Evidence map›Paper›PMID 38926437›Full record

ArticleScientific reports2024

Integration of molecular docking and molecular dynamics simulations with subtractive proteomics approach to identify the novel drug targets and their inhibitors in Streptococcus gallolyticus.

Peng Chao, Xueqin Zhang, Lei Zhang, Aiping Yang, Yong Wang, Xiaoyang Chen

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Frontiers in bioinformatics · 2026
    Article
  6. Review
  7. Frontiers in medicine · 2026
    Article
  8. 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

6 authors.

Peng Chao *Department of Cardiology, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, China.
Xueqin Zhang *Department of Nephrology, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, China.
Lei ZhangDepartment of Cardiology, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, China.
Aiping YangDepartment of Traditional Chinese Medicine, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, China.
Yong WangDepartment of Cardiology, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, China.
Xiaoyang ChenDepartment of Cardiology, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, China. chenxiaoyang20707@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Streptococcus gallolyticus (Sg) is a non-motile, gram-positive bacterium that causes infective endocarditis (inflammation of the heart lining). Because Sg has gained resistance to existing antibiotics and there is currently no drug available, developing effective anti-Sg drugs is critical. This study combined core proteomics with a subtractive proteomics technique to identify potential therapeutic targets for Sg. Several bioinformatics approaches were used to eliminate non-essential and human-specific homologous sequences from the bacterial proteome. Then, virulence, druggability, subcellular localization, and functional analyses were carried out to specify the participation of significant bacterial proteins in various cellular processes. The pathogen's genome contained three druggable proteins, glucosamine-1phosphate N-acetyltransferase (GlmU), RNA polymerase sigma factor (RpoD), and pantetheine-phosphate adenylyltransferase (PPAT) which could serve as effective targets for developing novel drugs. 3D structures of target protein were modeled through Swiss Model. A natural product library containing 10,000 molecules from the LOTUS database was docked against therapeutic target proteins. Following an evaluation of the docking results using the glide gscore, the top 10 compounds docked against each protein receptor were chosen. LTS001632, LTS0243441, and LTS0236112 were the compounds that exhibited the highest binding affinities against GlmU, PPAT, and RpoD, respectively, among the compounds that were chosen. To augment the docking data, molecular dynamics simulations and MM-GBSA binding free energy were also utilized. More in-vitro research is necessary to transform these possible inhibitors into therapeutic drugs, though computer validations were employed in this study. This combination of computational techniques paves the way for targeted antibiotic development, which addresses the critical need for new therapeutic strategies against S. gallolyticus infections.

Indexed as

Anti-Bacterial AgentsBacterial ProteinsMolecular Docking SimulationMolecular Dynamics SimulationProteomicsStreptococcus gallolyticusHumansAnti-Bacterial AgentsBacterial ProteinsCore proteomicsEndocarditisGlucosamine-1phosphate N-acetyltransferase (GlmU)Pantetheine-phosphate adenylyltransferase (PPAT)RNA polymerase sigma factor (RpoD)Streptococcus gallolyticus

Identifiers

PMID38926437
PMCPMC11208513

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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.