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In silico analysis of missense SNPs inGABRA1,GABRB1,andGABRB3genes associated with some diseases in neurodevelopmental disorders



Neurodevelopmental disorders are disorders that are generally seen in the early developmental period of an individual's life and involve more than one disease that causes disruptions in the central nervous system. These disorders can be given as examples of diseases such as autism, mental retardation, some epileptic disorders, communication disorders, and mental retardation. The aim of this study is to determine the possible harmful effects of missense single nucleotide polymorphisms (SNPs) in theGABRA1,GABRB1, andGABRB3genes, which are associated with neurodevelopmental disorders, on the structure and stabilization of the protein, using in silico methods. Software tools SIFT, PolyPhen-2 HumVar, PolyPhen-2 HumDiv, PROVEAN, SNAP2, PHD-SNP, SNP&GO, PANTHER, and Meta-SNP were used to predict harmful SNPs. I-Mutant and MUpro software tools were used to predict the effects of predicted harmful SNPs on protein stabilization. The STRING software tool was used for protein–protein interactions, the GeneMANIA software tool for gene–gene interactions, and the Project HOPE software tool for three-dimensional modeling examples.


As a result of the bioinformatics analysis, rs121434579, rs139163545, and rs267600530 in theGABRA1gene; rs74608570, rs75612351, rs78815529 in theGABRB1gene, and rs7819600779, rs1719850690, rs7819600779, rs171985060690, rs7819600779, rs1719850600779, rs149963014 in theGABRB3gene were predicted as harmful SNPs.


In this study, protein structure, function, and stabilization of SNPs known to cause amino acid substitutions inGABRA1,GABRB1, andGABRB3genes associated with some diseases in neurodevelopmental disorders were investigated using bioinformatics tools. As a result of the results obtained in our study, it is thought that it will benefit experimental studies and bioinformatics studies.


Neurodevelopmental disorders (NDD) are defined by delayed and abnormal development of the brain, especially early in development. Neurodevelopmental disorders lead to deficiencies in cognitive, verbal, and motor behaviors and other functions, especially accompanied by somatic findings [1]。In particular, various environmental and genetic factors cause diseases such as autism, Down Syndrome, Rett Syndrome, neurofibromatosis, and epilepsy which are examined among neurodevelopmental disorders. Neurodevelopmental disorders are seen in approximately 1–2% of the population compared to the general population [2]。Different genetic mutations and environmental factors are effective in the emergence of neurodevelopmental disorders. Examples of these environmental factors are various infections, immune dysfunction, endocrine and metabolic dysfunction, trauma, and nutritional differences [3]。Another factor that genetically affects neurodevelopmental disorders can be given as an example of single nucleotide polymorphism (SNP).

GABRA1encodes the alpha (a) subunit of the gamma-aminobutyric acid receptor (GABAAR) which is located in chromosome 5 [4]。这gene encodes the (GABA) gamma-aminobutyric receptor. GABA, a neurotransmitter in the mammalian brain, acts on the GABAA receptor with ligand-closed chloride channels. The chloride conductivity through which these channels act can be modified and regulated by agents that bind to the GABAA receptor, such as benzodiapenes (GeneCards n.d.).GABRB1, also known as Gamma-Aminobutyric Acid Type A Receptor Subunit Beta 1, is located between 46,995,740–47,428,461 base pairs on chromosome 4 (GeneCards n.d.). TheGABRB1gene is a good candidate gene among the specific genes participating in the structure and function of the thalamus. This gene acts on the beta subunit of the GABAA receptor, which specifically affects fast synaptic transmission in the mammalian brain. The domain of this gene has been found to affect postsynaptic current, a fast inhibitory site in the thalamus. Several clinical trials have been proposed, including studies betweenGABRB1and the thalamus and patients with bipolar disorder, autism, schizophrenia, neuropathic pain, and alcohol dependence [5]。TheGABRB3gene is a gene located on chromosome 15q12 that encodes beta-3 protein, a GABAA receptor-linked gamma-aminobutyric acid (GABA) receptor subunit. TheGABRB3gene is thought to have possible effects on histamine-directed effects, GABA iron-gated ion channel function, and inhibitory GABAergic synapses. The beta-3 subunit is expressed in structures such as the thalamus, cerebellum, cerebral grey matter, and hippocampi. Dysfunction of theGABRB3gene has been associated with neurodevelopmental disorders [6]。In this study, protein structure, function and stabilization of SNPs known to cause amino acid changes inGABRA1,GABRB1,andGABRB3genes associated with some diseases investigated in neurodevelopmental disorders were investigated using bioinformatics tools.

