SIME: Synthetic insight-based macrolide enumerator to generate the V1B library of 1 billion macrolides

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Abstract

We report on a new cheminformatics enumeration technology-SIME, synthetic insight-based macrolide enumerator-a new and improved software technology. SIME can enumerate fully assembled macrolides with synthetic feasibility by utilizing the constitutional and structural knowledge extracted from biosynthetic aspects of macrolides. Taken into account by the software are key information such as positions in macrolide structures at which chemical components can be inserted, and the types of structural motifs and sugars of interest that can be synthesized and incorporated at those positions. Additionally, we report on the chemical distribution analysis of the newly SIME-generated V1B (virtual 1 billion) library of macrolides. Those compounds were built based on the core of the Erythromycin structure, 13 structural motifs and a library of sugars derived from eighteen bioactive macrolides. This new enumeration technology can be coupled with cheminformatics approaches such as QSAR modeling and molecular docking to aid in drug discovery for rational designing of next generation macrolide therapeutics with desirable pharmacokinetic properties.[Figure not available: see fulltext.].

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Zin, P. P. K., Williams, G., & Fourches, D. (2020). SIME: Synthetic insight-based macrolide enumerator to generate the V1B library of 1 billion macrolides. Journal of Cheminformatics, 12(1). https://doi.org/10.1186/s13321-020-00427-6

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