Bioactive Natural Products Prioritization Using Massive Multi-informational Molecular Networks
chEMBL
Isolation
Chemical space
DOI:
10.1021/acschembio.7b00413
Publication Date:
2017-08-22T14:41:12Z
AUTHORS (16)
ABSTRACT
Natural products represent an inexhaustible source of novel therapeutic agents. Their complex and constrained three-dimensional structures endow these molecules with exceptional biological properties, thereby giving them a major role in drug discovery programs. However, the search for new bioactive metabolites is hampered by chemical complexity matrices which they are found. The purification single constituents from such requires significant amount work that it should be ideally performed only on high potential value (i.e., novelty activity). Recent bioinformatics approaches based mass spectrometry metabolite profiling methods beginning to address task compound identification within mixtures. parallel developments, providing information bioactivity natural prior their isolation still lacking key interest target valuable only. In present investigation, we propose integrated analysis strategy prioritization. Our approach uses massive molecular networks embedding various informational layers (bioactivity taxonomical data) highlight potentially scaffolds diversity crude extracts collections. We exemplify this workflow targeting predicted active nonactive two botanical sources (Bocquillonia nervosa Neoguillauminia cleopatra) against targets (Wnt signaling pathway chikungunya virus replication). Eventually, detection processes daphnane diterpene orthoester four 12-deoxyphorbols inhibiting Wnt exhibiting potent antiviral activities CHIKV detailed. Combined efficient annotation tools, prioritization pipeline proves efficient. Implementation programs extract screening speed up rationalize products.
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