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  • 标题:SAVI, in silico generation of billions of easily synthesizable compounds through expert-system type rules
  • 本地全文:下载
  • 作者:Hitesh Patel ; Wolf-Dietrich Ihlenfeldt ; Philip N. Judson
  • 期刊名称:Scientific Data
  • 电子版ISSN:2052-4463
  • 出版年度:2020
  • 卷号:7
  • 期号:1
  • 页码:1-14
  • DOI:10.1038/s41597-020-00727-4
  • 语种:English
  • 出版社:Nature Publishing Group
  • 摘要:We have made available a database of over 1 billion compounds predicted to be easily synthesizable, called Synthetically Accessible Virtual Inventory (SAVI). They have been created by a set of transforms based on an adaptation and extension of the CHMTRN/PATRAN programming languages describing chemical synthesis expert knowledge, which originally stem from the LHASA project. The chemoinformatics toolkit CACTVS was used to apply a total of 53 transforms to about 150,000 readily available building blocks (enamine.net). Only single-step, two-reactant syntheses were calculated for this database even though the technology can execute multi-step reactions. The possibility to incorporate scoring systems in CHMTRN allowed us to subdivide the database of 1.75 billion compounds in sets according to their predicted synthesizability, with the most-synthesizable class comprising 1.09 billion synthetic products. Properties calculated for all SAVI products show that the database should be well-suited for drug discovery. It is being made publicly available for free download from https://doi.org/10.35115/37n9-5738.
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