A novel and efficient ligand-based virtual screening approach using the HWZ scoring function and an enhanced shape-density model

In this work, we extend our previous ligand shape-based virtual screening approach by using the scoring function Hamza–Wei–Zhan (HWZ) score and an enhanced molecular shape-density model for the ligands. The performance of the method has been tested against the 40 targets in the Database of Useful Decoys and compared with the performance of our previous HWZ score method. The virtual screening results using the novel ligand shape-based approach demonstrated a favorable improvement (area under the receiver operator characteristics curve AUC?=?.89?±?.02) and effectiveness (hit rate HR^1%?=?53.0%?±?6.3 and HR^10%?=?71.1%?±?4.9). The comparison of the overall performance of our ligand shape-based method with the highest ligand shape-based virtual screening approach using the data fusion of multi queries showed that our strategy takes into account deeper the chemical information of the set of active ligands. Furthermore, the results indicated that our method are suitable for virtual screening and yields superior prediction accuracy than the other study derived from the data fusion using five queries. Therefore, our novel ligand shape-based screening method constitutes a robust and efficient approach to the 3D similarity screening of small compounds and open the door to a whole new approach to drug design by implementing the method in the structure-based virtual screening.     

种群增长的分段指数模型及其参数估计

本文给出了种群增长的分段指数模型其中N（t）是在时刻t种群的密度,No=N（t0）,r0和rl是群群的内禀增长率,t0是转变点,H（t-t0）=1,t≥t0,H（t-t0）=0,t＜t0．利用非线性模型的正割法（DUD,Doesn’tusederivatives）,可同时确定模型的所有参数（包括交点t0在内）．并用于描述长爪沙鼠种群动态．