DECIPHERING THE MOLECULAR FOUNDATIONS OF SAVANT
SYNDROME WITH CRISPR CAS9 DRIVEN GENOME EDITING AND
MUTATION ANALYSIS OF NRXN1
Tayyaba Noor 1, Ayesha Shakeel2, Javeria Aslam1, Zahra Azhar1, Komal Khalid1, Khadija Rani1,
1
Department of Biotechnology, Faculty of Science and Technology, University of Central Punjab, Lahore Pakistan.
2
Department of Biological Sciences, University of Chester, United Kingdom.
*
E-mail: tayyban911@gmail.com
(Tayyaba Noor), Tel: + +92 331 6989961
Abstract
Savant syndrome is a rare condition in which people with severe intellectual disabilities exhibit
some abilities that are well above average. Quick computations, artistic talent, the capacity to
create maps, and musical talent are a few examples. Some studies have identified associations
between Savant Syndrome and genetic variations in the genes that are involved in the development
and function of the brain, such as the NRXN1 which is involved in the formation of neural
connections. While it is believed to be related to differences in brain development and function,
more research is needed to fully understand the biological basis of Savant Syndrome. In silico,
mutation knockout for Savant syndrome involves the use of computational techniques to identify
and develop potential therapies that can target the underlying genetic or molecular mechanisms of
the condition. The first step of in silico mutation knockout is to identify the target molecules that
are involved in the pathogenesis of Savant syndrome. The implementation of these approaches for
future treatment strategies for Savant Syndrome could reduce the costs of medicines and reduce
the burden on patients, thereby providing hope that effective therapies can be rapidly translated
into Savant Syndrome. We have used different bioinformatics tools that are very effective to
perform mutation knockout as for the screening of the NRXN1 receptors coding region we have
used open reading frame (ORF) screening. It scanned the coding region in the NRXN1 gene that
encodes protein. The NCBI tool blast was used to check the similarity index, target alignment, and
identity score and for the genome engineering process or purpose we have used Cas9 endonuclease
protein. For designing gRNA, we have used a web-based CHOPCHOP as it is the most widely
used tool for CRISPR.
Keywords: Savant syndrome, artistic talent, memory, in silico mutation knockout.
1. Introduction:
Savant syndrome is a rare condition in which persons with various developmental disorders,
including autistic disorder, have amazing talent and extraordinary abilities in specific areas, such
as memory, art, or mathematics. These abilities, known as "islands of genius," are often in stark
contrast to the individual's overall cognitive and functional abilities. The exact prevalence of
Savant Syndrome is not known, but it is estimated to occur in about 1 in 10,000 individuals with
autism. It is more common in males than females. Savant skills can be present from early childhood
or can develop later in life (1).
Other studies have identified associations between Savant Syndrome and genetic variations in the
genes that are involved in the development and function of the brain, such as the NRXN1 gene
which is involved in the formation of neural connections, and the NLGN4 gene which is involved
in the function of neural connections. The cause of Savant Syndrome is not well understood, but
it is thought to be related to differences in brain development and function. Some researchers
believe that savant abilities may be a result of the brain compensating for areas of weakness by
developing exceptional abilities in other areas (2). Others suggest that savant abilities may be a
result of a hyper-specialization of specific brain regions. Currently, there is no specific treatment
for Savant Syndrome, and treatment is focused on addressing the underlying developmental
disorder, such as autism. However, some individuals with savant abilities have been able to use
their skills to achieve success in fields such as art, music, and mathematics (3).
One gap in our understanding of Savant Syndrome is the lack of a clear understanding of the
underlying causes of the condition. While it is believed to be related to differences in brain
development and function, more research is needed to fully understand the biological basis of
Savant Syndrome and how it leads to exceptional abilities in specific areas. Another gap is the lack
of effective treatments for Savant Syndrome. While treatment is currently focused on addressing
the underlying developmental disorder, such as autism, there is a need for specific interventions
that target the savant’s abilities themselves (4).
