Evidence map›Paper›PMID 29081700›Full record

ArticleCurrent genomics2017

A Systematic

Deepthi Nammi, Nagendra S Yarla, Vladimir N Chubarev, Vadim V Tarasov, George E Barreto, Amita Martin Corolina Pasupulati, Gjumrakch Aliev, Nageswara Rao Reddy Neelapu

Open access · greenAbstract read
In one paragraph

Article in Current genomics, 2017. 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
1.2field-weighted citation impact, top 20% 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

4 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Exploring the inhibitory potential ofFrontiers in molecular biosciences · 2023
    Article
  3. Frontiers in microbiology · 2022
    Review
  4. Review
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

8 authors at 4 institutions in 4 countries.

Deepthi NammiDepartment of Biochemistry and Bioinformatics, GITAM Institute of Science, GITAM University, Rushikonda, Visakhapatnam - 534005 (AP), India.
Nagendra S YarlaDepartment of Biochemistry and Bioinformatics, GITAM Institute of Science, GITAM University, Rushikonda, Visakhapatnam - 534005 (AP), India.
Vladimir N ChubarevInstitute of Pharmacy and Translational Medicine, Sechenov First Moscow State Medical University, 19991Moscow, Russia.
Vadim V TarasovInstitute of Pharmacy and Translational Medicine, Sechenov First Moscow State Medical University, 19991Moscow, Russia.
George E BarretoDepartamento de Nutrición y Bioquímica, Facultad de Ciencias, Pontificia Universidad Javeriama, BogotáD.C., Colombia.
Amita Martin Corolina PasupulatiDepartment of Biochemistry and Bioinformatics, GITAM Institute of Science, GITAM University, Rushikonda, Visakhapatnam - 534005 (AP), India.
Gjumrakch AlievInstitute of Pharmacy and Translational Medicine, Sechenov First Moscow State Medical University, 19991Moscow, Russia.
Nageswara Rao Reddy NeelapuDepartment of Biochemistry and Bioinformatics, GITAM Institute of Science, GITAM University, Rushikonda, Visakhapatnam - 534005 (AP), India.
GITAM University · INSechenov University · RUInternational Biomedical (United States) · USPontificia Universidad Javeriana · CO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHelicobacter pylori is associated with inflammation of different areas, such as the duodenum and stomach, causing gastritis and gastric ulcers leading to lymphoma and cancer. Pathogenic islands are a type of clustered mobile elements ranging from 10-200 Kb contributing to the virulence of the respective pathogen coding for one or more virulence factors. Virulence factors are molecules expressed and secreted by pathogen and are responsible for causing disease in the host. Bacterial genes/virulence factors of the pathogenic islands represent a promising source for identifying novel drug targets.

objectiveThe study aimed at identifying novel drug targets from pathogenic islands in H. pylori. MATERIAL &

methodsThe genome of 23 H. pylori strains were screened for pathogenic islands and bacterial genes/virulence factors to identify drug targets. Protein-protein interactions of drug targets were predicted for identifying interacting partners. Further, host-pathogen interactions of interacting partners were predicted to identify important molecules which are closely associated with gastric cancer.

resultsScreening the genome of 23 H. pylori strains revealed 642 bacterial genes/virulence factors in 31 pathogenic islands. Further analysis identified 101 genes which were non-homologous to human and essential for the survival of the pathogen, among them 31 are potential drug targets. Protein-protein interactions for 31 drug targets predicted 609 interacting partners. Predicted interacting partners were further subjected to host-pathogen interactions leading to identification of important molecules like TNF receptor associated factor 6, (TRAF6) and MAPKKK7 which are closely associated with gastric cancer.

conclusionThese provocative studies enabled us to identify important molecules in H. pylori and their counter interacting molecules in the host leading to gastric cancer and also a pool of novel drug targets for therapeutic intervention of gastric cancer.

Indexed as

Comparative analysisGenomic islandsPathogenicityVirulence factors

Identifiers

PMID29081700
PMCPMC5635650
OpenAlexW2736152252

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.