Zin Phyo Phyo Kyaw, Williams Gavin, Fourches Denis
Department of Chemistry, North Carolina State University, Raleigh, NC, USA.
Bioinformatics Research Center, North Carolina State University, Raleigh, NC, USA.
J Cheminform. 2020 Apr 10;12(1):23. doi: 10.1186/s13321-020-00427-6.
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.
我们报告了一种新的化学信息学枚举技术——SIME,即基于合成洞察的大环内酯枚举器,这是一种全新且经过改进的软件技术。SIME能够通过利用从大环内酯生物合成方面提取的组成和结构知识,枚举具有合成可行性的完全组装好的大环内酯。该软件考虑了诸如大环内酯结构中可插入化学成分的位置,以及可在这些位置合成并并入的感兴趣的结构基序和糖的类型等关键信息。此外,我们报告了新生成的SIME的大环内酯V1B(虚拟10亿)库的化学分布分析。这些化合物基于红霉素结构的核心、13种结构基序以及源自18种生物活性大环内酯的糖库构建而成。这种新的枚举技术可与化学信息学方法(如定量构效关系建模和分子对接)相结合,以助力药物发现,从而合理设计出具有理想药代动力学性质的下一代大环内酯类治疗药物。