Effects of rice-prawn (Macrobrachium nipponense) co-culture on the microbial community of soil.

In the Lixiahe region of China, co-culture has been rapidly promoted in flooded paddy fields owing to its ecological and economic benefits. Rice-prawn co-culture can reduce the damage of crab and shrimp to rice growth and paddy field and substantially change the soil microbial community and soil fertility. In this study, we compared changes in the soil microbial community and soil fertility in waterlogged paddies under conventional rice culture (CR), rice-prawn (Macrobrachium nipponense) co-culture (RP), and pond culture (PC). The microbial abundance in RP was significantly higher than that in CR. RP soil microbial diversity was significantly higher than PC soil microbial diversity. The dominant bacteria in RP soil were Proteobacteria, Chloroflexi, and Bacteroidetes. Compared with those in CR, total organic matter (TOM) and total nitrogen in RP were relatively stable, available potassium and available phosphorus (AP) decreased, and other indicators increased significantly. Soil fertility significantly benefited from co-culture, with total organic carbon (TOC) increasing. Interactive relationship analysis showed that TOM, TOC, AP, and NH4+-N were the main factors affecting the microbial community. Co-occurrence network analyses showed that network modularity increased with co-culture, indicating that a unique soil microbial community formed under co-culture, improving the adaptability and tolerance to co-culture. Thus, RP is a suitable culture method for this commercially important species. The results of this study can inform the practical operation of fertilizer use and sustainable development of rice-prawn aquaculture systems. KEY POINTS: • Microbial abundance and diversity increased under rice-prawn co-culture. • Co-culture significantly improved soil fertility, with an increase in TOC. • Rice-prawn co-culture is an ecologically suitable culture method for prawns.

In Silico Prediction of Endocrine Disrupting Chemicals Using Single-Label and Multilabel Models.

Endocrine disruption (ED) has become a serious public health issue and also poses a significant threat to the ecosystem. Due to complex mechanisms of ED, traditional in silico models focusing on only one mechanism are insufficient for detection of endocrine disrupting chemicals (EDCs), let alone offering an overview of possible action mechanisms for a known EDC. To remove these limitations, in this study both single-label and multilabel models were constructed across six ED targets, namely, AR (androgen receptor), ER (estrogen receptor alpha), TR (thyroid receptor), GR (glucocorticoid receptor), PPARg (peroxisome proliferator-activated receptor gamma), and aromatase. Two machine learning methods were used to build the single-label models, with multiple random under-sampling combining voting classification to overcome the challenge of data imbalance. Four methods were explored to construct the multilabel models that can predict the interaction of one EDC against multiple targets simultaneously. The single-label models of all the six targets have achieved reasonable performance with balanced accuracy (BA) values from 0.742 to 0.816. Each top single-label model was then joined to predict the multilabel test set with BA values from 0.586 to 0.711. The multilabel models could offer a significant boost over the single-label baselines with BA values for the multilabel test set from 0.659 to 0.832. Therefore, we concluded that single-label models could be employed for identification of potential EDCs, while multilabel ones are preferable for prediction of possible mechanisms of known EDCs.

Computational Investigation of Ligand Binding to the Peripheral Site in CYP3A4: Conformational Dynamics and Inhibitor Discovery.

Human cytochrome P450 3A4 (CYP3A4) is a major drug-metabolizing enzyme responsible for the metabolism of ∼50% of clinically used drugs and is often involved in drug-drug interactions. It exhibits atypical binding and kinetic behavior toward many ligands. Binding of ligands to CYP3A4 is a complex process. Recent studies from both crystallography and biochemistry suggested the existence of a peripheral ligand-binding site at the enzyme surface. However, the stability of the ligand bound at this peripheral site and the possibility of discovering new CYP3A4 ligands based on this site remain unclear. In this study, we employed a combination of molecular docking, multiparalleled molecular dynamics (MD) simulations, virtual screening, and experimental bioassay to investigate these issues. Our results revealed that the binding mode of progesterone (PGS), a substrate of CYP3A4, in the crystal structure was not stable and underwent a significant conformational change. Through Glide docking and MD refinement, it was found that PGS was able to stably bind at the peripheral site via contacts with Phe215, Phe219, Phe220, and Asp214. On the basis of the refined peripheral site, virtual screening was then performed against the Enamine database. A total of three compounds were finally found to have inhibitory activity against CYP3A4 in both human liver microsome and recombinant human CYP3A4 enzyme assays, one of which showed potent inhibitory activity with IC50 lower than 1 µM and two of which exhibited moderate inhibitory activity with IC50 values lower than 10 µM. The findings not only presented the dynamic behavior of PGS at the peripheral site but also demonstrated the first indication of discovering CYP3A4 inhibitors based on the peripheral site.