Abstract analysis, SNPs information of CYP11B gene was retrieved



Single nucleotide polymorphisms (SNPs) are frequently occurring genetic
variations in human genome. Recent studies focused on SNPs in CYP11B2 gene. Different
data sequencing technologies such as in Silico analysis and computational
analysis of SNPs in CYP11B2 gene showed that mutations in these genes leads to
different pathologies.

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Single nucleotide polymorphisms (SNPs) are most common genetic
variations in human genome and provide genetic basis of complex human diseases
and drug responses. Theoretical and computational methods are mainly used for
identification of SNPs because these methods are fast and reliable. The
aldosterone synthase (CYP11B2) gene is located on chromosome 8q24.3 and encodes
aldosterone synthase. This enzyme play important role in the aldosterone
biosynthesis. The structure of CPY11B2 gene is determined by X-ray
crystallography. Recently, there is considerable interest in understanding the
role of CYP11B2 gene in corticosterone methyl oxidase deficiency, primary
aldosteronism, and cardio-cerebral-vascular diseases. Only few SNPs are studied
in CYP11B2 gene.


Materials and Methods


Collection of Dataset


In computational analysis, SNPs information of CYP11B gene was
retrieved from the National Center of Biotechnology Information (NCBI) database
of SNPs (dbSNP).


nsSNP functionality assessment


By using SIFT, Polyphen, and I- Mutant Suite, the functional
perspective of nsSNPs was predicted. SIFT is a sequence homology-based tool for
predicting whether protein tolerate to amino acid substitution or damaged by
it. A tolerance index score of 0.05 indicated deleterious effects and lower
tolerance index value showed that amino acid substitution have some functional
impacts. PolyPhen is an automatic tool to predict possible effect of amino acid
substitution on different features such as sequence, phylogenetic, and
structural information. The PolyPhen output score ranges from 0 to 1. A zero
score value show neutral effect of amino acid substitution while high score
indicate its damaging effects on protein function.

I-Mutant Suite is support vector machine (SVM) based predictors of
protein stability according to enthalpy change, Gibbs free energy change, and
transition temperature.


nsSNPs evolutionary conservation analysis


An amino acid plays important role in the enzymatic catalysis and
remain unchanged during random evolutionary drift. The ConSurf server that is a
bioinformatics tool for predicting amino acid evolutionary conservation is
based on phylogenetic relationships between proteins and its homologs. A
conservation score of 1 to 4 indicates variable and score of 7 to 9 is
considered conserved.


UTR SNPs functional context evaluation


The 5′ and 3′ untranslated regions of eukaryotic mRNAs play
important role in posttranscriptional gene expression regulation. By using UTR
Scan, MirSNP, PolymiRTS and miRNASNP, functional perspectives of UTR were
studied. The UTR Scan search for UTR functional elements in user submitted
sequence data according to defined patterns in UTR site collection, which is a
collection of regulatory elements present in 5′ and 3′ UTRs whose structure and
function were known. If different functional patterns are found for different
sequences for each UTR SNP, then this UTR SNP considered to have functional
significance.  MirSNP is a database of
SNPs used to predict whether the SNP within the target site would
decrease/break or enhance according to information from miRBase 18 and dbSNP
135.  PolymiRTS is a database of
naturally occurring DNA variations in seed regions and target sites of miRNA.
PolymiRTS database provides extensive and precise interactions between mRNA and

MicroRNA SNP database is used to predict SNPs effect within
pre-microRNA, mature microRNA, miRNA target sequences and neighboring regions.


Molecular dynamics simulation and molecular modeling


For estimating the native and mutant proteins structural stability,
a structural analysis was done. Molecular dynamics stimulation techniques and
energy minimization is used for understanding the structural variations in
mutant protein in comparison with native structure using the NAMD 2.6 package. The
limit for electrostatic and van der walls interactions was 12.0 A ° and
temperature was maintained at 310K.


