Functional and structural analysis of non-synonymous single nucleotide polymorphisms (nsSNPs) in the MYB oncoproteins associated with human cancer

AbstractMYB proteins are highly conserved DNA-binding domains (DBD) and mutations in MYB oncoproteins have been reported to cause aberrant and augmented cancer progression. Identification of MYB molecular biomarkers predictive of cancer progression can be used for improving cancer management. To address this, a biomarker discovery pipeline was employed in investigating deleterious non-synonymous single nucleotide polymorphisms (nsSNPs) in predicting damaging and potential alterations on the properties of proteins. The nsSNP of the MYB family; MYB, MYBL1, and MYBL2 was extracted from the NCBI database. Five in silico tools (PROVEAN, SIFT, PolyPhen-2, SNPs&GO and PhD-SNP) were utilized to investigate the outcomes of nsSNPs. A total of 45 nsSNPs were predicted as high-risk and damaging, and were subjected to PMut and I-Mutant 2.0 for protein stability analysis. This resulted in 32 nsSNPs with decreased stability with a DDG score lower than − 0.5, indicating damaging effect. G111S, N183S, G122S, and S178C located within the helix-turn-helix (HTH) domain were predicted to be conserved, further posttranslational modifications and 3-D protein analysis indicated these nsSNPs to shift DNA-binding specificity of the protein thus altering the protein function. Findings from this study would help in the field of pharmacogenomic and cancer therapy towards better intervention and management of cancer.

Download Full-text

Exploring Single Nucleotide Polymorphisms in ITGAV for Gastric, Pancreatic and Liver Malignancies: An Approach towards Biomarker Discovery

Combinatorial Chemistry & High Throughput Screening ◽

10.2174/1386207323999200818164104 ◽

2020 ◽

Vol 23 ◽

Author(s):

Shreya Bhattacharya ◽

Pragati Prasad Sah ◽

Arundhati Banerjee ◽

Sujay Ray

Keyword(s):

Single Nucleotide Polymorphisms ◽

Cancer Progression ◽

Calcium Binding ◽

Biomarker Discovery ◽

Solvent Accessibility ◽

Structure Stability ◽

Nucleotide Polymorphisms ◽

Liver Malignancies ◽

Single Nucleotide ◽

Integrin Αv

Background: Integrin αV, encoded by ITGAV gene is one of the most studied protein subunits, closely associated with liver, pancreatic and stomach cancer progression and metastasis via regulation of angiogenesis. Occurrence of Single Nucleotide Polymorphisms (SNPs) in cancer-associated proteins is a key determinant for varied susceptibility of an individual towards cancer. Methodology: The study investigated the deleterious effects of these cancer-associated SNPs on the protein’s structure, stability and cancer causing potential using an in silico approach. Numerous computational tools were employed that identified the most deleterious cancer-associated SNPs and those to get actively involved in post-translational modifications. Impact of these SNPs on the protein structure, function and stability was also examined. Conclusion and Future Scope: A total 63 non-synonymous SNPs in ITGAV gene were observed to be associated in these three gastrointestinal cancers and among this 63, 19 were the most deleterious ones. The structural and functional importance of residues altered by most damaging SNPs was analyzed through evolutionary conservation and solvent accessibility. The study also elucidated three-dimensional structures of the 19 most damaging mutants. The analysis of conformational variation identified 5SNPs (D379Y, G188E, G513V, L950P, and R540L) in integrin αV, which influence protein’s structure. Three calcium binding sites were predicted at residues: D379, G384 and G408 and a peptide binding site at residue: R369 in integrin αV. Therefore, SNPs D379Y, G384C, G408R and R369W have the potential to alter the binding properties of the protein. Screening and characterization of deleterious SNPs could advance novel biomarker discovery and therapeutic development in future.

Download Full-text

Two single nucleotide polymorphisms in the human nescient helix-loop-helix 2 (NHLH2) gene reduce mRNA stability and DNA binding

Gene ◽

10.1016/j.gene.2012.09.068 ◽

2013 ◽

Vol 512 (1) ◽

pp. 134-142 ◽

Cited By ~ 5

Author(s):

Numan AL_Rayyan ◽

Umesh D. Wankhade ◽

Korie Bush ◽

Deborah J. Good

Keyword(s):

Dna Binding ◽

Single Nucleotide Polymorphisms ◽

Mrna Stability ◽

Nucleotide Polymorphisms ◽

Single Nucleotide ◽

Helix Loop Helix

Download Full-text

The impact of single-nucleotide polymorphisms of human apurinic/apyrimidinic endonuclease 1 on specific DNA binding and catalysis

Biochimie ◽

10.1016/j.biochi.2019.05.015 ◽

2019 ◽

Vol 163 ◽

pp. 73-83 ◽

Cited By ~ 8

Author(s):

Irina V. Alekseeva ◽

Anastasiia T. Davletgildeeva ◽

Olga V. Arkova ◽

Nikita A. Kuznetsov ◽

Olga S. Fedorova

Keyword(s):

Dna Binding ◽

Single Nucleotide Polymorphisms ◽

Nucleotide Polymorphisms ◽

Single Nucleotide ◽

The Impact

Download Full-text

DNA-Binding Small-Ligand-Immobilized Surface Plasmon Resonance Biosensor for Detecting Thymine-Related Single-Nucleotide Polymorphisms

Chemistry - A European Journal ◽

10.1002/chem.201101290 ◽

2011 ◽

Vol 17 (50) ◽

pp. 14104-14110 ◽

Cited By ~ 10

Author(s):

Sara Miura ◽

Seiichi Nishizawa ◽

Akinori Suzuki ◽

Yukiko Fujimoto ◽

Katsuya Ono ◽

...

