SAVI, in silico generation of billions of easily synthesizable compounds through expert-system type rules

Publication: Sci Data
Software: ADMET Predictor®

Abstract

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.

By Hitesh Patel, Wolf-Dietrich Ihlenfeldt, Philip N. Judson, Yurii S. Moroz, Yuri Pevzner, Megan L. Peach, Victorien Delannée, Nadya I. Tarasova & Marc C. Nicklaus