Evidence map›Paper›PMID 41968358›Full record

ArticleJournal of cheminformatics2026

Multiscale analysis and optimal glioma therapeutic candidate discovery using the CANDO platform.

Sumei Xu, Yakun Hu, William Mangione, Melissa Van Norden, Katherine Elefteriou, Zackary Falls, Ram Samudrala

Abstract read
In one paragraph

Article in Journal of cheminformatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Sumei XuPhase I Clinical Trial Center, Xiangya Hospital, Central South University, 87 Xiangya Rd, Changsha, 410008, Hunan, China.
Yakun HuDepartment of Biomedical Informatics, University at Buffalo, 77 Goodell Street, Buffalo, NY, 14203, USA. yaquinnhu@gmail.com.
William MangioneDepartment of Biomedical Informatics, University at Buffalo, 77 Goodell Street, Buffalo, NY, 14203, USA.
Melissa Van NordenDepartment of Biomedical Informatics, University at Buffalo, 77 Goodell Street, Buffalo, NY, 14203, USA.
Katherine ElefteriouDepartment of Biomedical Informatics, University at Buffalo, 77 Goodell Street, Buffalo, NY, 14203, USA.
Zackary FallsDepartment of Biomedical Informatics, University at Buffalo, 77 Goodell Street, Buffalo, NY, 14203, USA. zmfalls@buffalo.edu.
Ram SamudralaDepartment of Biomedical Informatics, University at Buffalo, 77 Goodell Street, Buffalo, NY, 14203, USA. ram@compbio.org.

Funding

University of Buffalo Clinical and Translational Science Institute - Supplement SchulyerUL1TR001412 · NCATS · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI MURPHY, TIMOTHY F · 2015 to 2024
$33.8M
National Library of Medicine Conference 2022T15LM012495 · NLM · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI PETER L. ELKIN · 2017 to 2026
$4.3M
NOVEL PARADIGMS FOR DRUG DISCOVERY: COMPUTATIONAL MULTITARGET SCREENINGDP1OD006779 · OD · UNIVERSITY OF WASHINGTON · PI SAMUDRALA, RAM · 2010 to 2011
$1.7M
A translational bioinformatics approach to elucidate and mitigate polypharmacy induced adverse drug reactionsK01DA056690 · NIDA · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI Zackary Michael Falls · 2022 to 2026
$1.0M
Buffalo Research Innovation in Genomic and Healthcare Technology (BRIGHT) Short-Term Training and EducationR25LM014213 · NLM · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI PETER L. ELKIN, RAM SAMUDRALA · 2022 to 2026
$668k
National Institute of Standards of Technology (NIST) Award 60NANB22D168National Institutes of Health (NIH) Director's Pioneer Award DP1OD006779NCATS NIH HHS UL1 TR001412NIDA Mentored Research Scientist Development Award K01DA056690NIDA NIH HHS K01 DA056690NIH Clinical and Translational Sciences (NCATS) Award UL1TR001412NIH HHS DP1 OD006779NIH National Library of Medicine (NLM) T15 Award T15LM012495NIH NLM R25 Award R25LM014213NLM NIH HHS R25 LM014213NLM NIH HHS T15 LM012495
6 · The paper itself

Abstract

Glioma is a highly malignant brain tumor with limited treatment options. We employed the Computational Analysis of Novel Drug Opportunities (CANDO) platform for multiscale therapeutic discovery to predict new glioma therapies. We began by computing interaction scores between extensive libraries of drugs/compounds and proteins to generate "interaction signatures" that model compound behavior on a proteomic scale. Compounds with signatures most similar to those of drugs approved for a given indication were considered potential treatments. These compounds were further ranked by degree of consensus in corresponding similarity lists. We benchmarked performance by measuring the recovery of approved drugs in these similarity and consensus lists at various cutoffs, using multiple metrics and comparing results to random controls and performance across all indications. Compounds ranked highly by consensus but not previously associated with the indication of interest were considered new predictions. Our benchmarking results showed that CANDO improved accuracy in identifying glioma-associated drugs across all cutoffs compared to random controls. Our predictions, supported by literature-based analysis, identified 24 potential glioma treatments, including approved drugs like vitamin D, taxanes, vinca alkaloids, topoisomerase inhibitors, and folic acid, as well as investigational compounds such as ginsenosides, chrysin, resiniferatoxin, and cryptotanshinone. Further functional annotation-based analysis of the top targets with the strongest interactions to these predictions identified Vitamin D3 receptor, thyroid hormone receptor, acetylcholinesterase, cyclin-dependent kinase 2, tubulin alpha chain, dihydrofolate reductase, and thymidylate synthase. These findings indicate that CANDO's multitarget, multiscale framework is effective in identifying glioma drug candidates thereby informing new strategies for improving treatment.Scientific contribution (1) We present a robust, multiscale drug discovery framework that accurately recovers known glioma therapies and uncovers 24 novel candidates with strong literature and mechanistic support. (2) By modeling compound behavior across the proteome, our method pinpoints key targets-including VDR, CDK2, and DHFR-implicated in glioma biology. (3) This work positions CANDO as a powerful tool for rational repurposing and discovery of urgently needed treatments for aggressive brain tumors.

Indexed as

Computational drug repurposingDeep learningGliomaMultiscale drug discoverySystems biologyTranslational bioinformatics

Identifiers

PMID41968358
PMCPMC13185303

What OpenQuestion holds

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LicenceCC BY
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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.