Another gap is the limited data and understanding of how savant abilities develop over time, how
they change with age, how they can be trained or improved, and whether they could be replicated
in non-savant individuals. Additionally, there is a need for more research on the psychological and
social aspects of Savant Syndrome, such as the impact of the condition on the individual's quality
of life and ability to function in society. Overall, more research is needed to fully understand the
complexities of Savant Syndrome and develop effective interventions to support individuals with
the condition (5).
The in silico procedure for knocking out a gene in savant syndrome involves several steps. The
first step is to identify the gene that is responsible for the savant syndrome. This can be done by
analyzing the genetic data of individuals with savant syndrome and comparing it to the genetic
data of individuals without the condition. Once the gene has been identified, a virtual model of the
gene can be created using bioinformatics tools. This model can be used to predict the effects of
knocking out the gene on the individual's brain function and behavior. The virtual model can then
be used to simulate the knock-out of the gene. This can be done by introducing a mutation into the
gene or by inhibiting its expression (6).
In general, the quality of life for individuals with savant syndrome can be affected by several
factors, including the severity of their cognitive and developmental disabilities, the presence of
other medical conditions, and access to appropriate support and resources. It's important to note
that most individuals with savant syndrome have some form of developmental disability, such as
autism, and may have difficulty with social interactions and other aspects of daily living. [43]
Additionally, the onset of savant syndrome can be caused by brain injury or disease, which can
have an additional impact on the individual life. Overall, the goal of treatment and support for
individuals with savant syndrome is to help them maximize their abilities and potential, while also
addressing any challenges they may face (7).
The future perspective of savant syndrome is likely to involve continued research into the causes
and potential therapies for the condition. Advances in brain imaging and genetic research may lead
to a better understanding of the neurological basis of savant syndrome and potentially lead to new
treatments. [40] Additionally, as technology continues to advance, it may also provide new tools
for individuals with savant syndrome to express and utilize their abilities. There is no in-silico
work is present on Savant syndrome. This research aims to design an effective method of gene
therapy that aids in the treatment of Savant Syndrome. However, it is important to note that savant
syndrome is a rare and complex condition, and more research is needed to fully understand its
implications. The implementation of in-silico approaches for the assessment of current and future
treatment strategies for Savant Syndrome could shorten the trial duration and reduce costs and
reduce the burden on patients, thereby providing hope that effective therapies can be rapidly
translated into the Savant Syndrome.
2. Materials and methods:
The study was carried out using bioinformatics-based approaches and the following materials and
methods were employed.
2.1. Sequence Retrieval:
National Centre for Biotechnology Information (NCBI) (https://www.ncbi.nlm.nih.gov/ ) was
used for retrieval of NRXN1 protein that carries mutations and causes Savant Syndrome. We need
Ref-Sequence from NCBI (National Centre for Biotechnology Information) because on NCBI
many raw sequences are available that are incorrect, and we are going to knock out the mutation
from the gene so we need the accurate sequence that’s why the reference sequence is preferable.
The gene whose sequence is retrieved was NRXN1 (Neurexin 1) whose accession ID: is
NM_001330078.2 (7).
2.2. Open Reading Frame (ORF) Screening:
An interactive web-based tool was used for the screening of NRXN1 receptor’s coding regions
commonly used for the prediction and analysis of Open Reading Frames. It is named ORF Finder
(https://www.ncbi.nlm.nih.gov/orffinder/). It scanned the coding region in the NRXN1 gene that
encodes protein. The possible coding regions present in the NRXN1 gene (8).
2.3. Search Similarity and Target alignment:
The NCBI tool BLAST (Basic Local Alignment Search Tool) was used to check the similarity
index, Target alignment, identity score, off-target sequence, and E value. The results showed
100.00 percent similarities between the coding regions. To check the similarity of our sequence
with the Database, we have to run BLASTx (it is a sub-tool of NCBI that helps to transcribe
nucleotides into protein) for further analysis (https://blast.ncbi.nlm.nih.gov/Blast.cgi). It gives
accurate similarity of our sequence with others so that we can proceed with our work to the next
step (9).
2.4. Cas9 Endonuclease Protein:
For genome engineering purposes, the specific enzyme Cas9 Endonuclease protein was employed.
