Degrading Characterization of the Newly Isolated Nocardioides sp. N39 for 3-Amino-5-methyl-isoxazole and the Related Genomic Information.

3-amino-5-methyl-isoxazole (3A5MI) is a persistent and harmful intermediate in the degradation of antibiotic sulfamethoxazole. It was accumulated in the environments day by day and has caused great environmental risks due to its refractory characteristic. Microbial degradation is economic and environmentally friendly and a promising method to eliminate this pollutant. In this study, a bacterial strain, Nocardioides sp. N39, was isolated. N39 can grow on 3A5MI as the sole carbon, nitrogen and energy resource. The effect of different factors on 3A5MI degradation by N39 was explored, including initial 3A5MI concentration, temperature, pH value, dissolved oxygen and additional carbon or nitrogen source. The degradation ability of N39 to various 3A5MI analogs was also explored. Nevertheless, the degrading ability of N39 for 3A5MI is not permanent, and long-term storage would lead to the loss of this ability. This may result from the mobile genetic elements in the bacterium according to the genomic comparison of N39 and its degrading ability-lost strain, N40. Despite this, N39 could support a lot of useful information about the degradation of 3A5MI and highlight the importance of studies about the environmental effects and potential degradation mechanism.

Virtual screening approach to identifying influenza virus neuraminidase inhibitors using molecular docking combined with machine-learning-based scoring function.

In recent years, an epidemic of the highly pathogenic avian influenza H7N9 virus has persisted in China, with a high mortality rate. To develop novel anti-influenza therapies, we have constructed a machine-learning-based scoring function (RF-NA-Score) for the effective virtual screening of lead compounds targeting the viral neuraminidase (NA) protein. RF-NA-Score is more accurate than RF-Score, with a root-mean-square error of 1.46, Pearson's correlation coefficient of 0.707, and Spearman's rank correlation coefficient of 0.707 in a 5-fold cross-validation study. The performance of RF-NA-Score in a docking-based virtual screening of NA inhibitors was evaluated with a dataset containing 281 NA inhibitors and 322 noninhibitors. Compared with other docking-rescoring virtual screening strategies, rescoring with RF-NA-Score significantly improved the efficiency of virtual screening, and a strategy that averaged the scores given by RF-NA-Score, based on the binding conformations predicted with AutoDock, AutoDock Vina, and LeDock, was shown to be the best strategy. This strategy was then applied to the virtual screening of NA inhibitors in the SPECS database. The 100 selected compounds were tested in an in vitro H7N9 NA inhibition assay, and two compounds with novel scaffolds showed moderate inhibitory activities. These results indicate that RF-NA-Score improves the efficiency of virtual screening for NA inhibitors, and can be used successfully to identify new NA inhibitor scaffolds. Scoring functions specific for other drug targets could also be established with the same method.