ArticleACS central science2026
Chemical Distance-Based Acceleration of Large Library Docking with ChemSTEP.
Article in ACS central science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
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0 citing papers in PubMed.
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Authors and funding
7 authors.
Funding
Abstract
While make-on-demand libraries now span trillions of molecules, full library docking struggles beyond a few billion, motivating prioritization that recovers top-scoring compounds while evaluating only a fraction of a library. Here we introduce a similarity-based prioritization approach, ChemSTEP, and define the effective size of a library treated by any prioritization algorithm, N
Identifiers
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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.