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Pharmacophore-Based Virtual Screening of Novel Competitive Inhibitors of the Neurodegenerative Disease Target Kynurenine-3-Monooxygenase.

ABSTRACT: The pathogenesis of several neurodegenerative diseases such as Alzheimer's or Huntington's disease has been associated with metabolic dysfunctions caused by imbalances in the brain and cerebral spinal fluid levels of neuroactive metabolites. Kynurenine monooxygenase (KMO) is considered an ideal therapeutic target for the regulation of neuroactive tryptophan metabolites. Despite significant efforts, the known KMO inhibitors lack blood-brain barrier (BBB) permeability and upon the mimicking of the substrate binding mode, are subject to produce reactive oxygen species as a side reaction. The computational drug design is further complicated by the absence of complete crystal structure information for human KMO (hKMO). In the current work, we performed virtual screening of readily available compounds using several protein-ligand complex pharmacophores. Each of the pharmacophores accounts for one of three distinct reported KMO protein-inhibitor binding conformations. As a result, six novel KMO inhibitors were discovered based on an in vitro fluorescence assay. Compounds VS1 and VS6 were predicted to be BBB permeable and avoid the hydrogen peroxide production dilemma, making them valuable, novel hit compounds for further drug property optimization and advancement in the drug design pipeline.

SUBMITTER: Gotina L

PROVIDER: S-EPMC8199213 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:AimTo identify the critical chemical features, with reliable geometric constraints, that contributes to the inhibition of butyrylcholinesterase (BChE) function.MethodsLigand-based pharmacophore modeling was used to identify the critical chemical features of BChE inhibitors. The generated pharmacophore model was validated using various techniques, such as Fischer's randomization method, test set, and decoy set. The best pharmacophore model was used as a query in virtual screening to identify novel scaffolds that inhibit BChE. Compounds selected by the best hypothesis in the virtual screening were tested for drug-like properties, and molecular docking study was applied to determine the optimal orientation of the hit compounds in the BChE active site. To find the reactivity of the hit compounds, frontier orbital analysis was carried out using density functional theory.ResultsBased on its correlation coefficient (0.96), root mean square (RMS) deviation (1.01), and total cost (105.72), the quantitative hypothesis Hypo1 consisting of 2 HBA, 1 Hy-Ali, and 1 Hy-Ar was selected as the best hypothesis. Thus, Hypo1 was used as a 3D query in virtual screening of the Maybridge and Chembridge databases. The hit compounds were filtered using ADMET, Lipinski's Rule of Five, and molecular docking to reduce the number of false positive results. Finally, 33 compounds were selected based on their critical interactions with the significant amino acids in BChE's active site. To confirm the inhibitors' potencies, the orbital energies, such as HOMO and LUMO, of the hit compounds and 7 training set compounds were calculated. Among the 33 hit compounds, 10 compounds with the highest HOMO values were selected, and this set was further culled to 5 compounds based on their energy gaps important for stability and energy transfer. From the overall results, 5 hit compounds were confirmed to be potential BChE inhibitors that satisfied all the pharmacophoric features in Hypo1.ConclusionThis study pinpoints important chemical features with geometric constraints that contribute to the inhibition of BChE activity. Five compounds are selected as the best hit BchE-inhibitory compounds.

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Pharmacophore-Based Virtual Screening of Novel Competitive Inhibitors of the Neurodegenerative Disease Target Kynurenine-3-Monooxygenase.

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