madhubioinformatics

CXCR5-knockout-AMD

The role of CXCR5 (C-X-C motif chemokine receptor 5) in age-related macular degeneration (AMD) remains elusive. The objective of this study is to investigate the role of chemokine receptor Cxcr5 in the pathogenesis of AMD.

G6PD-activators-Machine-learning

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 NADPH and produces the oxidative injury in retina that accelerate the dystrophic conditions to photoreceptor cells and damage the retinal blood barrier function. In this study, we constructed pharmacophore-based models based on the compound complex of G6PD with AG1 (G6PD activator) followed by virtual screening. 53 hit molecules were mapped with core pharmacophore features. We calculated molecular descriptors, clustering, principle component analysis (PCA) to pharmacophore hit molecules and further applied statistical machine learning methods . Results showed that the all model performed best and classified as drug-like (18) and nondrug-like (35) compounds. The drug-like compounds were further evaluated our established cheminformatics pipeline (molecular docking and in silico ADMET analysis). Finally, five hits with different scaffolds were picked out for docking studies and in silico ADMET analysis. This study proposes that the combination of machine learning methods with traditional structure-based virtual screening can effectively strengthen the ability in finding potential G6PD activators designing for G6PD deficiency diseases. Moreover, these compounds can be considered as safe agents for further validation studies at cell level, animal model, and even clinic setting.

PDAC_GPH

Mechanism of Enhancing Chemotherapy Efficacy in Pancreatic Ductal Adenocarcinoma with Paricalcitol and Hydroxychloroquine: A Single Cell RNA Sequencing

PlGF-regulates-PPP-pathway

scRNA-seq-data-analysis

hdWGCNA

High dimensional weighted gene co-expression network analysis

madhubioinformatics/G6PD-activators-Machine-learning

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 NADPH and produces the oxidative injury in retina that accelerate the dystrophic conditions to photoreceptor cells and damage the retinal blood barrier function. In this study, we constructed pharmacophore-based models based on the compound complex of G6PD with AG1 (G6PD activator) followed by virtual screening. 53 hit molecules were mapped with core pharmacophore features. We calculated molecular descriptors, clustering, principle component analysis (PCA) to pharmacophore hit molecules and further applied statistical machine learning methods . Results showed that the all model performed best and classified as drug-like (18) and nondrug-like (35) compounds. The drug-like compounds were further evaluated our established cheminformatics pipeline (molecular docking and in silico ADMET analysis). Finally, five hits with different scaffolds were picked out for docking studies and in silico ADMET analysis. This study proposes that the combination of machine learning methods with traditional structure-based virtual screening can effectively strengthen the ability in finding potential G6PD activators designing for G6PD deficiency diseases. Moreover, these compounds can be considered as safe agents for further validation studies at cell level, animal model, and even clinic setting.

madhubioinformatics/ClearSeqExtend

madhubioinformatics/CXCR5-knockout-AMD

The role of CXCR5 (C-X-C motif chemokine receptor 5) in age-related macular degeneration (AMD) remains elusive. The objective of this study is to investigate the role of chemokine receptor Cxcr5 in the pathogenesis of AMD.

madhubioinformatics/PlGF-regulates-PPP-pathway

madhubioinformatics/scRNA-seq-data-analysis