), Th2 (GATA-3, STAT-6), and Th17 (RORC) immunity in T lymphocyte. We found that the level of IL-2, IFN-γ, TNF-α, and IL-17 was significantly decreased when T lymphocytes were cultured in conditioned medium compared with control, while IL-10 and IL-4 level were not significantly changed. The presence of conditioned medium significantly decreased the ratio of Th1/Th2. The expression of GATA-3 and STAT-6 were significantly increased and STAT-4 was reduced when T lymphocyte was cultured in conditioned medium, while the expression of T-bet and RORC was not significantly different. We concluded that placental trophoblast-induced shift of Th1/Th2 balance toward Th2 and inhibition of Th17 might be among the mechanisms involved in maternal tolerance to fetus.