Discovery of N-(phenylsulfonyl)thiazole-2-carboxamides as potent α-glucosidase inhibitors.

In a search for novel nonsugar α-glucosidase inhibitors for diabetes treatment, a series of N-(phenylsulfonyl)thiazole-2-carboxamide derivatives were designed and synthesized, the α-glucosidase inhibitory activities were then evaluated. Several compounds with promising α-glucosidase inhibitory effects were identified. Among these, compound W24 which shows low cytotoxicity and good α-glucosidase inhibitory activity with an IC50 value of 53.0 ± 7.7 µM, is more competitive compared with the commercially available drug acarbose (IC50 = 228.3 ± 9.2 µM). W24 was identified as a promising candidate in the development of α-glucosidase inhibitors. Molecular docking studies and molecular dynamics simulation were also performed to reveal the binding pattern of the active compound to α-glucosidase, and the binding free energy of the best compound W24 was 36.3403 ± 3.91 kcal/mol.

[Study on a method for fast selecting feature wavelengths from the spectral information of crop nitrogen].

Research on a method for fast selecting feature wavelengths from the nitrogen spectral information is necessary, which can determine the nitrogen content of crops. Based on the uniformity of uniform design, the present paper proposed an improved particle swarm optimization (PSO) method. The method can choose the initial particle swarm uniformly and describe the optimization space well by fewer sample points, which is helpful to avoiding the local optimum and accelerate the convergence. Then, the method was applied to fast select the nitrogen spectral wavelengths of soybean, cotton and maize. Calibration models based on the partial least square (PLS) method and selected wavelengths were constructed. The results illustrate that compared with the original wavelengths, the number of selected wavelengths decreases about 93%, which means the computation is simplified. Also, the precision of PLS prediction mode based on the selected wavelengths improves by 34% at least, and the prediction ability of calibration model increases greatly. Therefore, the proposed method is both correct and effective.