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Article

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

AMA Style

Maruca A, Moraca F, Rocca R, Molisani F, Alcaro F, Gidaro MC, 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(9):1571. https://doi.org/10.3390/molecules22091571

Chicago/Turabian Style

Maruca, Annalisa, Federica Moraca, Roberta Rocca, Fulvia Molisani, Francesca Alcaro, Maria Concetta Gidaro, Stefano Alcaro, Giosuè Costa, and Francesco Ortuso. 2017. "Chemoinformatic Database Building and in Silico Hit-Identification of Potential Multi-Targeting Bioactive Compounds Extracted from Mushroom Species" Molecules 22, no. 9: 1571. https://doi.org/10.3390/molecules22091571

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