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SIME: synthetic insight-based macrolide enumerator to generate the V1B library of 1 billion macrolides
Journal of Cheminformatics ( IF 8.6 ) Pub Date : 2020-04-10 , DOI: 10.1186/s13321-020-00427-6
Phyo Phyo Kyaw Zin , Gavin Williams , Denis Fourches

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.

中文翻译:

SIME:基于合成洞察力的大环内酯枚举器,生成10亿个大环内酯的V1B库

我们报告了一种新的化学信息学枚举技术-SIME,基于合成洞察的大环内酯枚举器-一种经过改进的新软件技术。SIME可以利用从大环内酯的生物合成方面提取的组成和结构知识,列举具有合成可行性的完全组装的大环内酯。该软件考虑了关键信息,例如大环内酯结构中可以插入化学成分的位置,以及可以在这些位置上合成和掺入的结构基序和目标糖的类型。此外,我们报告了SIME新生成的大环内酯类V1B(虚拟10亿)文库的化学分布分析。这些化合物是基于红霉素结构的核心构建的,从18种生物活性大环内酯类化合物中提取13个结构基序和糖库。这项新的枚举技术可以与化学信息学方法(例如QSAR建模和分子对接)结合使用,以帮助药物发现,从而合理设计具有所需药代动力学特性的下一代大环内酯类药物。
更新日期:2020-04-10
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