Abstract

In-silico Ligands Target Prediction of Potential Inhibitors against Dementia using Chemo Informatics Approach

Author(s): Wamankar Suchita*, Gupta Anshita and Kaur Chanchal Deep

Background: One of the most prevalent neurodegenerative diseases, dementia is characterized by gradual memory loss and cognitive impairment. It has a variety of neurological signs that affect memory, judgement and social skills. The variety of ligands that may be investigated using experimental assays has fallen with the help of efficient in silico drug design techniques.

Methods: Through a review of the literature, seven phytochemicals that are effective against dementia were chosen for the current investigation. Using chemo-informatics tools like SWISS and the Molinspiration online server, these ligands were docked with putative Choline Esterase (ChE), N-Methyl-D-Aspartate (NMDA) and calcium channel receptors. Using in-silico study, the binding energies of the target-ligand complex and the ADME (absorption, distribution, metabolis and excretion) profile of phytochemicals were examined.

Results: A result showed that seven active phytochemicals had a higher binding energy values for Choline Esterase (ChE) receptor. And Resveratrol and Berberine also exhibited good ADME profiles that easily penetrate BBB and having potential inhibitory properties against Choline Esterase (ChE) receptor using chemo-informatics approaches.

Conclusions: These outcomes probably provide insight on the prospect of using resveratrol and berberine as an instance for developing new drugs for managing dementia.

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