Retrospective analysis of natural products provides insights for future discovery trends

Author:

Pye Cameron R.,Bertin Matthew J.,Lokey R. Scott,Gerwick William H.,Linington Roger G.ORCID

Abstract

Understanding of the capacity of the natural world to produce secondary metabolites is important to a broad range of fields, including drug discovery, ecology, biosynthesis, and chemical biology, among others. Both the absolute number and the rate of discovery of natural products have increased significantly in recent years. However, there is a perception and concern that the fundamental novelty of these discoveries is decreasing relative to previously known natural products. This study presents a quantitative examination of the field from the perspective of both number of compounds and compound novelty using a dataset of all published microbial and marine-derived natural products. This analysis aimed to explore a number of key questions, such as how the rate of discovery of new natural products has changed over the past decades, how the average natural product structural novelty has changed as a function of time, whether exploring novel taxonomic space affords an advantage in terms of novel compound discovery, and whether it is possible to estimate how close we are to having described all of the chemical space covered by natural products. Our analyses demonstrate that most natural products being published today bear structural similarity to previously published compounds, and that the range of scaffolds readily accessible from nature is limited. However, the analysis also shows that the field continues to discover appreciable numbers of natural products with no structural precedent. Together, these results suggest that the development of innovative discovery methods will continue to yield compounds with unique structural and biological properties.

Funder

NIH NCCIH/ ODS

HHS | NIH | National Institute of General Medical Sciences

Publisher

Proceedings of the National Academy of Sciences

Subject

Multidisciplinary

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