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Molecules
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Molecules
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Molecules
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Chemoinformatic Database Building and in Silico Hit-Identification of Potential Multi-Targeting Bioactive Compounds Extracted from Mushroom Species

Authors: Annalisa Maruca; Federica Moraca; Roberta Rocca; Fulvia Molisani; Francesca Alcaro; Maria Gidaro; Stefano Alcaro; +2 Authors

Chemoinformatic Database Building and in Silico Hit-Identification of Potential Multi-Targeting Bioactive Compounds Extracted from Mushroom Species

Abstract

Mushrooms are widely-consumed fungi which contain natural compounds that can be used both for their nutritive and medicinal properties, i.e., taking advantage of their antimicrobial, antiviral, antitumor, anti-allergic, immunomodulation, anti-inflammatory, anti-atherogenic, hypoglycemic, hepatoprotective and antioxidant effects. Currently, scientific interest in natural compounds extracted from the fungal species is increasing because these compounds are also known to have pharmacological/biological activity. Unfortunately, however, their mechanisms of action are often unknown, not well understood or have not been investigated in their entirety. Given the poly-pharmacological properties of bioactive fungal compounds, it was decided to carry out a multi-targeted approach to predict possible interactions occurring among bioactive natural fungal extracts and several macromolecular targets that are therapeutically interesting, i.e., proteins, enzymes and nucleic acids. A chemical database of compounds extracted from both edible and no-edible mushrooms was created. This database was virtually screened against 43 macromolecular targets downloaded from the Protein Data Bank website. The aim of this work is to provide a molecular description of the main interactions involving ligand/multi-target recognition in order to understand the polypharmacological profile of the most interesting fungal extracts and to suggest a design strategy of new multi-target agents.

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Keywords

polypharmacology, multi-target, Organic chemistry, virtual screening, mushrooms, metabolic diseases, Article, QD241-441, neurodegenerative diseases, database; mushrooms; polypharmacology; multi-target; virtual screening; metabolic diseases; anti-cancer; neurodegenerative diseases; anti-inflammatory, database, anti-cancer, anti-inflammatory

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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.
    Top 10%
    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.
    Top 10%
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selected citations
These citations are derived from selected sources.
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).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
26
Top 10%
Average
Top 10%
Green
gold