Evidence map›Paper›PMID 37707619›Full record

ReviewJournal of computer-aided molecular design2023

Exploring DrugCentral: from molecular structures to clinical effects.

Liliana Halip, Sorin Avram, Ramona Curpan, Ana Borota, Alina Bora, Cristian Bologa, Tudor I Oprea

Erratum issuedAbstract readReview
In one paragraph

Review in Journal of computer-aided molecular design, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. The evolving landscape of drug targets.Nature reviews. Drug discovery · 2026
    Review
  2. Article
  3. Review
  4. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Liliana Halip *Department of Computational Chemistry, "Coriolan Dragulescu" Institute of Chemistry, Timisoara, Romania.
Sorin Avram *Department of Computational Chemistry, "Coriolan Dragulescu" Institute of Chemistry, Timisoara, Romania.
Ramona CurpanDepartment of Computational Chemistry, "Coriolan Dragulescu" Institute of Chemistry, Timisoara, Romania.
Ana BorotaDepartment of Computational Chemistry, "Coriolan Dragulescu" Institute of Chemistry, Timisoara, Romania.
Alina BoraDepartment of Computational Chemistry, "Coriolan Dragulescu" Institute of Chemistry, Timisoara, Romania.
Cristian BologaTranslational Informatics Division, Department of Internal Medicine, University of New Mexico School of Medicine, Albuquerque, NM, USA.
Tudor I OpreaTranslational Informatics Division, Department of Internal Medicine, University of New Mexico School of Medicine, Albuquerque, NM, USA. toprea@salud.unm.edu.

Funding

Machine Learning Model Validation for AD/ADRDU24CA224370 · NCI · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI EDWARDS, JEREMY S · 2018 to 2023
$6.4M
NCI NIH HHS U24 CA224370NIH HHS U24 CA224370
6 · The paper itself

Abstract

DrugCentral, accessible at https://drugcentral.org , is an open-access online drug information repository. It covers over 4950 drugs, incorporating structural, physicochemical, and pharmacological details to support drug discovery, development, and repositioning. With around 20,000 bioactivity data points, manual curation enhances information from several major digital sources. Approximately 724 mechanism-of-action (MoA) targets offer updated drug target insights. The platform captures clinical data: over 14,300 on- and off-label uses, 27,000 contraindications, and around 340,000 adverse drug events from pharmacovigilance reports. DrugCentral encompasses information from molecular structures to marketed formulations, providing a comprehensive pharmaceutical reference. Users can easily navigate basic drug information and key features, making DrugCentral a versatile, unique resource. Furthermore, we present a use-case example where we utilize experimentally determined data from DrugCentral to support drug repurposing. A minimum activity threshold t should be considered against novel targets to repurpose a drug. Analyzing 1156 bioactivities for human MoA targets suggests a general threshold of 1 µM: t = 6 when expressed as - log[Activity(M)]). This applies to 87% of the drugs. Moreover, t can be refined empirically based on water solubility (S): t = 3 - logS, for logS < - 3. Alongside the drug repurposing classification scheme, which considers intellectual property rights, market exclusivity protections, and market accessibility, DrugCentral provides valuable data to prioritize candidates for drug repurposing programs efficiently.

Indexed as

Drug-Related Side Effects and Adverse ReactionsDrug Delivery SystemsDrug DiscoveryDrug RepositioningHumansMolecular StructureBioactivityDatabasesDrug repurposingDrugsDrug targetsPharmacology

Identifiers

PMID37707619
PMCPMC10692006

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.