Evidence map›Paper›PMID 37670359›Full record

ArticleBiology direct2023

Total network controllability analysis discovers explainable drugs for Covid-19 treatment.

Xinru Wei, Chunyu Pan, Xizhe Zhang, Weixiong Zhang

Open access · goldAbstract read
In one paragraph

Article in Biology direct, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.2field-weighted citation impact, top 18% of its field
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

5 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 4 institutions in 2 countries.

Xinru Wei *Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, 210029, China.
Chunyu Pan *School of Computer Science and Engineering, Northeastern University, Shenyang, Liaoning, 110167, China.
Xizhe ZhangEarly Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, 210029, China. zhangxizhe@njmu.edu.cn.
Weixiong ZhangDepartment of Health Technology and Informatics, Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China. weixiong.zhang@polyu.edu.hk.
Hong Kong Polytechnic University · HKNanjing Brain Hospital · CNNanjing Medical University · CNNortheastern University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe active pursuit of network medicine for drug repurposing, particularly for combating Covid-19, has stimulated interest in the concept of structural controllability in cellular networks. We sought to extend this theory, focusing on the defense rather than control of the cell against viral infections. Accordingly, we extended structural controllability to total structural controllability and introduced the concept of control hubs. Perturbing any control hub may render the cell uncontrollable by exogenous stimuli like viral infections, so control hubs are ideal drug targets.

resultsWe developed an efficient algorithm to identify all control hubs, applying it to a largest homogeneous network of human protein interactions, including interactions between human and SARS-CoV-2 proteins. Our method recognized 65 druggable control hubs with enriched antiviral functions. Utilizing these hubs, we categorized potential drugs into four groups: antiviral and anti-inflammatory agents, drugs acting on the central nervous system, dietary supplements, and compounds enhancing immunity. An exemplification of our approach's effectiveness, Fostamatinib, a drug initially developed for chronic immune thrombocytopenia, is now in clinical trials for treating Covid-19. Preclinical trial data demonstrated that Fostamatinib could reduce mortality rates, ICU stay length, and disease severity in Covid-19 patients.

conclusionsOur findings confirm the efficacy of our novel strategy that leverages control hubs as drug targets. This approach provides insights into the molecular mechanisms of potential therapeutics for Covid-19, making it a valuable tool for interpretable drug discovery. Our new approach is general and applicable to repurposing drugs for other diseases.

Indexed as

COVID-19AminopyridinesAntiviral AgentsCOVID-19 Drug TreatmentHumansMorpholinesPyrimidinesSARS-CoV-2AminopyridinesAntiviral AgentsfostamatinibMorpholinesPyrimidinesControl hubsExplainable drugs for Covid-19Total controllability

Identifiers

PMID37670359
PMCPMC10478273
OpenAlexW4386441892

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.