The main reason to use this enzyme is that it is simple to use and has all the basic capabilities to
split DNA molecules into a single strand. The Cas9 genome editing protein includes blunt ends
cut sites, RNA-guided endonucleases, PAM site (TGG), crRNA, and tracrRNA. It can cut specific
regions of the genomic DNA. The double-stranded break in NRXN1 genomic DNA was done by
the cas9 protein (10).
2.5. Designing of gRNA:
The single-guided RNA was designed from verified sequences with the most authentic web-based
tool CHOPCHOP (an online tool that gives us wide input ranges and alignments to minimize
search times). We get the gRNA by an automated method. Three target sites of the NRXN1 gene
were selected for designing target sgRNAs based on their location in the exonic region, off-target
scores, and GC content (11).
2.6. Steps for Generating gRNA from CHOPCHOP:
Enter the Gene name on the home page of CHOPCHOP (https://chopchop.cbu.uib.no/ ). Now,
select your version of genome/specie. As we use CRISPR technology so select the specific version
of cas9 protein. Select the interest whether you want to knock out the mutation or gene inhibit or
repress. The general setting of CHOPCHOP is set by default. After setting all options click to find
your target. In the end, it gives the list of all gRNA present in your sequence. We select the desired
gRNA accordingly (12).
Characteristics of the off-Target and on-Target Scores:
Because GC includes three hydrogen bonds and is more stable guanine and cytosine are thought
to have a stronger connection. As a result GC content, of up to 50% destabilized off-target
hybridization
while
stabilizing
the
DNA-RNA
duplex.
The choice of the number range was made since it falls within the NRXN1 coding zone. [13] This
numerical range represents the off-target and on-target ratings for gRNA. They run from 0 to 100
with
100
being
considered
the
best
score
in
each
situation.
The genomic area of the gene being targeted must be carefully chosen. The NRXN1 gene was used
to obtain accurate off-target scores by Benching. On chromosome X, a single genomic area was
detected in a case. Exon of the NRXN1 receptor (13).
2.7. Verification of gRNA:
We need to check the gRNA capacity to bind the receptor of both off and on target for
confirmation. Many tools are offered for this purpose but usually, pick IDT (integrated DNA
TECHNOLOGY) (https://www.idtdna.com/pages ) database that allows the study of DNA or RNA
at the molecular scale. And more suitable gRNA becomes the greater quantity of on and off-target
concentration (14).
2.8. Designing importance Vector for gRNA:
We use a web tool named "vector builder" (to easily generate multiple kinds of a vector)
(https://en.vectorbuilder.com/ ). First, we pick Mammalian CRISPR gene editing, because it
includes the same restriction enzymes of the target gene we finally decided on adenoviruses.
Secondly, we chose a double gRNA vector. It automatically deletes the restriction enzymes,
allowing space for the gRNA sequence and cas9 protein to be inserted (15).
2.9.Calculation Ensemble Prediction thermodynamic:
A reliable tool for measuring hybridized energies and studying the thermodynamic relationship
between both the target gene and expected sgRNA is the RNAfold web tool
(http://rna.tbi.univie.ac.at/cgi-bin/RNAWebSuite/RNAfold.cgi ). Furthermore, Vienna RNA can
be applied, it also shows base pairing in RNA sequences. RNAfold was applied to evaluate
optimum duplex structure concentrations and innovative communication energies (16).
2.10. Prediction of Secondary structure:
The Mfold web application (http://rna.umrc rochester.edu/RNAstructureWeb) includes the
UNAfold tool, among the most reliable and commonly used techniques for the prediction of
secondary structure. These were used to predict the sgRNA of secondary structure strands. The
sgRNA structures containing the method are effectively predicted by reducing free energy (16).
Results:
1. Sequence Retrieval and Analysis:
Neurexin1 gene sequence retrieval was done from National Center for Biotechnology Information
(NCBI) using accession number NM_001330078.2. The sequence was selected by reviewing the
previous literature as well. NRXN1 (Neurexin 1) is a Protein Coding gene. The selected sequence
was of the start codon of the Neurexin1 gene, X chromosome positioned at 3421-3447.
