Cheminformatics in Natural Product‐based Drug Discovery

Abstract: This review seeks to provide a timely survey of the scope and limitations of cheminformatics methods in natural product‐based drug discovery. Following an overview of data resources of chemical, biological and structural information on natural products, we discuss, among other aspects, in silico methods for (i) data curation and natural products dereplication, (ii) analysis, visualization, navigation and comparison of the chemical space, (iii) quantification of natural product‐likeness, (iv) prediction of the bioactivities (virtual screening, target prediction), ADME and safety profiles (toxicity) of natural products, (v) natural products‐inspired de novo design and (vi) prediction of natural products prone to cause interference with biological assays. Among the many methods discussed are rule‐based, similarity‐based, shape‐based, pharmacophore‐based and network‐based approaches, docking and machine learning methods.

Standort
Deutsche Nationalbibliothek Frankfurt am Main
Umfang
Online-Ressource
Sprache
Englisch

Erschienen in
Cheminformatics in Natural Product‐based Drug Discovery ; volume:39 ; number:12 ; year:2020 ; extent:16
Molecular informatics ; 39, Heft 12 (2020) (gesamt 16)

Urheber

DOI
10.1002/minf.202000171
URN
urn:nbn:de:101:1-2022062612343017711599
Rechteinformation
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Letzte Aktualisierung
15.08.2025, 07:21 MESZ

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