Evidence map›Paper›PMID 36881567›Full record

ArticlePloS one2023

Identification of potential therapeutic intervening targets by in-silico analysis of nsSNPs in preterm birth-related genes.

Muhammad Bilal Azmi, Waqasuddin Khan, M Kamran Azim, Muhammad Imran Nisar, Fyezah Jehan

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2023. 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
1.1field-weighted citation impact, top 23% 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, 7 citations in OpenAlex.

  1. Article
  2. 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 at 2 institutions in 1 country.

Muhammad Bilal AzmiDepartment of Biochemistry, Dow Medical College, Dow University of Health Sciences, Karachi, Pakistan.ORCID 0000-0001-8320-4479
Waqasuddin KhanBiorepositroy and Omics Research Group, Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Karachi, Pakistan.ORCID 0000-0001-7995-8163
M Kamran AzimDepartment of Biosciences, Faculty of Life Sciences, Mohammad Ali Jinnah University, Karachi, Pakistan.
Muhammad Imran NisarBiorepositroy and Omics Research Group, Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Karachi, Pakistan.
Fyezah JehanBiorepositroy and Omics Research Group, Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Karachi, Pakistan.ORCID 0000-0002-5874-4358
Aga Khan University · PKMohammad Ali Jinnah University · PK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prematurity is the foremost cause of death in children under 5 years of age. Genetics contributes to 25-40% of all preterm births (PTB) yet we still need to identify specific targets for intervention based on genetic pathways. This study involved the effect of region-specific non-synonymous variations and their transcript level mutational impact on protein functioning and stability by various in-silico tools. This investigation identifies potential therapeutic targets to manage the challenge of PTB, corresponding protein cavities and explores their binding interactions with intervening compounds. We searched 20 genes coding 55 PTB proteins from NCBI. Single Nucleotide Polymorphisms (SNPs) of concerned genes were extracted from ENSEMBL, and filtration of exonic variants (non-synonymous) was performed. Several in-silico downstream protein functional effect prediction tools were used to identify damaging variants. Rare coding variants were selected with an allele frequency of ≤1% in 1KGD, further supported by South Asian ALFA frequencies and GTEx gene/tissue expression database. CNN1, COL24A1, IQGAP2 and SLIT2 were identified with 7 rare pathogenic variants found in 17 transcript sequences. The functional impact analyses of rs532147352 (R>H) of CNN1 computed through PhD-SNP, PROVEAN, SNP&GO, PMut and MutPred2 algorithms showed impending deleterious effects, and the presence of this pathogenic mutation in CNN1 resulted in large decrease in protein structural stability (ΔΔG (kcal/mol). After structural protein identification, homology modelling of CNN1, which has been previously reported as a biomarker for the prediction of PTB, was performed, followed by the stereochemical quality checks of the 3D model. Blind docking approach were used to search the binding cavities and molecular interactions with progesterone, ranked with energetic estimations. Molecular interactions of CNN1 with progesterone were investigated through LigPlot 2D. Further, molecular docking experimentation of CNN1 showed the significant interactions at S102, L105, A106, K123, Y124 with five selected PTB-drugs, Allylestrenol (-7.56 kcal/mol), Hydroxyprogesterone caproate (-8.19 kcal/mol), Retosiban (-9.43 kcal/mol), Ritodrine (-7.39 kcal/mol) and Terbutaline (-6.87 kcal/mol). Calponin-1 gene and its molecular interaction analysis could serve as an intervention target for the prevention of PTB.

Indexed as

Genes, RegulatorPremature BirthExonsHumansInfant, NewbornMolecular Docking SimulationPolymorphism, Single NucleotideProgesteroneProgesterone

Identifiers

PMID36881567
PMCPMC9990928
OpenAlexW4323347268

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.