With the identification of quantitative trait loci as a result of genome-wide association studies (GWAS) for the detection of sequence variation in humans, interest in large-scale high-density SNP studies has increased significantly [7]。SNP is defined as single base sequence variations encountered in a particular region of the genome. As a result of human genome studies, SNPs are quite common in the human genome and SNPs can be used especially in the mapping of genetic diseases. There may be millions of SNPs in an individual, and these millions of SNPs are an important type of DNA polymorphism in the emergence of genetic and morphological differences between individuals. SNPs can be used in different fields. For example, it can be used for individual identification and identification, for ancestry, for phenotype determination, and for pathological and toxicological studies [8]。

In silico, in its most general sense, means the determination of chemical substances and the calculation and scientific analysis of their effects using computer and computer simulation technologies. In silico methods have recently gained momentum in the field of toxicology and pharmacology. With these methods, the body's properties, effects, and response to these effects can be predicted through computer-based chemical and drug programs. Considering the benefits of in silico methods, data can be determined in a short time with this method, it is cheap and fast, and it allows the evaluation of more than one data at the same time. It also provides an alternative to animal experiments and in vitro testing [9]。

The purpose of this study is to predict deleterious SNPs in theGABRA1,GABRB1,andGABRB3genes associated with neurodevelopmental disorders and to analyze three-dimensional models of proteins encoded by those genes, gene–gene interactions, and protein–protein interactions using various online software tools to provide data for further experimental and bioinformatic studies.


Data collecting

The SFARI database was used to select genes to be studied in our study ( NCBI ( and NCBI dbSNP (, were used to determine the SNP ID, position, nucleotide change, and amino acid changes of the SNPs within those genes. UniProt database ( was used to obtain FASTA format amino acid sequence and UniProtKB entry numbers of proteins.

Gene–gene interactions

The gene–gene interactions were examined by using the GeneMANIA software tool ( GeneMANIA is a website for making assumptions about the function of genes, constructing gene sequences, analyzing gene sequences, and identifying genes for functional analysis. This software tool can be used for single-gene queries, multi-gene queries, and network scanning. When a gene is scanned to this website, it finds its possible interaction with other genes [10]。

Protein–protein interactions

Protein–protein interaction was determined using the STRING software tool ( The STRING database aims to collect and integrate this information by bringing together data involved in known or probable protein–protein interactions for more than one organism [11]。

In silico analysis of SNPs

筛选,PolyPhen-2 (HumVar HumDiv), PROVEAN,系统网络体系结构(SNA)P2, PHD-SNP, SNP&GO, PANTHER, and Meta-SNP software tools were used to predict the possible effects of SNPs in theGABRA1,GABRB1andGABRB3genes on the protein structure and function. In the results obtained from these software tools, SNPs that have predicted common deleterious or disease-related results have been determined in all of them.

Sorting Intolerant From Tolerant (SIFT) is a publicly available software tool that estimates if an amino acid change causes impaired protein function based on physical features and sequence homology of amino acids [12] ( Polymorphism Phenotyping v2 (PolyPhen-2) is a publicly available software tool that estimates the stability and effect of amino acid changes on human proteins by evaluating based on functional and physical evolution [13] ( PROVEAN (Protein Variation Effect Analyzer) is a publicly available software tool that evaluates if an amino acid substitution or indel (small genetic variation) has an effect on the functionality of a protein. Harmful and neutral results can be achieved with PROVEAN ( SNAP2 is a neural network-based software tool to discriminate between various neutral and non-neutral variants, reveal biochemical differences of input, and reveal functional and structural features of the predicted protein sequence [14] ( PHD-SNP is a publicly available software tool for predicting whether single point protein mutations in a given region will be disease-causing or neutral polymorphisms. Two different results can be obtained “disease” or “neutral” by this software tool ( SNP&GO is a publicly available software tool for predicting single-point protein mutations in human diseases. SNP&GO is a support vector machine-based tool that estimates disease-causing mutations in the protein ( PANTHER (Protein Analysis Through Evolutionary Relationships) is a public database designed to facilitate gene and protein classes. In this software tool, proteins are classified according to their various functions ( In the Meta-SNP software tool, results can be obtained with the help of the SIFT, PHD-SNP, PANTHER, and SNAP2 software tools to distinguish between disease-related non-synonymous SNVs (nsSNV) (

