Annie Hatmaker, Ph.D. (@annemakerofhats.bsky.social)

Machine-Readable Structural Information Is Essential for Natural Products Research Structural drawings of secondary metabolites encapsulate a wealth of information, but their static nature hinders their sharing and reuse. At a time when research increasingly relies on, and benefits from, access to comprehensive natural products “big data”, this hindrance is contrary to the norms of science. This Perspective discusses current challenges in sharing and accessing structure data and offers a simple solution, namely, publishing machine-readable text descriptors for new secondary metabolites. Requiring such descriptors will be straightforward to implement for both authors and publishers and will help derive even greater value from the efforts expended to understand the chemistry of Nature. https://pubs.acs.org/doi/10.1021/acs.jnatprod.5c00836?utm_source=SendGrid_ealert&utm_medium=ealert&utm_campaign=ASAP_jnprdf_v0_i0