Evidence map›Paper›PMID 34978201›Full record

ArticleJournal of chemical information and modeling2022

PlayMolecule Glimpse: Understanding Protein-Ligand Property Predictions with Interpretable Neural Networks.

Alejandro Varela-Rial, Iain Maryanow, Maciej Majewski, Stefan Doerr, Nikolai Schapin, José Jiménez-Luna, Gianni De Fabritiis

Abstract read
In one paragraph

Article in Journal of chemical information and modeling, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Article
  2. Machine Learning to Predict CDK4 Inhibition.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  3. CDK7 as a Target for Docking Screens.Methods in molecular biology (Clifton, N.J.) · 2026
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  4. Molegro Virtual Docker for Docking Screens.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  5. Hands-On Docking with Molegro Virtual Docker.Methods in molecular biology (Clifton, N.J.) · 2026
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  6. Molegro Data Modeller for Machine Learning.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  7. Extremely Randomized Trees to Determine Binding Affinity.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  8. AlphaFold for Docking Screens.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  9. Neural Networks with Molegro Data Modeller.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  10. Targeting CDK9 with Molegro Virtual Docker.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  11. Differential Evolution for Docking Simulations.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  12. Molegro Data Modeller to Estimate CDK6 Inhibition.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  13. Neural Networks to Calculate CDK2 Inhibition.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  14. Tree-Based Methods to Predict Enzyme Inhibition.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  15. Article
  16. Review
  17. Article
  18. Review
  19. Article
  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

7 authors.

Alejandro Varela-RialComputational Science Laboratory, Universitat Pompeu Fabra, Barcelona Biomedical Research Park (PRBB), Carrer Dr. Aiguader 88, 08003 Barcelona, Spain.ORCID 0000-0002-6918-1765
Iain MaryanowAcellera Labs, Doctor Trueta 183, 08005 Barcelona, Spain.
Maciej MajewskiComputational Science Laboratory, Universitat Pompeu Fabra, Barcelona Biomedical Research Park (PRBB), Carrer Dr. Aiguader 88, 08003 Barcelona, Spain.ORCID 0000-0003-2605-8166
Stefan DoerrAcellera Labs, Doctor Trueta 183, 08005 Barcelona, Spain.
Nikolai SchapinComputational Science Laboratory, Universitat Pompeu Fabra, Barcelona Biomedical Research Park (PRBB), Carrer Dr. Aiguader 88, 08003 Barcelona, Spain.
José Jiménez-LunaComputational Science Laboratory, Universitat Pompeu Fabra, Barcelona Biomedical Research Park (PRBB), Carrer Dr. Aiguader 88, 08003 Barcelona, Spain.
Gianni De FabritiisComputational Science Laboratory, Universitat Pompeu Fabra, Barcelona Biomedical Research Park (PRBB), Carrer Dr. Aiguader 88, 08003 Barcelona, Spain.ORCID 0000-0003-3913-4877

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Deep learning has been successfully applied to structure-based protein-ligand affinity prediction, yet the black box nature of these models raises some questions. In a previous study, we presented K

Indexed as

Neural Networks, ComputerProteinsLigandsLigandsProteins

Identifiers

PMID34978201
PMCPMC8790755

What OpenQuestion holds

Textmetadata
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.