Evidence map›Paper›PMID 23716176›Full record

ArticleJournal of molecular modeling2013

In silico discrimination of nsSNPs in hTERT gene by means of local DNA sequence context and regularity.

C George Priya Doss, Chiranjib Chakraborty, B Rajith, N Nagasundaram

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of molecular modeling, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.6field-weighted citation impact, top 32% 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

3 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

4 authors at 2 institutions in 1 country.

C George Priya DossMedical Biotechnology Division, School of Biosciences and Technology, VIT University, Vellore, 632014, Tamil Nadu, India. georgecp77@yahoo.co.in
Chiranjib Chakraborty
B Rajith
N Nagasundaram
Vellore Institute of Technology University · INGalgotias University · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding and predicting the significance of novel genetic variants revealed by DNA sequencing is a major challenge to integrate and interpret in medical genetics with medical practice. Recent studies have afforded significant advances in characterization and predicting the association of single nucleotide polymorphisms in human TERT with various disorders, but the results remain inconclusive. In this context, a comparative study between disease causing and novel mutations in hTERT gene was performed computationally. Out of 59 missense mutations, five variants were predicted to be less stable with the most deleterious effect on hTERT gene by in silico tools, in which two mutations (L584W and M970T) were not previously reported to be involved in any of the human disorders. To get insight into the structural and functional impact due to the mutation, docking study and interaction analysis was performed followed by 6 ns molecular dynamics simulation. These results may provide new perspectives for the targeted drug discovery in the coming future.

Indexed as

Models, MolecularPolymorphism, Single NucleotideAmino AcidsAnemia, AplasticComputational BiologyDyskeratosis CongenitaHumansIdiopathic Pulmonary FibrosisLigandsMolecular Docking SimulationMolecular Dynamics SimulationMutationProtein BindingProtein ConformationProtein Interaction Domains and MotifsTelomeraseAmino AcidsLigandsTelomeraseTERT protein, human

Identifiers

PMID23716176
OpenAlexW2031989456

What OpenQuestion holds

Textmetadata
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.