Evidence map›Paper›PMID 38886570›Full record

ReviewOncogene2024

Impact of structural biology and the protein data bank on us fda new drug approvals of low molecular weight antineoplastic agents 2019-2023.

Stephen K Burley, Amy Wu-Wu, Shuchismita Dutta, Shridar Ganesan, Steven X F Zheng

Abstract readReview
In one paragraph

Review in Oncogene, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. 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. Article
  2. How many crystal structures do you need to trust your docking results?bioRxiv : the preprint server for biology · 2025
    Article
  3. Article
  4. 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

5 authors.

Stephen K BurleyResearch Collaboratory for Structural Bioinformatics Protein Data Bank, Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ, 08854, USA. Stephen.Burley@RCSB.org.ORCID 0000-0002-2487-9713
Amy Wu-WuResearch Collaboratory for Structural Bioinformatics Protein Data Bank, Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ, 08854, USA.
Shuchismita DuttaResearch Collaboratory for Structural Bioinformatics Protein Data Bank, Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ, 08854, USA.ORCID 0000-0002-2109-5411
Shridar GanesanRutgers Cancer Institute of New Jersey, Robert Wood Johnson Medical School, New Brunswick, NJ, 08903, USA.
Steven X F ZhengRutgers Cancer Institute of New Jersey, Robert Wood Johnson Medical School, New Brunswick, NJ, 08903, USA.ORCID 0000-0003-0813-3599

Funding

PDB MANAGEMENT BY THE RESEARCH COLLABORATORY FOR STRUCTURAL BIOINFORMATICSR01GM133198 · NIGMS · RUTGERS, THE STATE UNIV OF N.J. · PI BURLEY, STEPHEN K · 2019 to 2023
$19.3M
National Science Foundation (NSF) DBI-1832184NIGMS NIH HHS R01 GM133198U.S. Department of Energy (DOE) DE-SC0019749U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI) R01GM133198U.S. Department of Health & Human Services | NIH | National Institute of Allergy and Infectious Diseases (NIAID) R01GM133198U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (NIGMS) R01GM133198
6 · The paper itself

Abstract

Open access to three-dimensional atomic-level biostructure information from the Protein Data Bank (PDB) facilitated discovery/development of 100% of the 34 new low molecular weight, protein-targeted, antineoplastic agents approved by the US FDA 2019-2023. Analyses of PDB holdings, the scientific literature, and related documents for each drug-target combination revealed that the impact of structural biologists and public-domain 3D biostructure data was broad and substantial, ranging from understanding target biology (100% of all drug targets), to identifying a given target as likely druggable (100% of all targets), to structure-guided drug discovery (>80% of all new small-molecule drugs, made up of 50% confirmed and >30% probable cases). In addition to aggregate impact assessments, illustrative case studies are presented for six first-in-class small-molecule anti-cancer drugs, including a selective inhibitor of nuclear export targeting Exportin 1 (selinexor, Xpovio), an ATP-competitive CSF-1R receptor tyrosine kinase inhibitor (pexidartinib,Turalia), a non-ATP-competitive inhibitor of the BCR-Abl fusion protein targeting the myristoyl binding pocket within the kinase catalytic domain of Abl (asciminib, Scemblix), a covalently-acting G12C KRAS inhibitor (sotorasib, Lumakras or Lumykras), an EZH2 methyltransferase inhibitor (tazemostat, Tazverik), and an agent targeting the basic-Helix-Loop-Helix transcription factor HIF-2α (belzutifan, Welireg).

Indexed as

Antineoplastic AgentsDatabases, ProteinDrug ApprovalUnited States Food and Drug AdministrationDrug DiscoveryHumansMolecular WeightUnited StatesAntineoplastic Agents

Identifiers

PMID38886570
PMCPMC11245395

What OpenQuestion holds

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LicenceCC BY
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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.