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Molecules 2017, 22(9), 1571; doi:10.3390/molecules22091571

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

Laboratorio di Chimica Farmaceutica, Dipartimento di Scienze della Salute, Università “Magna Græcia” di Catanzaro, Viale Europa, 88100 Catanzaro, Italy
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Received: 4 August 2017 / Revised: 13 September 2017 / Accepted: 17 September 2017 / Published: 19 September 2017
(This article belongs to the Special Issue Medicinal Chemistry in Europe)
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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. View Full-Text
Keywords: database; mushrooms; polypharmacology; multi-target; virtual screening; metabolic diseases; anti-cancer; neurodegenerative diseases; anti-inflammatory database; mushrooms; polypharmacology; multi-target; virtual screening; metabolic diseases; anti-cancer; neurodegenerative diseases; anti-inflammatory
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Maruca, A.; Moraca, F.; Rocca, R.; Molisani, F.; Alcaro, F.; Gidaro, M.C.; Alcaro, S.; Costa, G.; Ortuso, F. Chemoinformatic Database Building and in Silico Hit-Identification of Potential Multi-Targeting Bioactive Compounds Extracted from Mushroom Species. Molecules 2017, 22, 1571.

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