Systematic comparison of ligand-based and structure-based virtual screening methods on poly (ADP-ribose) polymerase-1 inhibitors.

The poly (ADP-ribose) polymerase-1 (PARP1) has been regarded as a vital target in recent years and PARP1 inhibitors can be used for ovarian and breast cancer therapies. However, it has been realized that most of PARP1 inhibitors have disadvantages of low solubility and permeability. Therefore, by discovering more molecules with novel frameworks, it would have greater opportunities to apply it into broader clinical fields and have a more profound significance. In the present study, multiple virtual screening (VS) methods had been employed to evaluate the screening efficiency of ligand-based, structure-based and data fusion methods on PARP1 target. The VS methods include 2D similarity screening, structure-activity relationship (SAR) models, docking and complex-based pharmacophore screening. Moreover, the sum rank, sum score and reciprocal rank were also adopted for data fusion methods. The evaluation results show that the similarity searching based on Torsion fingerprint, six SAR models, Glide docking and pharmacophore screening using Phase have excellent screening performance. The best data fusion method is the reciprocal rank, but the sum score also performs well in framework enrichment. In general, the ligand-based VS methods show better performance on PARP1 inhibitor screening. These findings confirmed that adding ligand-based methods to the early screening stage will greatly improve the screening efficiency, and be able to enrich more highly active PARP1 inhibitors with diverse structures.

[Spatial variability of nutrients and heavy metals in paddy field soils based on GIS and Geostatistics.] / 基于GISå’Œåœ°ç»Ÿè®¡å­¦çš„ç¨»ç”°åœŸå£¤å »åˆ†ä¸Žé‡é‡‘å±žç©ºé—´å˜å¼‚.

Based on a grid (25 m X 25 m) equidistant sampling, the spatial variability of pH, organic matter, total nitrogen, available phosphorus, CEC and three typical heavy metal elements Cd, As and Pb in soil tillage layer (0-20 cm) were analyzed by using GIS and Geostatistics in the paddy field of 3.56 hm2 in Beishan Town, Changsha County, Hunan Province. The results showed that soil pH value and Pb content showed weak variation, and other indexes showed moderate variation. The order of variation was following available phosphorus ＞ Cd ＞ total nitrogen ＞ organic matter ＞ CEC ＞ As ＞ Pb ＞ pH. Results of the semi-variance test showed that the best fitting model of the semi-variance function of organic matter, available phosphorus and As was exponential, and the best semi-variance function of pH, total nitrogen, CEC, Cd, Pb was spherical. All the indicators had a strong spatial correlation except for CEC, which showed moderate spatial correlation. Kriging interpolation analysis showed that pH, total nitrogen, CEC, Pb were plaque distribution, while organic matter, available phosphorus, Cd and As were block and banded distribution. Vegetation, topography and human activities were the main factors driving the variation of soil nutrients and heavy metals in the study area. The correlation between soil nutrients and heavy metals content was significant, among which pH and organic matter, Cd and Pb reached a very significant correlation level.