Identification of potential AChE inhibitors through combined machine-learning and structure-based design approaches

Alzheimer’s disease (AD) is an irreversible, progressive neurodegenerative disease characterised by dementia.The depletion of acetylcholine (ACh) is involved the synaptic cleft is responsible for dementia due to neuronal loss. The acetylcholinesterase (AChE) enzyme isinvolved in the hydrolytic degradation of ACh and its inhibition is therapeutically beneficial for the treatment in memory loss.The use of machine learning (ML) for the identification of enzyme inhibitors has recently become popular. It identifies important patterns in the reported inhibitors to predict the new molecules. Hence, in this study, a set of support vector classifier-based ML models were developed,validated and employed to predict AChE inhibitors. Further, 247 predicted compounds obtained through PAINS and molecular property filters were docked on the AChE enzyme. The docking study identified compounds AAM132011183, ART21232619 and LMG16204648 as AChE inhibitors with suitable ADME properties. The selected compounds produced stable interactions with enzymes in molecular dynamics studies. The novel inhibitors obtained from the study may be proposed as active leads for AChE inhibition

Glycolytic enzyme inhibitory and antiglycation potential of rutin

The aim of the present was to determine the mechanism for the antidiabetic potential exerted by rutin by studying its effect on the glycolytic enzyme inhibitory and antiglycation potential. For the determination of glycolytic enzyme inhibitory potential of rutin, porcine pancreatic amylase inhibitory assay and α-glucosidase inhibitory assay were performed. The antiglycation potential was determined by glycation of bovine serum albumin followed by antiglycation estimation of fructosamines adducts, protein carbonyls, protein thiols, congo red absorbance. Rutin showed a significant inhibition of α-amylase (p < 0.001; 53.66%) and α-glucosidase (p < 0.001; 52.56%). To study antiglycation potential, various parameters were determined and fructosamine inhibition was found to be 35.55%, protein carbonyls were inhibited up to 13.49%. Protein thiols were inhibited up to 80.27%. In the present study, it was concluded that rutin showed glycolytic enzyme inhibitory and antiglycation potential

Identification of potential AChE inhibitors through combined machine-learning and structure-based design approaches

619-631Alzheimer’s disease (AD) is an irreversible, progressive neurodegenerative disease characterised by dementia.The depletion of acetylcholine (ACh) is involved the synaptic cleft is responsible for dementia due to neuronal loss. The acetylcholinesterase (AChE) enzyme isinvolved in the hydrolytic degradation of ACh and its inhibition is therapeutically beneficial for the treatment in memory loss.The use of machine learning (ML) for the identification of enzyme inhibitors has recently become popular. It identifies important patterns in the reported inhibitors to predict the new molecules. Hence, in this study, a set of support vector classifier-based ML models were developed,validated and employed to predict AChE inhibitors. Further, 247 predicted compounds obtained through PAINS and molecular property filters were docked on the AChE enzyme. The docking study identified compounds AAM132011183, ART21232619 and LMG16204648 as AChE inhibitors with suitable ADME properties. The selected compounds produced stable interactions with enzymes in molecular dynamics studies. The novel inhibitors obtained from the study may be proposed as active leads for AChE inhibition

Effect of sulfonamide derivatives of phenylglycine on scopolamine‐induced amnesia in rats

Abstract Alzheimer's disease is a neurodegenerative disease responsible for dementia and other neuropsychiatric symptoms. In the present study, compounds 30 and 33, developed earlier in our laboratory as selective butyrylcholinesterase inhibitors, were tested against scopolamine‐induced amnesia to evaluate their pharmacodynamic effect. The efficacy of the compounds was determined by behavioral experiments using the Y‐maze and the Barnes maze and neurochemical testing. Both compounds reduced the effect of scopolamine treatment in the behavioral tasks at a dose of 20 mg/kg. The results of the neurochemical experiment indicated a reduction in cholinesterase activity in the prefrontal cortex and the hippocampus. The levels of antioxidant enzymes superoxide dismutase and catalase were restored compared to the scopolamine‐treated groups. The docking study on rat butyrylcholinesterase (BChE) indicated tight binding, with free energies of −9.66 and −10.23 kcal/mol for compounds 30 and 33, respectively. The two aromatic amide derivatives of 2‐phenyl‐2‐(phenylsulfonamido) acetic acid produced stable complexes with rat BChE in the molecular dynamics investigation

Tuberculosis: integrated studies for a complex disease 2050

Tuberculosis (TB) has been a disease for centuries with various challenges [1]. Like other places where challenges and opportunities come together, TB challenges were the inspiration for the scientific community to mobilize different groups for the purpose of interest. For example, with the emergence of drug resistance, there has been a huge volume of research on the discovery of new medicines and drug delivery methods and the repurposing of old drugs [2, 3]. Moreover, to enhance the capacity to detect TB cases, studies have sought diagnostics and biomarkers, with much hope recently expressed in the direction of point-of-care tests [4]. Despite all such efforts as being highlighted in 50 Chapters of this volume, we are still writing about TB and thinking about how to fight this old disease–implying that the problem of TB might be complex, so calling the need for an integrated science to deal with multiple dimensions in a simultaneous and effective manner. We are not the first one; there have been proposed integrated platform for TB research, integrated prevention services, integrated models for drug screening, integrated imaging protocol, integrated understanding of the disease pathogenesis, integrated control models, integrated mapping of the genome of the pathogen, etc. [5–12], to name some. These integrated jobs date back decades ago. So, a question arises: why is there a disease named TB yet? It might be due to the fact that this integration has happened to a scale that is not global, and so TB remains to be a problem, especially in resource-limited settings. Hope Tuberculosis: Integrated Studies for a Complex Disease helps to globalize the integrated science of TB.info:eu-repo/semantics/publishedVersio