Effects of predicted harmful SNPs on protein stabilization

I-Mutant 3.0 and MUpro software tools based on support vector machines were used to predict the impacts of predicted harmful SNPs on protein stabilization. The I-Mutant 3.0 and MUpro are publicly available software tools that predict the effects of mutations at a single location on the stabilization of proteins. (, (

Creating three-dimensional models of predicted deleterious variations

The 3D modeling of the proteins was obtained via the Project HOPE software tool. Project HOPE is a public website that analyzes the point mutation in the protein sequence. In this software tool, 3D shapes and animations are reported by searching and integrating the information in the system by entering protein mutation and sequence information. In addition, results of amino acids in terms of size, charge, hydrophobicity, and conservation were obtained with the Project HOPE software tool. (


Prediction results of harmful SNPs by in silico methods

A total of 21,956 SNPs of which 263 were missense SNPs were found in theGABRA1gene. 299 amino acid substitutions for 263 SNPs were examined. 399 missense SNPs were determined in theGABRB1gene among a total of 170,637 SNPs and 335 amino acid changes were analyzed for those missense SNPs.GABRB3gene contained 338 missense SNPs among 86,129 SNPs and 357 amino acid substitutions were determined for those missense ones.

Using all software tools, it was determined that there were three harmful SNPs (rs121434579, rs139163545, rs267600530) in theGABRA1gene (Table1), three SNPs (rs74608570,rs75612351, rs78815529) in theGABRB1gene (Table2) and six SNPs (rs78196007,rs78196007, rs17850679, rs72708067, rs111596597, rs149963014) in theGABRB3gene (Table3).

表1 snp可能的预测结果software tools in the GABRA1 gene
Table 2 Possible prediction results of SNPs using software tools in the GABRB1 gene
Table 3 Possible prediction results of SNPs using software tools in the GABRB3 gene

Results of the protein stabilization

The effects of high-risk SNPs in theGABRA1,GABRB1,andGABRB3genes on the protein stabilization were investigated using software tools I-Mutant 3.0 and MuPro. The results are shown in Tables1,2, and3, respectively.

Gene–gene interactions

The GeneMANIA software tool was used to examine the interaction of theGABRA1,GABRB1, andGABRB3genes with other genes, respectively. The gene–gene interactions within the three genes are shown in Fig.1. Co-expression/localization, genetic/physical interactions, predicted, pathway, and shared protein domains were also shown in Fig.1.

Fig. 1
figure 1

AGABRA1,BGABRB1andCGABRB3gene–gene interaction network (GeneMANIA n.d.)

Protein–protein interaction

The STRING database shows the relationship to 10 proteins encoded by theGABRA1,GABRB1,andGABRB3(Fig.2) genes.

Fig. 2
figure 2

Interaction network of proteins associated with theAGABRA1,BGABRB1 andCGABRB3 protein (STRING n.d.)

Creating three-dimensional models of predicted harmful variations

The possible effects of amino acid substitution because of by SNPs in theGABRA1,GABRB1,andGABRB3genes were investigated using the Project HOPE and the three-dimensional modeling of the proteins was obtained (Table4). Also, the differences in hydrophobicity, charge, and size between wild and mutant-type amino acid residues at polymorphism positions were investigated with Project HOPE. The results are summarized in Table5. In addition, according to the evolutionary conservation analysis scores of the Project HOPE software tool, it is estimated that the mutation is likely to be damaging to the protein due to mutant residues in the S303F, R147W, and A322D substitutions in the GABRA1; D450G and P458L substitutions in the GABRB1; I213T, Q173L, T85I, and T156I substitutions in the GABRB3 are near a conserved region. In addition, W469C amino acid change in the GABRB1 is estimated to be probably damaging to the protein because of wild-type residue is very conserved. Although the wild-type residue is very conserved in the M80V substitution in GABRB3, the mutation might not be damaging in some rare cases due to the properties of mutant residue which is near to a highly conserved position. Due to the characteristics of the Y324C mutant residue in the GABRB3, this mutation is acceptable even though the mutant residue is near a conserved region [18]。

Table 4 Project HOPE software tool modeling results ofGABRA1、GABRB1 GABRB3
Table 5 Results of differences between wild and mutant variants from the Project HOPE software tool


