Discovery of Small-Molecule Activators for Glucose-6-Phosphate Dehydrogenase (G6PD) Using Machine Learning Approaches.

Glucose-6-Phosphate Dehydrogenase (G6PD) is a ubiquitous cytoplasmic enzyme converting glucose-6-phosphate into 6-phosphogluconate in the pentose phosphate pathway (PPP). The G6PD deficiency renders the inability to regenerate glutathione due to lack of Nicotine Adenosine Dinucleotide Phosphate (NADPH) and produces stress conditions that can cause oxidative injury to photoreceptors, retinal cells, and blood barrier function. In this study, we constructed pharmacophore-based models based on the complex of G6PD with compound AG1 (G6PD activator) followed by virtual screening. Fifty-three hit molecules were mapped with core pharmacophore features. We performed molecular descriptor calculation, clustering, and principal component analysis (PCA) to pharmacophore hit molecules and further applied statistical machine learning methods. Optimal performance of pharmacophore modeling and machine learning approaches classified the 53 hits as drug-like (18) and nondrug-like (35) compounds. The drug-like compounds further evaluated our established cheminformatics pipeline (molecular docking and in silico ADMET (absorption, distribution, metabolism, excretion and toxicity) analysis). Finally, five lead molecules with different scaffolds were selected by binding energies and in silico ADMET properties. This study proposes that the combination of machine learning methods with traditional structure-based virtual screening can effectively strengthen the ability to find potential G6PD activators used for G6PD deficiency diseases. Moreover, these compounds can be considered as safe agents for further validation studies at the cell level, animal model, and even clinic setting.

Amelioration of experimental autoimmune uveoretinitis by inhibition of glyceraldehyde-derived advanced glycation end-product formation.

AGEs are permanently modified macromolecule derivatives that form through nonenzymatic glycation of amino groups of proteins. Glycer-AGEs are highly toxic and play an important role in the pathogenesis of chronic inflammatory diseases. However, the contribution of glycer-AGEs to the pathogenesis of uveitis is unclear. In this study, we measured serum levels of glycer-AGEs in 100 patients with endogenous uveitis (22 with HLA-B27-associated uveitis, 20 with VKH disease, 14 with Behçet's disease, and 44 with sarcoidosis) and 33 healthy volunteers. We then examined the effect of the AGE inhibitor in a mouse model of human endogenous uveitis (EAU) by continuous oral administration of pyridoxamine at 200 or 400 mg/kg/day. Regardless of the etiology, serum glycer-AGE levels were significantly higher in patients with uveitis than in healthy subjects. Treatment with 400 mg/kg pyridoxamine significantly reduced the clinical and histological severity of EAU and was accompanied by a significant decrease in serum and retinal glycer-AGE levels and suppression of translocation of NF-κB p65 into the nucleus of retinal cells. Serum glycer-AGE levels may therefore serve as a biomarker of human uveitis, as well as systemic inflammation, and may contribute to the progression of uveitis, including diabetic iritis, via the activation of NF-κB.