Comparative study between 3D-QSAR and Docking-Based Pharmacophore models for potent Plasomodium falciparum dihydroorotate dehydrogenase inhibitors. Issue 2 (15th January 2016)

• Record Type: Journal Article
• Authors: Tseng, Tien-Sheng; Lee, Yu-Ching; Hsiao, Nai-Wan; Liu, Yun-Ru; Tsai, Keng-Chang
• Is Part Of: Bioorganic & medicinal chemistry letters. Volume 26:Issue 2(2016)
• Page Start: 265
• Page End: 271
• Publication Date: 2016-01-15
• Subjects: Pharmacophore -- PfDHODH inhibitor -- Catalyst -- 3D-QSAR Pharmacophore Generation -- Docking-Based Pharmacophore Development; Bioorganic chemistry -- Periodicals; Pharmaceutical chemistry -- Periodicals; 572
• DOI: 10.1016/j.bmcl.2015.12.043
• Languages: English
• ISSNs: 0960-894X

Abstract

Graphical abstract: The pharmacophore mapped conformation of the test compound NO.65 (equal ensemble of A26) is well-overlapped with the A26 inhibitor of Pf DOHDH complex structure (PDB ID:1TV5 ), rmsd = 0.475. Abstract: Malaria, caused by infections of the human malaria parasites Plasmodium falciparum, is a global infectious parasitic disease. Each year, about three million people died from malaria and the majority of whom are pregnant women and young children. Recently, a number of research attempt to reduce malaria parasite resistance and the toxicity of anti-malarial drugs. Nowadays, Plasmodium falciparum dihydroorotate dehydrogenase ( Pf DHODH) was validated as a potent drug target to inhibit malarial activity by blocking pyrimidine biosynthesis. In this study, we employed 3D-QSAR Pharmacophore Generation and Docking-Based Pharmacophore Development to build the pharmacophore by using the collected 67 effective inhibitors against Pf DHODH. 3D-QSAR Pharmacophore model, Hypo1, shows the high correlation coefficient (0.935), the lowest RMS deviation (2.15), the predicting accuracy of successful rates to training set (89.4%) and test set compounds (72.4%), respectively, revealing favorable predictive ability and is a reliable for further study. Additionally, Docking-Based Pharmacophore model, DBP-All255, exhibits comparable predictive capability to that of Hypo1, while DBP-Top1 shows poor statistical significance. This study reveals pharmacophore features of Hypo1, built by 3D-QSAR Pharmacophore Generation, are well-complementary to the functional residues in the active site of Pf DHODH and is of great reliable for database screening.