Evidence map›Paper›PMID 36344599›Full record

ArticleScientific reports2022

A bioinformatics approach to the identification of novel deleterious mutations of human TPMT through validated screening and molecular dynamics.

Sidharth Saxena, T P Krishna Murthy, C R Chandrashekhar, Lavan S Patil, Abhinav Aditya, Rohit Shukla, Arvind Kumar Yadav, Tiratha Raj Singh, Mahesh Samantaray, Amutha Ramaswamy

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. 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
1.8field-weighted citation impact, top 13% 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

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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, 12 citations in OpenAlex.

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  4. Population-Specific Distribution ofTherapeutics and clinical risk management · 2023
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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

10 authors at 3 institutions in 1 country.

Sidharth SaxenaDepartment of Biotechnology, Ramaiah Institute of Technology, Bengaluru, Karnataka, 560054, India.
T P Krishna MurthyDepartment of Biotechnology, Ramaiah Institute of Technology, Bengaluru, Karnataka, 560054, India. tpk@live.in.ORCID 0000-0002-9533-7567
C R ChandrashekharDepartment of Biotechnology, Ramaiah Institute of Technology, Bengaluru, Karnataka, 560054, India.
Lavan S PatilDepartment of Biotechnology, Ramaiah Institute of Technology, Bengaluru, Karnataka, 560054, India.
Abhinav AdityaDepartment of Biotechnology, Ramaiah Institute of Technology, Bengaluru, Karnataka, 560054, India.
Rohit ShuklaDepartment of Biotechnology and Bioinformatics, Jaypee University of Information Technology (JUIT), Solan, Himachal Pradesh, 173234, India.
Arvind Kumar YadavDepartment of Biotechnology and Bioinformatics, Jaypee University of Information Technology (JUIT), Solan, Himachal Pradesh, 173234, India.
Tiratha Raj SinghDepartment of Biotechnology and Bioinformatics, Jaypee University of Information Technology (JUIT), Solan, Himachal Pradesh, 173234, India.
Mahesh SamantarayDepartment of Bioinformatics, Pondicherry University, Pondicherry, 605014, India.
Amutha RamaswamyDepartment of Bioinformatics, Pondicherry University, Pondicherry, 605014, India.
M S Ramaiah University of Applied Sciences · INJaypee University of Information Technology · INPondicherry University · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Polymorphisms of Thiopurine S-methyltransferase (TPMT) are known to be associated with leukemia, inflammatory bowel diseases, and more. The objective of the present study was to identify novel deleterious missense SNPs of TPMT through a comprehensive in silico protocol. The initial SNP screening protocol used to identify deleterious SNPs from the pool of all TPMT SNPs in the dbSNP database yielded an accuracy of 83.33% in identifying extremely dangerous variants. Five novel deleterious missense SNPs (W33G, W78R, V89E, W150G, and L182P) of TPMT were identified through the aforementioned screening protocol. These 5 SNPs were then subjected to conservation analysis, interaction analysis, oncogenic and phenotypic analysis, structural analysis, PTM analysis, and molecular dynamics simulations (MDS) analysis to further assess and analyze their deleterious nature. Oncogenic analysis revealed that all five SNPs are oncogenic. MDS analysis revealed that all SNPs are deleterious due to the alterations they cause in the binding energy of the wild-type protein. Plasticity-induced instability caused by most of the mutations as indicated by the MDS results has been hypothesized to be the reason for this alteration. While in vivo or in vitro protocols are more conclusive, they are often more challenging and expensive. Hence, future research endeavors targeted at TPMT polymorphisms and/or their consequences in relevant disease progressions or treatments, through in vitro or in vivo means can give a higher priority to these SNPs rather than considering the massive pool of all SNPs of TPMT.

Indexed as

Computational BiologyMethyltransferasesGenotypeHumansMolecular Dynamics SimulationMutationPolymorphism, Single NucleotideMethyltransferasesTPMT protein, human

Identifiers

PMID36344599
PMCPMC9640560
OpenAlexW4308444868

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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.