2. Open Reading Frame (ORF) Screening:
The screening of our coding region of the Neurexin1 gene was performed by the open reading
frame finder. The ORF finder is most frequently used for the prediction and analysis of open
reading frames. In the Neurexin1 there are 48 ORFS are reported. And the ORFS were calculated
from the 1054_5593.
Figure 2: representing the open reading frame (ORF) of the NRXN1 gene.
3. Analyse the designed guide RNA:
The gRNA was designed on the base that it will identify or cut our target gene. Chop chop is the
web-based tool used to design our gRNA sequence. Then the targeted gene NRXN1 is added into
the software, the blue box represents the exon region and the red lines are showing to be introns.
Figure 3: is showing the structure of the NRXN1 gene. The CHOPCHOP has generated multiple
gRNA for the target gene. The CHOPCHOP will represent that sequence on the top which will
have zero mismatchesThehe mismatch numbers must be zero because if the number is greater than
one, it will cut he targeted as well as thee non-targeted region of our gene. We will select the top
3 target sequence from CHOPCHOP on the bases of their efficiency and 100% matching with the
target.
Figure 3 : The whole exonic and intronic structure of NRXN1 gene.
Figure 4: ACTGTCCACTCGCACCAATACGG, a rank 11 sequence, was picked from a
particular genomic region on chromosome 2 at position 50236825. This sequence showed two
occurrences of self-complementarity and has a 50% GC content. The left primer for this sequence
is
discovered
at
the
coordinates
chr2:50236935-50236957.
It
has
the
sequence
ATCTTTAGCAAAGGTGGTGGAC and a melting temperature of 59.5. Having a product size of
281, the appropriate primer, with the sequence AACAAAGTACTGGTTTCTGGGG and off-
target matches, is placed at the locations chr2:50236676-50236698. While the first gRNA is
present in the final exon, it is basically true that muar a protein's C-terminus are not always result
in a loss of function.
Figure
5:
At
position
50236895
on
chromosome
2,
a
rank
22
sequence,
GTACTGGGTCGGTCATTAGGAGG, were taken from the genome. This sequence showed two
instance of self-complementarity and has a 55% GC content. The left primer for this sequence is
situated at the coordinate values chr2:50236973-50236995. It contains the sequence
TTGGTTTTTTGGTTTTTGTTCC as well as a melting temperature of 60.1 degrees. With a
product size of 181, the right primer, with the sequence AAGCCTGAAGAACTGTCCACTC and
no off-target matches, is located at the positions chr2:50236814-50236836. And while the first
gRNA is situated in the final exon, it is basically true that mutations closer to a protein's C-terminus
are not always result in a loss of function.
Figure 6: AGAAGCCGTATTGGTGCGAGTGG, a rank 54 sequence, was chosen from a specific
genome sequence on chromosome 2 at location 50236895. This sequence shows no selfcomplementarity and has a 55% GC content. The left primer for this sequence is identified at the
coordinates
chr2:50236963-50236957.
It
also
has
the
sequence
ATCTTTAGCAAAGGTGGTGGAC and a melting temperature of 59.5. With a product size of
281, the right primer, with the sequence AACAAAGTACTGGTTTCTGGGG and no off-target
matches, is located at the positions chr2:50236676-50236698. Even though the first gRNA is
located in the last exon, it is basically true that mutations closer to a protein's C-terminus are less
likely to lead the protein to lose its function.
In this article, three gRNAs were designed (sgRNA1, sgRNA2, and sgRNA3) respectively. An
NRXN1 was positioned at chr2:50236825 in the NRXN1 gene within the target sequence
ACTGTCCACTCGCACCAATACGG. An NRXN2 was positioned at chr2:50236895 in the
NRXN1 gene sequence within the target sequence GTACTGGGTCGGTCATTAGGAGG and
NRXN3 was positioned at chr2:50236895 in the NRXN1 gene sequence within the target sequence
AGAAGCCGTATTGGTGCGAGTGG results are explained in table 1.
