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Principal Investigator: MARC NICKLAUS
Organization: DIVISION OF BASIC SCIENCES - NCI
Fiscal Year: 2024
Award: $423,890
Funding agency: National Cancer Institute
The SAVI Project is based on: (a) a set of transforms with rich chemical context annotation including functional group reactivity data; (b) a set of building blocks from Enamine (c) the chemoinformatics toolkit CACTVS with custom development (Xemistry GmbH, Germany) The transforms are a set of more than 1,500 rules described in the CHMTRN/PATRAN language for encoding chemical transformations with chemical context and quality criteria added, based ultimately on the pioneering work of E. J. Corey. These rules, in contrast to simple SMIRKS transforms, allow/provide: - Computation of whether a reaction, depending on the overall structural features of the target, will work at all. - Scoring: If the reaction works, how robust it is, taking into account overall structural features. - Whether protection of interfering groups is required - and these can then already be integrated in the final starting materials queries to prioritize pre-protected starting materials. - Proposal of suitable context-dependent reaction conditions. - Textual warnings in specific circumstances, such as potential of multiple products, borderline conditions, etc. Additional novel transforms for chemistry heretofore not in the knowledgebase have been written, yielding a total of currently about 120 productive and drafted transforms. With 53 productive transforms, we finished calculating 1.75 billion SAVI products in early 2020. We have made them publicly available for download on the CADD Group's web server at https://doi.org/10.35115/37N9-5738, with an accompanying peer-reviewed paper published in Nature Scientific Data. SAVI syntheses have been extraordinarily successful at 97% success rates with the SAVI-predicted route. Out of about 170 synthesized molecules tested against cancer, HIV-1, and SARS-CoV-2 targets, tens have shown activity. Recent studies in the context of SAVI have investigated "non-druggable" targets such as the STAT3 N-terminal domain, as well as the correlation of protein binding pocket properties with hits' chemistries used in generation of ultra-large virtual libraries such as SAVI. A sister project of SAVI is the project "SMARTS and Logic In ChEmistry" (SLICE).
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