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Identification of phytochemicals, inhibitors for MAO-b and COMT: An in silico approach

Authors: Harshnad Maru; Kotak Heema; Jani, Krishna; Tarpara Pravina; Trivedi Meera; Georrge, John J.;

Identification of phytochemicals, inhibitors for MAO-b and COMT: An in silico approach

Abstract

Parkinson’s disease (PD) is a neurodegenerative, progressive, and incurable disorder characterized by patients’ cardinal motor and non-motor features. In severe cases, PD can be diagnosed by deformity of motor skills such as shivering, rigidity, decreased muscle movement, and dementia. The significant proteins responsible for PD are COMT and MAO-B. Inhibition of these proteins can pacify this gruesome disorder. As it is known that plant secondary metabolites have widely been used as potential drug candidates, and almost 85% of the modern drugs are the derivatives of these phytochemicals, they can play a crucial role in treating PD. Indian and Chinese herbal extracts with Green tea extracts are the most potent draggable candidates for PD treatments. Antioxidant phytochemicals such as Anthocyanins, Levodopamine, Catechin have proven effective against PD. This presentation depicts the in silico molecular docking study of 18 potent secondary metabolites derived from various plants and a comparative analysis of the approved drugs used to treat PD with the help of bioinformatics tools and repositories.

Keywords

Anthocyanins, Parkinson's disease, neurodegenerative, Levodopamine, bioinformatics, Catechin

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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