sgRNAs
Target sequence (5’-3’)
Position
of Off-
NRXN1gene
On-
GC%
target
target
Content
source
sources
s
sg(NRXN
ACTGTCCACTCGCACCAATAC
1)1
GG
sg(NRXN
GTACTGGGTCGGTCATTAGGA
1)2
GG
sg(NRXN
AGAAGCCGTATTGGTGCGAGT
1)3
GG
chr2:50236825
85
71
50%
chr2:50236895
83
55.7
55%
chr2:50236895
86
47.4
55%
Table 1: three gRNAs were designed (sgRNA1, sgRNA2, and sgRNA3
Primer validation: For the validation of the primer CHOPCHOP tool was used and the result
obtained from it are shown in table 2.
chr2:50236935-50236957
chr2:50236676-50236698
Assembly 1 FWD
Assembly 1 REV
5' ATCTTTAGCAAAGGTGGTGGAC 3’
Position +/
Tm 60°C
5' AACAAAGTACTGGTTTCTGGGG3'
Position –/
Tm 60°C
Length
22
Length
22
GC Content
45%
GC Content
45.5%
Melting Temp. Tm
59.5°C
Melting Temp. Tm
59.4°C
chr2:50236973-50236995
chr2:50236814-50236836
Assembly 2 FWD
Assembly 2 REV
5' TTGGTTTTGGTTTTTGTTTTCC 3'
Position +/
Tm 60°C
5' AAGCCTGAAGAACTGTCCACTC 3'
Position –/
Tm 60°C
Length
22
Length
22
GC Content
40%
GC Content
50%
Melting Temp. Tm
60.1°C
Melting Temp. Tm
59.9°C
chr2:50236935-50236957
chr2:50236676-50236698
Assembly 2 FWD
Assembly 2 REV
5' ATCTTTAGCAAAGGTGGTGGAC 3 '
Tm 60°C
Position +/
5' AACAAAGTACTGGTTTCTGGGG 3'
Position –/
Tm 60°C
Length
22
Length
22
GC Content
45%
GC Content
45.5%
Melting Temp. Tm
59.5°C
Melting Temp. Tm
59.4°C
4. Design of plasmid for genome editing:
Vector
builder
web
tool
(https://en.vectorbuilder.com/?gclid=EAIaIQobChMI4cG00IDo_
AIVUgOLCh1vuAk_EAAYAiAAEgLTnPD_BwE) was to generate plasmid, figure 7 shows the
various regions that have been present in the plasmid. To build a plasmid from vector builder
firstly, select the option design my vector then, select the mammalian CRISPR gene editing vector.
Now select the adenovirus and click on single guide RNA. This web tool vector builder provides
us space to add our guide RNA and Cas protein. our desired plasmid is ready. The plasmid contains
both chimeric guide RNA and the hCas9 expression site. A single gRNA scaffold was applied to
clone a set of processed fragments. The oligos were designed with both the target sequence site
(20bp) as the base and a 3bp PAM sequence (AGG) upstream of the protospacer on each side at
3'end.
Figure 7: showing the structure of the plasmid
For specific genome editing of the NRXN1 gene, plasmids was used to deliver CRISPR
component. NRXN1 gene multiple genome editing with very high efficiency using a CRISPR
CAS9 engineered technology gRNA express sequence was introduced into the plasmid used for
this study, while Cas9 gRNA was a founder with gRNA that recognized the target sequence or
gene from this cassette. Therefore, it is expected that the target sequence of the gene might be
targeted and deleted immediately as gRNA expression within the plasmid. Resulting in the
substantially longer Cas9 expression gRNA for Cas9 and NRXN1 genes being delivered by the
plasmid mechanism (17).
5. Prediction using a Thermodynamic ensemble:
The approximate prediction of the secondary structure free energy model is shown in Table. It was
such an energy-binding domain change between both the gRNA and off-target RNA. The least
frequency of free energy and ensemble variability were evaluated against target RNA sequences.