Keyword(s):

Surface Plasmon Resonance ◽

Dna Binding ◽

Single Nucleotide Polymorphisms ◽

Surface Plasmon ◽

Plasmon Resonance ◽

Nucleotide Polymorphisms ◽

Single Nucleotide ◽

Surface Plasmon Resonance Biosensor

Download Full-text

Study of Single-Stranded DNA Binding Protein–Nucleic Acids Interactions using Unmodified Gold Nanoparticles and Its Application for Detection of Single Nucleotide Polymorphisms

Analytical Chemistry ◽

10.1021/ac200525a ◽

2011 ◽

Vol 83 (11) ◽

pp. 4251-4257 ◽

Cited By ~ 58

Author(s):

Yen Nee Tan ◽

Kwai Han Lee ◽

Xiaodi Su

Keyword(s):

Gold Nanoparticles ◽

Dna Binding ◽

Single Nucleotide Polymorphisms ◽

Nucleic Acids ◽

Binding Protein ◽

Dna Binding Protein ◽

Nucleotide Polymorphisms ◽

Single Nucleotide ◽

Single Stranded Dna

Download Full-text

The Effect of Synonymous Single-Nucleotide Polymorphisms on an Atypical Cystic Fibrosis Clinical Presentation

Life ◽

10.3390/life11010014 ◽

2020 ◽

Vol 11 (1) ◽

pp. 14

Author(s):

Giovana Bampi ◽

Anabela Ramalho ◽

Leonardo Santos ◽

Johannes Wagner ◽

Lieven Dupont ◽

...

Keyword(s):

Cystic Fibrosis ◽

Single Nucleotide Polymorphisms ◽

Protein Expression ◽

Protein Function ◽

Low Frequency ◽

Exon Skipping ◽

Cftr Gene ◽

Nucleotide Polymorphisms ◽

Single Nucleotide ◽

Exon 11

Synonymous single nucleotide polymorphisms (sSNPs), which change a nucleotide, but not the encoded amino acid, are perceived as neutral to protein function and thus, classified as benign. We report a patient who was diagnosed with cystic fibrosis (CF) at an advanced age and presented very mild CF symptoms. The sequencing of the whole cystic fibrosis transmembrane conductance regulator (CFTR) gene locus revealed that the patient lacks known CF-causing mutations. We found a homozygous sSNP (c.1584G>A) at the end of exon 11 in the CFTR gene. Using sensitive molecular methods, we report that the c.1584G>A sSNP causes cognate exon skipping and retention of a sequence from the downstream intron, both of which, however, occur at a relatively low frequency. In addition, we found two other sSNPs (c.2562T>G (p.Thr854=) and c.4389G>A (p.Gln1463=)), for which the patient is also homozygous. These two sSNPs stabilize the CFTR protein expression, compensating, at least in part, for the c.1584G>A-triggered inefficient splicing. Our data highlight the importance of considering sSNPs when assessing the effect(s) of complex CFTR alleles. sSNPs may epistatically modulate mRNA and protein expression levels and consequently influence disease phenotype and progression.

Download Full-text

A comparative study of machine-learning methods to predict the effects of single nucleotide polymorphisms on protein function

Bioinformatics ◽

10.1093/bioinformatics/btg297 ◽

2003 ◽

Vol 19 (17) ◽

pp. 2199-2209 ◽

Cited By ~ 89

Author(s):

V.G. Krishnan ◽

D.R. Westhead

Keyword(s):

Machine Learning ◽

Single Nucleotide Polymorphisms ◽

Comparative Study ◽

Protein Function ◽

Nucleotide Polymorphisms ◽

Learning Methods ◽

Single Nucleotide ◽

Machine Learning Methods

Download Full-text

Comprehensive Characterization of the Coding and Non-Coding Single Nucleotide Polymorphisms in the Tumor Protein p63 (TP63) Gene Using In Silico Tools

Biomolecules ◽

10.3390/biom11111733 ◽

2021 ◽

Vol 11 (11) ◽

pp. 1733

Author(s):

Shamima Akter ◽

Shafaat Hossain ◽

Md. Ackas Ali ◽

Md. Ismail Hosen ◽

Hossain Uddin Shekhar

Keyword(s):

Single Nucleotide Polymorphisms ◽

Protein Stability ◽

Protein Function ◽

Association Studies ◽

Md Simulations ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Single Nucleotide ◽

Comprehensive Characterization

Single nucleotide polymorphisms (SNPs) help to understand the phenotypic variations in humans. Genome-wide association studies (GWAS) have identified SNPs located in the tumor protein 63 (TP63) locus to be associated with the genetic susceptibility of cancers. However, there is a lack of in-depth characterization of the structural and functional impacts of the SNPs located at the TP63 gene. The current study was designed for the comprehensive characterization of the coding and non-coding SNPs in the human TP63 gene for their functional and structural significance. The functional and structural effects of the SNPs were investigated using a wide variety of computational tools and approaches, including molecular dynamics (MD) simulation. The deleterious impact of eight nonsynonymous SNPs (nsSNPs) affecting protein stability, structure, and functions was measured by using 13 bioinformatics tools. These eight nsSNPs are in highly conserved positions in protein and were predicted to decrease protein stability and have a deleterious impact on the TP63 protein function. Molecular docking analysis showed five nsSNPs to reduce the binding affinity of TP63 protein to DNA with significant results for three SNPs (R319H, G349E, and C347F). Further, MD simulations revealed the possible disruption of TP63 and DNA binding, hampering the essential protein function. PolymiRTS study found five non-coding SNPs in miRNA binding sites, and the GTEx portal recognized five eQTLs SNPs in single tissue of the lung, heart (LV), and cerebral hemisphere (brain). Characterized nsSNPs and non-coding SNPs will help researchers to focus on TP63 gene loci and ascertain their association with certain diseases.

Download Full-text