ReviewThe Yale journal of biology and medicine2011
Biology in a gray box: targeting the emergent properties of protein complexes: 2011 Yale Chemical Biology Symposium.
Review in The Yale journal of biology and medicine, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
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Who cites it
2 citing papers in PubMed.
- Advancing Molecular Simulations: Merging Physical Models, Experiments, and AI to Tackle Multiscale Complexity.The journal of physical chemistry letters · 2025Review
- Direct and Propagated Effects of Small Molecules on Protein-Protein Interaction Networks.Frontiers in bioengineering and biotechnology · 2015Review
Corrections and comments
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
At the 2011 Yale Chemical Biology Symposium, Jason Gestwicki presented a novel yet intuitive approach to drug screening. This method, which he termed "gray box" screening, targets protein complexes that have been reconstituted in vitro. Therefore, the gray box screen can achieve greater phenotypic complexity than biochemical assays but avoids the need for target identification that follows cell-based assays. Dr. Gestwicki's research group was able to use the gray box screen to identify myricetin as an inhibitor of the DnaK-DnaJ chaperone complex. This review will discuss Dr. Gestwicki's approach to identifying DnaK-DnaJ inhibitors as well as where the gray box screen fits among traditional techniques in drug discovery.
Indexed as
Identifiers
22180688PMC3238318What 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.