The thermodynamic composite predictions are shown and were projected that use RNA fold web
server. (http://rna.tbi.univie.ac.at/cgi-bin/RNAWebSuite/RNAfold.cgi)
Target
Target RNA sequence
No
01
ACTGTCCACTCGCACCA
Free
Energy
of Frequency of Ensemble
Thermodynamic
the MFE
Diversity
-0.65 kcal/mol
34.78 %
2.73
-0.83 kcal/mol
42.31 %
2.81
-2.81 kcal/mol
51.66 %
3.05
ATACGG
02
GTACTGGGTCGGTCATT
AGGAGG
03
AGAAGCCGTATTGGTGC
GAGTGG
Table 3: show thermodynamic composite predictions
Graph 1: represent the MFE structure, thermodynamic ensemble of RNA structures, and the
centroid structure. The optimal secondary structure ACTGTCCACTCGCACCAATACGG with a
frequency of minimum free energy -0.65 kcal/mol represent in graph.
Graph 2: represents the MFE structure, thermodynamic ensemble of RNA structures, and the
centroid structure. The optimal secondary structure GTACTGGGTCGGTCATTAGGAGG with a
frequency of minimum free energy -0.83 kcal/mol represent in the graph.
Graph 3: represent the MFE structure, thermodynamic ensemble of RNA structures, and the
centroid structure. The optimal secondary structure AGAAGCCGTATTGGTGCGAGTGG with a
frequency of minimum free energy -2.81 kcal/mol represent in the graph.
6. GC content calculation:
For
GC
content
prediction
was
used
“DNA
/RNA
calculator
of
GC
content”
(http://www.endmemo.com/bio/gc.php) . also used sgRNA gene must be brought down to a
particular minimum concentration. Identification of sg RNA’s secondary structure and free energy
folding were done using the CRISPR Cas9 mfold system. Our gRNA have respectively 50%, 55%,
and 55% GC content as reported by this server.
Graph 4: showing the percentage of the GC content
7. Secondary structure Prediction:
To predict the secondary structure of gRNA we use online tool from Mathew’s lab
(https://rna.urmc.rochester.edu/RNAstructure.html) first inputs the RNA sequence of interest into
the software. The software then performs a number of calculations, including energy minimization
and partition function analysis, to predict the most likely secondary structure of the RNA molecule.
This tool predict structure in a graphical format, such as a dot plot or a secondary structure diagram,
and can also output the structure in a variety of formats for further analysis.
A
B
Figure 9: (A) Secondary structure of target gRNA1 fold (B) Secondary structure of target gRNA1
MaxExpect (C) Secondary structure of target gRNA1 Partition.
A
C
B
Figure 10: (A) Secondary structure of target gRNA2 fold (B) Secondary structure of target
gRNA2 MaxExpect (C) Secondary structure of target gRNA2 Partition.
A
B
C
Figure 11:(A) Secondary structure of target gRNA3 fold (B) Secondary structure of target gRNA3
MaxExpect (C) Secondary structure of target gRNA3 Partition.
8. gRNA Designed evaluation:
The NRXN1 gene region is the target of a specially designed sgRNAs 1 and 2. The very first 20
nucleotide of the RNA, that are shown in green, encode specific selectivity of this compound. The
DNA sequence is changed by modifications to such 20-nt sequences.
Figure 12: The NRXN1 gene region is the target of a specially designed sgRNAs 1 and 2.
Study of the gRNAs. The gene's (-) sense side joined to a Cas9RNP, resulting a dual strand break
at location 50236825 and 50236925.
The gRNA should connect with complementary strand which is of the greatest importance. The
results are also presented in a similar form, showing the strong integration of the controlled strand.
The sgRNA's ability to bind with both the complementary strand of the targeted area indicated that
it was able to act as a gRNA.
Discussion:
Savant syndrome is a rare condition in which persons with various developmental disorders,
including autistic disorder, have amazing talent and extraordinary abilities in specific areas, such
as memory, art, or mathematics. These abilities, known as "islands of genius," are often in stark
contrast to the individual's overall cognitive and functional abilities. The exact prevalence of
Savant Syndrome is not known, but it is estimated to occur in about 1 in 10,000 individuals with
autism. It is more common in males than females. Savant skills can be present from early childhood
or can develop later in life. It is thought to be caused by a combination of genetic and
environmental factors, and studies have shown that variations in certain genes, such as NRXN1,
may be associated with an increased risk of developing savant syndrome (18).
