title: 3D-QSAR studies of triazolopyrimidine derivatives of Plasmodium falciparum dihydroorotate dehydrogenase inhibitors using a combination of molecular dynamics, docking, and genetic algorithm-based methods.
abstract: A series of 35 triazolopyrimidine analogues reported as Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH) inhibitors were optimized using quantum mechanics methods, and their binding conformations were studied by docking and 3D quantitative structure-activity relationship studies. Genetic algorithm-based criteria was adopted for selection of training and test sets while maintaining structural diversity of training and test sets, which is also very crucial for model development and validation. Both the comparative molecular field analyses ([Formula: see text], [Formula: see text]) and comparative molecular similarity indices analyses ([Formula: see text], [Formula: see text]) show excellent correlation and high predictive power. Furthermore, molecular dynamics simulations were performed to explore the binding mode of the two of the most active compounds of the series, 10 and 14. Harmonization in the two simulation results validate the analysis and therefore applicability of docking parameters based on crystallographic conformation of compound 14 bound to receptor molecule. This work provides useful information about the inhibition mechanism of this class of molecules and will assist in the design of more potent inhibitors of PfDHODH.
authors: Molecular and Structural Biology Division, Central Drug Research Institute, Lucknow, 226 001 India.
authors: Priyanka
authors: P
authors: Shah
authors: Sumit
authors: S
authors: Kumar
authors: Sunita
authors: S
authors: Tiwari
authors: Mohammad Imran
authors: MI
authors: Siddiqi
keywords: Genetic algorithm-based feature selection, hierarchical clustering, and docking; Molecular dynamics; QSAR
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