Evidence map›Paper›PMID 25019558›Full record

ReviewMolecules (Basel, Switzerland)2014

Challenges, applications, and recent advances of protein-ligand docking in structure-based drug design.

Sam Z Grinter, Xiaoqin Zou

Abstract readReview
In one paragraph

Review in Molecules (Basel, Switzerland), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 87 papers.

0numbers the graph read from it
0cells of the map it votes in
87citing 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

87 citing papers in PubMed.

  1. Review
  2. Review
  3. Can Cavity Prediction Algorithms Help in Docking Experiments?Journal of computational chemistry · 2026
    Article
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Review
  10. Review
  11. Molegro Virtual Docker for Docking Screens.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
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  18. Article
  19. Improved Prediction of Ligand-Protein Binding Affinities by Meta-modeling.Journal of chemical information and modeling · 2024
    Article
  20. Article

27 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.

Sam Z GrinterInformatics Institute, University of Missouri, Columbia, MO 65211, USA. szg4y4@mail.missouri.edu.
Xiaoqin ZouInformatics Institute, University of Missouri, Columbia, MO 65211, USA. zoux@missouri.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The docking methods used in structure-based virtual database screening offer the ability to quickly and cheaply estimate the affinity and binding mode of a ligand for the protein receptor of interest, such as a drug target. These methods can be used to enrich a database of compounds, so that more compounds that are subsequently experimentally tested are found to be pharmaceutically interesting. In addition, like all virtual screening methods used for drug design, structure-based virtual screening can focus on curated libraries of synthesizable compounds, helping to reduce the expense of subsequent experimental verification. In this review, we introduce the protein-ligand docking methods used for structure-based drug design and other biological applications. We discuss the fundamental challenges facing these methods and some of the current methodological topics of interest. We also discuss the main approaches for applying protein-ligand docking methods. We end with a discussion of the challenging aspects of evaluating or benchmarking the accuracy of docking methods for their improvement, and discuss future directions.

Indexed as

Databases, ProteinDrug DesignHumansMolecular Docking SimulationProteinsStructure-Activity RelationshipProteins

Identifiers

PMID25019558
PMCPMC6270832

What OpenQuestion holds

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Registered trials

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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.