The current study demonstrates the proof-of-concept utilizing the cellular disorder model whereby
genetic defect Savant syndrome could be corrected using CRISPR-Cas9 with results indicating
that they are more similar to 99%. It demonstrates the on-target and off-target scores that hold GC
content within 40-60%, observed by RNA /DNA GC Content Calculator. [40] This prediction is
considered significant for the implementation of sgRNAs action. CRISPR-Cas9 mechanism on the
mutant NRXN1 gene (19). Three target sites of NRXN1 gene were selected for designing target
sgRNAs based on their location in the exonic region,. Notably, the designed sgRNA1 and sgRNA2
targeted a sequence in the NRXN1 gene. The specificity of this complex is encoded in the first
20nt of the gRNA as shown in figure 5 (A) and (B). The binding ability of sgRNA with the
complementary sequence of the target region proves their aptitude for working as gRNA (20, 21).
Further validations are the minimum free energy that is considered as a benchmark of sgRNAs
structural accuracy. It measures the stability of the guide strand. The Mfold web server was used
to calculate the minimum free energy. RNA structure webserver was used to predict the secondary
structure of an oligonucleotide by folding minimum free energy as shown in table 2. This server
predicts the most stable structures of an oligonucleotide with max-expected accuracy as shown in
the graphical representation in Graphs 1,2 and 3. These graphs represent the MFE structure, the
thermodynamic ensemble of RNA structures, and the centroid structure. The folded structures of
oligonucleotides were predicted at a specific temperature of 39°C. These results indicate that
CRISPR-Cas9 can provide one of the best therapeutic approaches to Savant syndrome (19).
CRISPR technology is a novel strategy that is used for genome editing purposes. Imbued by the
CRISPR mechanism and suitability of gRNA, pharmaceuticals and, researchers are working to
utilize this strategy as a therapeutic approach for the next generation. By using CRISPR
technology, researchers can easily modify the gene function and alter the DNA sequence. The
emergence of CRISPR technology opens a new avenue to correct genetic disorders. Recently, it
has been used as an efficient tool for, site-specific, genome editing in single cells and entire
organisms in a specific manner. This study presents a specific possible future candidate in the
treatment of Savant syndrome that holds a tremendous potential therapeutic approach for a genetic
disorder (22, 23).
Conclusion:
In conclusion, savant syndrome is a rare disorder characterized by exceptional abilities in certain
areas such as music, art, or mathematics, despite overall intellectual impairment. It is thought to
be caused by a combination of genetic and environmental factors, and studies have shown that
variations in certain genes, such as NRXN1, may be associated with an increased risk of
developing savant syndrome. However, the exact causes of savant syndrome are not fully
understood and more research is needed to fully understand the underlying mechanisms of this
disorder.
We have used different bioinformatics tools that are very effective for the insilico drug designing
of savant syndrome such as for the screening of the NRXN1 receptors cotalentsion extraordinary
reading frame (ORF) screening. The NCBI tool blast was used to check the similarity index, target
alignment and identity score and E value, etc and for the genome engineering process or purpose
we have used Cas9 endonuclease protein. For designing gRNA we have used a web-based tool
CHOPCHOP as it is the most widely used tool for CRISPR.
Recommendation:
Since Savant Syndrome is a disease caused by NRXN1 proteins, in this research we attempted to
block the disease-causing expression of the gene by using CRISPR. The gRNA designed will bind
on the target site allowing the enzyme to perform cleavage and this will result in the removal of
those defective exons. This will cause the restoration of regular protein production similar to the
use of CRISPR in other diseases, which are caused by abnormal numbers of exons in the gene, e.g.
Huntington’s disease. The bioinformatics-based approach has shown accurate results, which need
to be backed by in vitro and in vivo results for the clinical manifestation of this method. We
encourage further research on this particular and possible way of curing this disease as CRISPRbased gene editing has tremendous potential for doing miracles in medical science.
CONFLICT OF INTEREST
The authors confirm that they have no known financial or interpersonal conflicts that would have
appeared to have an impact on the research presented in this study.
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