Evidence map›Paper›PMID 29370102›Full record

ReviewMolecules (Basel, Switzerland)2018

NMR-Fragment Based Virtual Screening: A Brief Overview.

Meenakshi Singh, Benjamin Tam, Barak Akabayov

Abstract readReview
In one paragraph

Review in Molecules (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
–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

22 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Perspectives on Applications ofMolecules (Basel, Switzerland) · 2024
    Review
  5. Advances in Cathepsin S Inhibition: Challenges and Breakthroughs in Drug Development.Pathophysiology : the official journal of the International Society for Pathophysiology · 2024
    Review
  6. Article
  7. Review
  8. Review
  9. Review
  10. Article
  11. Review
  12. Using Structure-guided Fragment-Based Drug Discovery to TargetFrontiers in molecular biosciences · 2022
    Review
  13. Article
  14. Review
  15. Review
  16. Review
  17. Review
  18. Article
  19. Review
  20. Review
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

3 authors.

Meenakshi SinghDepartment of Chemistry, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel. meenaksh@post.bgu.ac.il.
Benjamin TamDepartment of Chemistry, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel. tamb@post.bgu.ac.il.
Barak AkabayovDepartment of Chemistry, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel. akabayov@bgu.ac.il.ORCID 0000-0002-3882-2742

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fragment-based drug discovery (FBDD) using NMR has become a central approach over the last twenty years for development of small molecule inhibitors against biological macromolecules, to control a variety of cellular processes. Yet, several considerations should be taken into account for obtaining a therapeutically relevant agent. In this review, we aim to list the considerations that make NMR fragment screening a successful process for yielding potent inhibitors. Factors that may govern the competence of NMR in fragment based drug discovery are discussed, as well as later steps that involve optimization of hits obtained by NMR-FBDD.

Indexed as

Computer SimulationDrug DiscoveryMagnetic Resonance SpectroscopyAnimalsDrug Evaluation, PreclinicalHigh-Throughput Screening AssaysHumansLigandsNuclear Magnetic Resonance, BiomolecularQuantitative Structure-Activity RelationshipSmall Molecule LibrariesLigandsSmall Molecule Librariesfragment-based drug discoveryfragment based virtual screeningnuclear magnetic resonance

Identifiers

PMID29370102
PMCPMC6017141

What OpenQuestion holds

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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.