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

Abstract

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.

Keywords:

• ligand shape-based virtual screening
• useful Decoys (DUD)
• area under the ROC curve (AUC)

Acknowledgments

The research was supported in part by Tunisian State Secretariat for Research and Technology and by UNDP/World Bank/WHO (Grant N° 990960 to A. Hamza). This work is realized in memory of Mme Om el khir Hamza, April 2012. The authors acknowledge the Computer Center at University of Kentucky for supercomputing time on a Dell Supercomputer Cluster consisting of 388 nodes or 4816 processors.