Evidence map›Paper›PMID 32704157›Full record

ArticleScientific reports2020

Investigating the pathogenic SNPs in BLM helicase and their biological consequences by computational approach.

Faisal A Alzahrani, Firoz Ahmed, Monika Sharma, Mohd Rehan, Maryam Mahfuz, Mohammed N Baeshen, Yousef Hawsawi, Ahmed Almatrafi, Suliman Abdallah Alsagaby, Mohammad Azhar Kamal and 3 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
2.1field-weighted citation impact, top 12% 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

21 citing papers in PubMed, 32 citations in OpenAlex.

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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

13 authors at 8 institutions in 4 countries.

Faisal A Alzahrani *Department of Biochemistry, Faculty of Science, Stem Cells Unit, King Fahd Medical Research Center, King Abdulaziz University, Jeddah, 21589, Saudi Arabia.ORCID http://orcid.org/0000-0003-0441-4000
Firoz Ahmed *Department of Biochemistry, College of Science, University of Jeddah, Jeddah, 21589, Saudi Arabia. fahmed1@uj.edu.sa.ORCID http://orcid.org/0000-0003-4702-5144
Monika Sharma *Department of Chemical Sciences, Indian Institute of Science Education and Research (IISER), Mohali, India.ORCID http://orcid.org/0000-0001-9864-3298
Mohd RehanKing Fahd Medical Research Center, King Abdulaziz University, Jeddah, Saudi Arabia.
Maryam MahfuzDepartment of Computer Science, Jamia Millia Islamia, New Delhi, Delhi, India.
Mohammed N BaeshenDepartment of Biology, College of Science, University of Jeddah, Jeddah, 21589, Saudi Arabia.
Yousef HawsawiDepartment of Genetics, Research Center, King Faisal Specialist Hospital, and Research Center, MBC-03, PO Box 3354, Riyadh, 11211, Saudi Arabia.ORCID http://orcid.org/0000-0003-1901-697X
Ahmed AlmatrafiDepartment of Biology, Faculty of Science, University of Taibah, Medinah, Saudi Arabia.
Suliman Abdallah AlsagabyDepartment of Medical Laboratories, Central Biosciences Research Laboratories, College of Science in Al Zulfi, Majmaah University, Al Majma'ah, Saudi Arabia.ORCID http://orcid.org/0000-0002-2242-5638
Mohammad Azhar KamalDepartment of Biochemistry, College of Science, University of Jeddah, Jeddah, 21589, Saudi Arabia.
Mohiuddin Khan WarsiDepartment of Biochemistry, College of Science, University of Jeddah, Jeddah, 21589, Saudi Arabia.
Hani ChoudhryDepartment of Biochemistry, Cancer Metabolism and Epigenetic Unit, Faculty of Science, Cancer and Mutagenesis Unit, King Fahd Center for Medical Research, King Abdulaziz University, Jeddah, Saudi Arabia.
Mohammad Sarwar JamalKing Fahd Medical Research Center, King Abdulaziz University, Jeddah, Saudi Arabia. Sarwar4u@gmail.com.
University of Jeddah · SAKing Abdulaziz University · SAAston University · GBIndian Institute of Science Education and Research Mohali · INJamia Millia Islamia · INKing Faisal Specialist Hospital & Research Centre · SAMajmaah University · SATaibah University · SA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The BLM helicase protein plays a vital role in DNA replication and the maintenance of genomic integrity. Variation in the BLM helicase gene resulted in defects in the DNA repair mechanism and was reported to be associated with Bloom syndrome (BS) and cancer. Despite extensive investigation of helicase proteins in humans, no attempt has previously been made to comprehensively analyse the single nucleotide polymorphism (SNPs) of the BLM gene. In this study, a comprehensive analysis of SNPs on the BLM gene was performed to identify, characterize and validate the pathogenic SNPs using computational approaches. We obtained SNP data from the dbSNP database version 150 and mapped these data to the genomic coordinates of the "NM_000057.3" transcript expressing BLM helicase (P54132). There were 607 SNPs mapped to missense, 29 SNPs mapped to nonsense, and 19 SNPs mapped to 3'-UTR regions. Initially, we used many consensus tools of SIFT, PROVEAN, Condel, and PolyPhen-2, which together increased the accuracy of prediction and identified 18 highly pathogenic non-synonymous SNPs (nsSNPs) out of 607 SNPs. Subsequently, these 18 high-confidence pathogenic nsSNPs were analysed for BLM protein stability, structure-function relationships and disease associations using various bioinformatics tools. These 18 mutants of the BLM protein along with the native protein were further investigated using molecular dynamics simulations to examine the structural consequences of the mutations, which might reveal their malfunction and contribution to disease. In addition, 28 SNPs were predicted as "stop gained" nonsense SNPs and one SNP was predicted as "start lost". Two SNPs in the 3'UTR were found to abolish miRNA binding and thus may enhance the expression of BLM. Interestingly, we found that BLM mRNA overexpression is associated with different types of cancers. Further investigation showed that the dysregulation of BLM is associated with poor overall survival (OS) for lung and gastric cancer patients and hence led to the conclusion that BLM has the potential to be used as an important prognostic marker for the detection of lung and gastric cancer.

Indexed as

Computational BiologyDatabases, ProteinModels, MolecularPolymorphism, Single NucleotideRecQ HelicasesBinding SitesEnzyme StabilityHumansBloom syndrome proteinRecQ Helicases

Identifiers

PMID32704157
PMCPMC7378827
OpenAlexW3045187060

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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.