Gene/Protein Disease Symptom Drug Enzyme Compound
Pivot Concepts:   Target Concepts:
Query: EC:1.5.1.3 (dihydrofolate reductase)
 5,819 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

The molecular basis of the binding of the lipophilic antifolate compound fluoronitropyrimethamine [2,4-diamino-5-(4-fluoro-3-nitrophenyl)-6-ethylpyrimidine] to its target enzyme dihydrofolate reductase has been investigated using a combination of 19F NMR spectroscopy and molecular mechanical calculations. 19F NMR reveals the presence of two different conformational states for the fluoronitropyrimethamine-Lactobacillus casei enzyme complex. MM2 molecular mechanical calculations predict restricted rotation about the C5-C1' bond of the ligand and this gives rise to two slowly interconverting rotamers which are an enantiomeric pair. The results of 19F NMR spectroscopy reveal that both these isomers bind to the enzyme, with different affinities. There is no detectable interconversion of the bound rotamers themselves on the NMR timescale. The effect of the addition of co-enzyme to the sample is to reverse the preference the enzyme has for each rotamer.
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PMID:Direct 19F NMR observation of the conformational selection of optically active rotamers of the antifolate compound fluoronitropyrimethamine bound to the enzyme dihydrofolate reductase. 314 93

Modeling studies using 3D-QSAR and molecular docking methods were performed on a set of 34 hybrids of 4-aminoquinoline derivatives previously studied as effective antimalarial agents of wild type and quadruple mutant Plasmodium falciparum dihydrofolate reductase (DHFR). So, the famous mathematical method multiple linear regression (MLR) was explored to build the QSAR model. The DFT-B3LYP method with the basis set 6-31G was used to calculate the quantum chemical descriptors, chosen to represent the electronic descriptors of molecular structures. On the contrary, the MM2 method was used to calculate lipophilic, geometrical, physicochemical, and steric descriptors. The QSAR model tested with artificial neural network (ANN) method shows high performance towards its predictability. The predicted model was confirmed by three validation methods: leave-one-out (LOO) cross validation, Y-randomization, and validation external. The molecular docking study of three compounds 9, 11, and 26 on both wild and quadruple mutant types of pf-DHFR-TS as the protein target helps to understand more and then predict the binding modes with the binding sites.
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PMID:Molecular Modeling of Antimalarial Agents by 3D-QSAR Study and Molecular Docking of Two Hybrids 4-Aminoquinoline-1,3,5-triazine and 4-Aminoquinoline-oxalamide Derivatives with the Receptor Protein in Its Both Wild and Mutant Types. 3003 81