Evidence map›Paper›PMID 36675202›Full record

ArticleInternational journal of molecular sciences2023

CLC-Pred 2.0: A Freely Available Web Application for In Silico Prediction of Human Cell Line Cytotoxicity and Molecular Mechanisms of Action for Druglike Compounds.

Alexey A Lagunin, Anastasia V Rudik, Pavel V Pogodin, Polina I Savosina, Olga A Tarasova, Alexander V Dmitriev, Sergey M Ivanov, Nadezhda Y Biziukova, Dmitry S Druzhilovskiy, Dmitry A Filimonov and 1 more

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing 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

33 citing papers in PubMed.

  1. Article
  2. AI/ML-based computational models for toxicity prediction.Environmental science and pollution research international · 2026
    Review
  3. Article
  4. Article
  5. Article
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  7. Article
  8. Article
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  10. QSAR Modeling for Predicting ICInternational journal of molecular sciences · 2025
    Article
  11. Article
  12. Article
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  15. Article
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  17. Article
  18. Review
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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

11 authors.

Alexey A LaguninDepartment of Bioinformatics, Institute of Biomedical Chemistry, 119435 Moscow, Russia.ORCID 0000-0003-1757-8004
Anastasia V RudikDepartment of Bioinformatics, Institute of Biomedical Chemistry, 119435 Moscow, Russia.
Pavel V PogodinDepartment of Bioinformatics, Institute of Biomedical Chemistry, 119435 Moscow, Russia.ORCID 0000-0003-1843-7668
Polina I SavosinaDepartment of Bioinformatics, Institute of Biomedical Chemistry, 119435 Moscow, Russia.
Olga A TarasovaDepartment of Bioinformatics, Institute of Biomedical Chemistry, 119435 Moscow, Russia.ORCID 0000-0002-3723-7832
Alexander V DmitrievDepartment of Bioinformatics, Institute of Biomedical Chemistry, 119435 Moscow, Russia.ORCID 0000-0002-2431-3429
Sergey M IvanovDepartment of Bioinformatics, Institute of Biomedical Chemistry, 119435 Moscow, Russia.ORCID 0000-0002-3177-6237
Nadezhda Y BiziukovaDepartment of Bioinformatics, Institute of Biomedical Chemistry, 119435 Moscow, Russia.
Dmitry S DruzhilovskiyDepartment of Bioinformatics, Institute of Biomedical Chemistry, 119435 Moscow, Russia.
Dmitry A FilimonovDepartment of Bioinformatics, Institute of Biomedical Chemistry, 119435 Moscow, Russia.
Vladimir V PoroikovDepartment of Bioinformatics, Institute of Biomedical Chemistry, 119435 Moscow, Russia.ORCID 0000-0001-7937-2621

Funding

Russian Science Foundation 19-15-00396
6 · The paper itself

Abstract

In vitro cell-line cytotoxicity is widely used in the experimental studies of potential antineoplastic agents and evaluation of safety in drug discovery. In silico estimation of cytotoxicity against hundreds of tumor cell lines and dozens of normal cell lines considerably reduces the time and costs of drug development and the assessment of new pharmaceutical agent perspectives. In 2018, we developed the first freely available web application (CLC-Pred) for the qualitative prediction of cytotoxicity against 278 tumor and 27 normal cell lines based on structural formulas of 59,882 compounds. Here, we present a new version of this web application: CLC-Pred 2.0. It also employs the PASS (Prediction of Activity Spectra for Substance) approach based on substructural atom centric MNA descriptors and a Bayesian algorithm. CLC-Pred 2.0 provides three types of qualitative prediction: (1) cytotoxicity against 391 tumor and 47 normal human cell lines based on ChEMBL and PubChem data (128,545 structures) with a mean accuracy of prediction (AUC), calculated by the leave-one-out (LOO CV) and the 20-fold cross-validation (20F CV) procedures, of 0.925 and 0.923, respectively; (2) cytotoxicity against an NCI60 tumor cell-line panel based on the Developmental Therapeutics Program's NCI60 data (22,726 structures) with different thresholds of IG

Indexed as

Antineoplastic AgentsSoftwareBayes TheoremCell Line, TumorHumansPrednisoneAntineoplastic AgentsPrednisonecell linesCLC-Predcytotoxicityin silico predictionmechanism of actionPASSSAR

Identifiers

PMID36675202
PMCPMC9861947

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.