Informatics and Computational Methods in Natural Product Drug Discovery: A Review and Perspectives
The discovery of new pharmaceutical drugs is one of the preeminent tasks—scientifically, economically, and socially—in biomedical research. Advances in informatics and computational biology have increased productivity at many stages of the drug discovery pipeline. Nevertheless, drug discovery has sl...
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doaj-40276900b8bd44fea372e8c1f9d231b42020-11-25T01:18:37ZengFrontiers Media S.A.Frontiers in Genetics1664-80212019-04-011010.3389/fgene.2019.00368442506Informatics and Computational Methods in Natural Product Drug Discovery: A Review and PerspectivesJoseph D. Romano0Joseph D. Romano1Joseph D. Romano2Joseph D. Romano3Nicholas P. Tatonetti4Nicholas P. Tatonetti5Nicholas P. Tatonetti6Nicholas P. Tatonetti7Department of Biomedical Informatics, Columbia University, New York, NY, United StatesDepartment of Systems Biology, Columbia University, New York, NY, United StatesDepartment of Medicine, Columbia University, New York, NY, United StatesData Science Institute, Columbia University, New York, NY, United StatesDepartment of Biomedical Informatics, Columbia University, New York, NY, United StatesDepartment of Systems Biology, Columbia University, New York, NY, United StatesDepartment of Medicine, Columbia University, New York, NY, United StatesData Science Institute, Columbia University, New York, NY, United StatesThe discovery of new pharmaceutical drugs is one of the preeminent tasks—scientifically, economically, and socially—in biomedical research. Advances in informatics and computational biology have increased productivity at many stages of the drug discovery pipeline. Nevertheless, drug discovery has slowed, largely due to the reliance on small molecules as the primary source of novel hypotheses. Natural products (such as plant metabolites, animal toxins, and immunological components) comprise a vast and diverse source of bioactive compounds, some of which are supported by thousands of years of traditional medicine, and are largely disjoint from the set of small molecules used commonly for discovery. However, natural products possess unique characteristics that distinguish them from traditional small molecule drug candidates, requiring new methods and approaches for assessing their therapeutic potential. In this review, we investigate a number of state-of-the-art techniques in bioinformatics, cheminformatics, and knowledge engineering for data-driven drug discovery from natural products. We focus on methods that aim to bridge the gap between traditional small-molecule drug candidates and different classes of natural products. We also explore the current informatics knowledge gaps and other barriers that need to be overcome to fully leverage these compounds for drug discovery. Finally, we conclude with a “road map” of research priorities that seeks to realize this goal.https://www.frontiersin.org/article/10.3389/fgene.2019.00368/fulldrug discoverymethodscheminformaticsbioinformaticsontologiestranslation |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Joseph D. Romano Joseph D. Romano Joseph D. Romano Joseph D. Romano Nicholas P. Tatonetti Nicholas P. Tatonetti Nicholas P. Tatonetti Nicholas P. Tatonetti |
spellingShingle |
Joseph D. Romano Joseph D. Romano Joseph D. Romano Joseph D. Romano Nicholas P. Tatonetti Nicholas P. Tatonetti Nicholas P. Tatonetti Nicholas P. Tatonetti Informatics and Computational Methods in Natural Product Drug Discovery: A Review and Perspectives Frontiers in Genetics drug discovery methods cheminformatics bioinformatics ontologies translation |
author_facet |
Joseph D. Romano Joseph D. Romano Joseph D. Romano Joseph D. Romano Nicholas P. Tatonetti Nicholas P. Tatonetti Nicholas P. Tatonetti Nicholas P. Tatonetti |
author_sort |
Joseph D. Romano |
title |
Informatics and Computational Methods in Natural Product Drug Discovery: A Review and Perspectives |
title_short |
Informatics and Computational Methods in Natural Product Drug Discovery: A Review and Perspectives |
title_full |
Informatics and Computational Methods in Natural Product Drug Discovery: A Review and Perspectives |
title_fullStr |
Informatics and Computational Methods in Natural Product Drug Discovery: A Review and Perspectives |
title_full_unstemmed |
Informatics and Computational Methods in Natural Product Drug Discovery: A Review and Perspectives |
title_sort |
informatics and computational methods in natural product drug discovery: a review and perspectives |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Genetics |
issn |
1664-8021 |
publishDate |
2019-04-01 |
description |
The discovery of new pharmaceutical drugs is one of the preeminent tasks—scientifically, economically, and socially—in biomedical research. Advances in informatics and computational biology have increased productivity at many stages of the drug discovery pipeline. Nevertheless, drug discovery has slowed, largely due to the reliance on small molecules as the primary source of novel hypotheses. Natural products (such as plant metabolites, animal toxins, and immunological components) comprise a vast and diverse source of bioactive compounds, some of which are supported by thousands of years of traditional medicine, and are largely disjoint from the set of small molecules used commonly for discovery. However, natural products possess unique characteristics that distinguish them from traditional small molecule drug candidates, requiring new methods and approaches for assessing their therapeutic potential. In this review, we investigate a number of state-of-the-art techniques in bioinformatics, cheminformatics, and knowledge engineering for data-driven drug discovery from natural products. We focus on methods that aim to bridge the gap between traditional small-molecule drug candidates and different classes of natural products. We also explore the current informatics knowledge gaps and other barriers that need to be overcome to fully leverage these compounds for drug discovery. Finally, we conclude with a “road map” of research priorities that seeks to realize this goal. |
topic |
drug discovery methods cheminformatics bioinformatics ontologies translation |
url |
https://www.frontiersin.org/article/10.3389/fgene.2019.00368/full |
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