Evidence map›Paper›PMID 36296697›Full record

ReviewMolecules (Basel, Switzerland)2022

In Silico Methods for Identification of Potential Active Sites of Therapeutic Targets.

Jianbo Liao, Qinyu Wang, Fengxu Wu, Zunnan Huang

Abstract readReview
In one paragraph

Review in Molecules (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing 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

34 citing papers in PubMed.

  1. Article
  2. Bioassay-Guided Fractionation ofMolecules (Basel, Switzerland) · 2026
    Article
  3. Article
  4. Article
  5. In Silico Druggability Assessment ofAntibiotics (Basel, Switzerland) · 2026
    Article
  6. Review
  7. Article
  8. Article
  9. AnCurrent drug targets · 2026
    Article
  10. Frontiers in bioinformatics · 2026
    Review
  11. Article
  12. The Human Omnibus of Targetable Pockets.Journal of cheminformatics · 2025
    Article
  13. Article
  14. Article
  15. Review
  16. Review
  17. Article
  18. Article
  19. Databases of ligand-binding pockets and protein-ligand interactions.Computational and structural biotechnology journal · 2024
    Review
  20. Article
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

4 authors.

Jianbo LiaoKey Laboratory of Big Data Mining and Precision Drug Design of Guangdong Medical University, Key Laboratory of Computer-Aided Drug Design of Dongguan City, Key Laboratory for Research and Development of Natural Drugs of Guangdong Province, School of Pharmacy, Guangdong Medical University, Dongguan 523808, China.
Qinyu WangKey Laboratory of Big Data Mining and Precision Drug Design of Guangdong Medical University, Key Laboratory of Computer-Aided Drug Design of Dongguan City, Key Laboratory for Research and Development of Natural Drugs of Guangdong Province, School of Pharmacy, Guangdong Medical University, Dongguan 523808, China.
Fengxu WuHubei Key Laboratory of Wudang Local Chinese Medicine Research, School of Pharmaceutical Sciences, Hubei University of Medicine, Shiyan 442000, China.
Zunnan HuangKey Laboratory of Big Data Mining and Precision Drug Design of Guangdong Medical University, Key Laboratory of Computer-Aided Drug Design of Dongguan City, Key Laboratory for Research and Development of Natural Drugs of Guangdong Province, School of Pharmacy, Guangdong Medical University, Dongguan 523808, China.ORCID 0000-0002-5821-703X

Funding

Cultivating Project for Young Scholars at Hubei University of Medicine 2020QDJZR017Higher Education Reform Project of Guangdong Province 2019268Key Discipline Construction Project of Guangdong Medical University 4SG21004G
6 · The paper itself

Abstract

Target identification is an important step in drug discovery, and computer-aided drug target identification methods are attracting more attention compared with traditional drug target identification methods, which are time-consuming and costly. Computer-aided drug target identification methods can greatly reduce the searching scope of experimental targets and associated costs by identifying the diseases-related targets and their binding sites and evaluating the druggability of the predicted active sites for clinical trials. In this review, we introduce the principles of computer-based active site identification methods, including the identification of binding sites and assessment of druggability. We provide some guidelines for selecting methods for the identification of binding sites and assessment of druggability. In addition, we list the databases and tools commonly used with these methods, present examples of individual and combined applications, and compare the methods and tools. Finally, we discuss the challenges and limitations of binding site identification and druggability assessment at the current stage and provide some recommendations and future perspectives.

Indexed as

Drug DiscoveryBinding SitesCatalytic Domainbinding sitedrug discoverydruggabilitytarget identificationtherapeutic target

Identifiers

PMID36296697
PMCPMC9609013

What OpenQuestion holds

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LicenceCC BY
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.