In silico chemical profiling and identification of neuromodulators from Curcuma amada targeting acetylcholinesterase

AbstractCurcuma amada is a potent medicinal herb with diverse bioactive molecules, demonstrating anti-inflammatory, antihypercholesterolemic, and antioxidant properties, and used conventionally to treat various neurodegenerative diseases, including Alzheimer ’s disease (AD). The present study characterized the secondary metabolites ofCurcuma amada for their drug-likeness properties, identified potent hits by targeting Acetylcholinesterase (AChE). Here in silico ADMET analysis was performed for chemical profiling, while molecular docking and molecular dynamics (MD) simulations were used for hit selection and binding characterizations. Accordingly, ADMET analysis showed that around 87.59% of compounds processed drug-likeness activity, and 92.07% of compounds have the BBB crossing ability, while 87.59% of compounds were active in the CNS system. Four compounds were screened out by molecular docking simulation, where the curcumin derivatives (demethoxycurcumin and bisdemethoxycurcumin) and β-sitosterol showed high binding energy and maintained substantial interactions with AChE during the MD simulation. Together, the present in silico-based characterization demonstratesCurcuma amada as a great source of neuromodulating agents, which can be considered in complementary and alternative medicine and drug development for preventing and treating neurodegenerative disorders.
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - Category: Bioinformatics Source Type: research

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