Informatics and Computational Methods in Natural Product Drug Discovery: A Review and Perspectives
Informatics and Computational Methods in Natural Product Drug Discovery: A Review and Perspectives
Joseph D. Romano1,2,3,4 and Nicholas P. Tatonetti1,2,3,4*
1Department of Biomedical Informatics, Columbia University, New York, NY, United States
2Department of Systems Biology, Columbia University, New York, NY, United States
3Department of Medicine, Columbia University, New York, NY, United States
4Data Science Institute, Columbia University, New York, NY, United States
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 bioinforma...
Source: Frontiers in Genetics - Category: Genetics & Stem Cells Source Type: research
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