ArticleScientific data2025
SAVI Space-combinatorial encoding of the billion-size synthetically accessible virtual inventory.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Strategies for Identifying Molecules of Interest in Large Chemical Spaces.Journal of chemical information and modeling · 2026Article
- The (r)evolution of chemical space and molecular modeling: a time-resolved perspective.Journal of computer-aided molecular design · 2026Review
- Guiding Similarity Search in Chemical Fragment Spaces with Weighted Fingerprints.Journal of chemical information and modeling · 2026Article
- SLICE (SMARTS and Logic In ChEmistry): fast generation of molecules using advanced chemical synthesis logic and modern coding style.Journal of cheminformatics · 2025Article
Corrections and comments
- Erratum issued
Authors and funding
6 authors.
Funding
Abstract
The Synthetically Accessible Virtual Inventory (SAVI) comprises a huge molecule collection. LHASA transform rules, originally intended for retro-synthetic analysis, were applied to Enamine Building Blocks in a forward synthetic manner. Adding new transforms, expressly developed for SAVI, resulted in SAVI-Lib-2020, a collection of more than a billion synthetically accessible compounds. Handling a billion molecules explicitly is computationally quite demanding for drug discovery applications. SAVI-Space-2024 was created to address this shortcoming. In this paper, we describe the design and implementation of SAVI-Space-2024. We emphasize its reaction-driven combinatorial data structure that encodes transformation rules as reaction SMARTS and applies them in a combinatorial manner. Based on Enamine Building Blocks, this approach yields 7.5 billion molecules while requiring only a fraction of the memory (1.4 GB compared to 210 GB). Furthermore, the improved search capabilities - including fast similarity and substructure searches and docking applications on standard hardware - represent a significant advance over the enumerated SAVI library.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.