Evidence map›Paper›PMID 36430850›Full record

ArticleInternational journal of molecular sciences2022

Antiproliferative Activity Predictor: A New Reliable In Silico Tool for Drug Response Prediction against NCI60 Panel.

Annamaria Martorana, Gabriele La Monica, Alessia Bono, Salvatore Mannino, Silvestre Buscemi, Antonio Palumbo Piccionello, Carla Gentile, Antonino Lauria, Daniele Peri

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
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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

9 authors.

Annamaria MartoranaDipartimento di Scienze e Tecnologie Biologiche Chimiche e Farmaceutiche "STEBICEF", Università Degli Studi di Palermo, Viale Delle Scienze Ed. 17, I-90128 Palermo, Italy.ORCID 0000-0002-9560-1882
Gabriele La MonicaDipartimento di Scienze e Tecnologie Biologiche Chimiche e Farmaceutiche "STEBICEF", Università Degli Studi di Palermo, Viale Delle Scienze Ed. 17, I-90128 Palermo, Italy.ORCID 0000-0001-6510-1943
Alessia BonoDipartimento di Scienze e Tecnologie Biologiche Chimiche e Farmaceutiche "STEBICEF", Università Degli Studi di Palermo, Viale Delle Scienze Ed. 17, I-90128 Palermo, Italy.ORCID 0000-0002-9283-4920
Salvatore ManninoDipartimento di Scienze e Tecnologie Biologiche Chimiche e Farmaceutiche "STEBICEF", Università Degli Studi di Palermo, Viale Delle Scienze Ed. 17, I-90128 Palermo, Italy.
Silvestre BuscemiDipartimento di Scienze e Tecnologie Biologiche Chimiche e Farmaceutiche "STEBICEF", Università Degli Studi di Palermo, Viale Delle Scienze Ed. 17, I-90128 Palermo, Italy.
Antonio Palumbo PiccionelloDipartimento di Scienze e Tecnologie Biologiche Chimiche e Farmaceutiche "STEBICEF", Università Degli Studi di Palermo, Viale Delle Scienze Ed. 17, I-90128 Palermo, Italy.ORCID 0000-0003-4402-5798
Carla GentileDipartimento di Scienze e Tecnologie Biologiche Chimiche e Farmaceutiche "STEBICEF", Università Degli Studi di Palermo, Viale Delle Scienze Ed. 17, I-90128 Palermo, Italy.ORCID 0000-0001-5861-3342
Antonino LauriaDipartimento di Scienze e Tecnologie Biologiche Chimiche e Farmaceutiche "STEBICEF", Università Degli Studi di Palermo, Viale Delle Scienze Ed. 17, I-90128 Palermo, Italy.ORCID 0000-0002-5116-6815
Daniele PeriDipartimento di Ingegneria Dell'innovazione Industriale e Digitale, Università Degli Studi di Palermo, Viale Delle Scienze Ed. 6, I-90128 Palermo, Italy.ORCID 0000-0002-8763-7199

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In vitro antiproliferative assays still represent one of the most important tools in the anticancer drug discovery field, especially to gain insights into the mechanisms of action of anticancer small molecules. The NCI-DTP (National Cancer Institute Developmental Therapeutics Program) undoubtedly represents the most famous project aimed at rapidly testing thousands of compounds against multiple tumor cell lines (NCI60). The large amount of biological data stored in the National Cancer Institute (NCI) database and many other databases has led researchers in the fields of computational biology and medicinal chemistry to develop tools to predict the anticancer properties of new agents in advance. In this work, based on the available antiproliferative data collected by the NCI and the manipulation of molecular descriptors, we propose the new in silico Antiproliferative Activity Predictor (AAP) tool to calculate the GI

Indexed as

Antineoplastic AgentsCurcuminCell Line, TumorDatabases, FactualAntineoplastic AgentsCurcuminantiproliferative activity predictorDRUDITGI50ligand-based toolsmolecular descriptorsNCI60

Identifiers

PMID36430850
PMCPMC9694168

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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.