Statistical analysis


Statistical analysis for determining RMSD, Rg and SASA value
differences between native and mutant protein was performed by using SAS 9.1
software. T-test was used for comparing differences between the native and
mutant protein, if quantitative data is adequate for both normal distribution
and homogeneity of variance. Nonparametric Wilcoxon two sample test was used
for other cases. Medians and interquartile ranges were used for summarizing parameters.
The difference was considered statistically significant, if P-value was less
than 0.05.


Construction of CYP11B2 database


The natural variants in database retrieved from the database of SNP
(dbSNP). The functional effects for each nsSNP were predicted by using SIFT,
PolyPhen-2, and I-Mutant Suite. Meanwhile, functional significance of UTRs SNPs
were predicted by using MirSNP, PolymiRTS and miRNASNP.




Dataset of SNP from dbSNP


The human CYP11B2 gene consists of 358 SNPs and out of these 358
SNPs, 51 are nsSNPs and 36 are coding synonymous SNPs. The non-coding region
contains 166 SNPs in intronic region, 79 SNPs in the “near gene” region, and 26
SNPs in the mRNA UTR region.


Deleterious and damaging nsSNPs identification


The nsSNPs identification that confer resistance to human diseases
became possible with improvement in silico tools. For determining nsSNPs
functional significance in CYP11B2 gene, three in silico tools were
used. 19 nsSNPs analyzed through SIFT with score of less than or equal to 0.05
were considered to be deleterious and seven out of these were considered to be
highly deleterious with score of 0. Through PolyPhen, 51 nsSNPs were analyzed.
Out of these 51 nsSNPs, 14 nsSNPs were found to be ”probably damaging”, 9 nsSNPs
were predicted to be ”possibly damaging”, and 23 nsSNPs were found to be
damaging. Through I-Mutant Suite, 24 nsSNPs were found to show value of less
than 20.5, indicating that these are largely unstable.


nsSNPs analysis in the conserved region


A disease causing mutation frequently exist in highly conserved
regions. Out of six nsSNPs analyzed by using ConSurf server, four nsSNPs
positions of V129M, T498A, F487V, and V403E were found to be exited in a highly
conserved amino acid region.


UTR SNPs functional elements


UTRs play an important role in the post-transcriptional regulation
of gene expression and variations in UTR are responsible for serious pathology.
Using UTR scan, all of the 26 UTR SNPs were analyzed. Comparison of each UTR
SNP functional elements, three SNPs rs61763988, rs35574522, and rs3097 showed a
change of upstream open reading frame (uORF).


Native and mutant CYP11B2 proteins molecular dynamics simulation


The RMSD, Rg, and SASA variations were examined between the native
and four mutant structures. In all these five structures, significant
structural variations were detected during the initial few picoseconds, which
leads to RMSD of 1.2A ° and then significant structural deviations during the
rest of the stimulations. Rg is the mass-weight root mean square distance of
collection of atoms from their common center of mass. It provides understanding
of overall protein dimension. The Rg value statistical analysis during last 200
picoseconds of the simulation showed that F487V, V129M, and T498A had
significant differences with native structure. The SASA is the biomolecule
surface area that is available to solvent and can be linked to the hydrophobic
core. SASA is calculated by ‘rolling ball’ algorithm. Data analyses showed
significant differences between four mutant structures and native structure.


Database of CYP11B2


CYP11B2 database allows user to retrieve data quickly and analyze
the effect of protein variants rapidly. This database also allows dynamic
utilization by permitting users to select only most important mutations and
algorithms results. The use of in silico analysis provide help in
further experimental research.




Due to different technologies, it was identified that different
genomic variants, specifically SNPs, are rapidly growing in human genome. Computational
analysis of SNPs in CRY11B2 gene showed that mutations in this gene leads to
complex human diseases. The UTR SNPs in the CYP11B2 gene were predicted by UTR
Scan, MirSNP, PolymiRTS and miRNASNP. It was found that three SNPs in the 3′
UTR region show change in upstream open reading frames (uORFs) and eight SNPs
in this region effect miRNA binding.


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