Evidence map›Paper›PMID 29328784›Full record

ReviewAnnual review of biochemistry2018

DNA-Encoded Chemical Libraries: A Selection System Based on Endowing Organic Compounds with Amplifiable Information.

Dario Neri, Richard A Lerner

Abstract readReview
In one paragraph

Review in Annual review of biochemistry, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 138 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
138citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

138 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
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  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. PNA-Encoded Synthesis (PES) and DNA Display of Small-Molecule Libraries.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  12. A tailored CoA ligase-Nature catalysis · 2026
    Article
  13. CIMT 2025: Report on the 22Human vaccines & immunotherapeutics · 2025
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. Article

78 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Dario NeriDepartment of Chemistry and Applied Biosciences, Swiss Federal Institute of Technology (ETH Zürich), 8093 Zürich, Switzerland; email: neri@pharma.ethz.ch.
Richard A LernerDepartment of Chemistry, The Scripps Research Institute, La Jolla, California 92037, USA; email: rlerner@scripps.edu.

Funding

European Research Council 670603Swiss National Science Foundation 163479
6 · The paper itself

Abstract

The discovery of organic ligands that bind specifically to proteins is a central problem in chemistry, biology, and the biomedical sciences. The encoding of individual organic molecules with distinctive DNA tags, serving as amplifiable identification bar codes, allows the construction and screening of combinatorial libraries of unprecedented size, thus facilitating the discovery of ligands to many different protein targets. Fundamentally, one links powers of genetics and chemical synthesis. After the initial description of DNA-encoded chemical libraries in 1992, several experimental embodiments of the technology have been reduced to practice. This review provides a historical account of important milestones in the development of DNA-encoded chemical libraries, a survey of relevant ongoing research activities, and a glimpse into the future.

Indexed as

Gene LibrarySmall Molecule LibrariesAnimalsCombinatorial Chemistry TechniquesDrug DiscoveryHumansLigandsPeptide LibraryLigandsPeptide LibrarySmall Molecule Librariescombinatorial chemistryDNA-encoded chemical librariesdrug discovery

Identifiers

PMID29328784
PMCPMC6080696

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.