2019
DOI: 10.1016/j.jtice.2019.08.005
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Identification of novel inhibitors of p-hydroxyphenylpyruvate dioxygenase using receptor-based virtual screening

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Cited by 25 publications
(7 citation statements)
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“…The best way to predict the interaction of small molecules with receptor binding pockets at the molecular level is molecular docking. To understand the mechanism by which compound 6c and Oxyfluorfen acted on the target site of PPO, molecular docking experiments were carried out. As shown in Figure , the results showed that compound 6c and Oxyfluorfen had similar interactions with the surrounding amino acid residues but the interaction of compound 6c with amino acid residues was stronger than that of Oxyfluorfen.…”
Section: Resultsmentioning
confidence: 99%
“…The best way to predict the interaction of small molecules with receptor binding pockets at the molecular level is molecular docking. To understand the mechanism by which compound 6c and Oxyfluorfen acted on the target site of PPO, molecular docking experiments were carried out. As shown in Figure , the results showed that compound 6c and Oxyfluorfen had similar interactions with the surrounding amino acid residues but the interaction of compound 6c with amino acid residues was stronger than that of Oxyfluorfen.…”
Section: Resultsmentioning
confidence: 99%
“…Protein–ligand crystal interactions were solvated through a simple point charge (SPC) water model with an orthogonal box with boundary conditions 46 . In addition, the OPLS_2005 force field was used to minimize the energy of the complex system at the maximum interaction of 2000 and a convergence threshold of 1.0 kcal mol Å −1 47 . The most rapid descent and limited‐memory Broyden–Fletcher–Goldfarb–Shanno (LBFGS) algorithm minimized the system energy in up to 5000 steps until a gradient threshold of 25 kcal mol Å −1 was reached.…”
Section: Methodsmentioning
confidence: 99%
“…Starting from the cocrystallyzed complex between AtHPPD and sulcotrione (entry 6isd of the protein data bank, Table 1), the receptor−ligand pharmacophore generation routine of the DiscoveryStudio software was applied to build a structurebased pharmacophoric model constituted by aromatic ring features that accounted for the interaction with Phe381 and Phe424, hydrophobic regions that contacted Pro280, and hydrogen bond acceptor/donor features that were responsible for iron chelation. 55 The model was then used to virtually screen the Zinc database and the prioritized compounds were further pruned by molecular docking and dynamics simulations. Six compounds were eventually identified (Figure 27), characterized by terminal phenyl and amide moieties linked by a four-or five-membered spacer.…”
Section: ■ Computer-driven Design and Identification Of Hppd Inhibitorsmentioning
confidence: 99%