SNPs can alter the effects of the encoded protein and disease outcome. Due to differences in genetic sequences and their effects on protein structure and stabilization, in silico studies of SNPs have accelerated the understanding of this relationship. Experimentally investigating the effect of multiple SNPs can be very costly. It is also a laborious process and takes a lot of time. Consequently, in silico methods can be a preliminary platform to investigate the function of SNPs [15]。In our study, possible harmful effects of SNPs inGABRA1,GABRB1,andGABRB3genes associated with neurodevelopmental disorders were investigated with SIFT, PolyPhen-2, PROVEAN, SNAP2, PHD-SNP, SNP&Go, PANTHER, and META-SNP. The effects of amino acid change caused by SNPs on protein stabilization were investigated using I-Mutant 3.0 and MuPro software tools (Tables1,2, and3). The differences in hydrophobicity, charge, and size between wild and mutant type amino acids as well as three-dimensional modeling of protein and polymorphism sites were investigated using the Project HOPE software tool (Tables4,5). Gene–gene and protein–protein interactions were determined via GeneMANIA and STRING software tools, respectively (Figs.1,2).

In our study, there was no study other than the A322D and R147W variants in the GABRA1 gene in the literature on SNPs, which we found to be potentially harmful in common with all software tools. Biterge Süt et al. (2021) investigated nsSNPs of ion channel-related genes in epilepsy and they reported that A322D in the GABRA1 gene was pathogenic and decreased protein stability via in silico methods [16]。Hernandez et al. (2016) investigated variants inGABRgenes in cases of genetic epilepsy 2016. The R147W variant is one of the variants identified by exon sequencing. Also, the R147W variant was scored as deleterious via with PolyPhen-2 software tool [17]。

The size differences between wild and mutant type amino acids can affect the contacts with the lipid-membrane, can disturb the multimeric interactions, or can cause an empty space in the core of the protein (Table5). These disruptions differ according to the position of the amino acid, whether the residue is embedded or surface, and whether the mutant residue is larger or smaller than the wild. If one of the wild or mutant residues is glycine or proline, the flexibility and rigidity properties of these amino acids, respectively, may be affected by the mutation, thus locally affecting the conformation [18]。The charge differences between wild and mutant type amino acids are shown in Table5. Differences in charge between wild and mutant residues, such as being oppositely charged, having a charged residue when uncharged, or vice versa, can lead to different results. For example, the mutation can cause repulsion between the mutant residue and neighboring residues or loss of the charge of a buried residue [18]。The differences in hydrophobicity between residues are shown in Table5. If the hydrophobicity of the residues differs this can cause various situations such as loss of hydrophobic interactions with other molecules on the surface of the protein, affecting the hydrogen bond formation or the multimeric contacts [18]。的hydrophobicity value of amino acids is related to the side chains. In particular, it is a scale of how strongly the side chains are pushed out. If the hydrophobicity is positive, it indicates that this amino acid is not present in the aqueous medium. The negative value of hydrophobicity indicates a higher affinity of the amino acid toward water [19]。Finally, changes in the structure of the protein can be observed due to the decrease in the stabilization of the proteins. In addition, its solubility may be affected and protein activity may decrease or disappear completely [20]。Furthermore, the increase in stability may reduce unfolding rates which results in the formation of aggregates [21]。


In conclusion, the protein structure, function, and stabilization of SNPs known to cause amino acid substitutions in theGABRA1,GABRB1,andGABRB3genes, which are associated with some diseases processed in neurodevelopmental disorders, using bioinformatics tools in this study. As a result of the results obtained in our study, it is thought that it will benefit experimental studies and bioinformatics studies.

Availability of data and materials

The datasets used or analyzed during the current study are available from the corresponding author on reasonable request.



Single nucleotide polymorphisms


Neurodevelopmental disorders


Gamma-aminobutyric receptor


Gamma-aminobutyric acid receptor


Genome-wide association studies


Sorting Intolerant From Tolerant


Protein Variation Effect Analyzer


Protein Analysis Through Evolutionary Relationships


Non-synonymous SNVs


  1. Millan MJ (2013) An epigenetic framework for neurodevelopmental disorders: From pathogenesis to potential therapy. Neuropharmacology 68:1–82

    ArticleGoogle Scholar

  2. Castrén E, Elgersma Y, Maffei L, Hagerman R (2012) Treatment of neurodevelopmental disorders in adulthood. J Neurosci 32(41):14074–14079

    ArticlePubMedPubMed CentralGoogle Scholar

  3. Ehninger D, Li W, Fox K, Stryker MP, Silva AJ (2008) Reversing neurodevelopmental disorders in adults. Neuron 60(6):950–960

    ArticleCASPubMedPubMed CentralGoogle Scholar

  4. Reyes-Nava NG, Yu H-C, Coughlin CR, Shaikh TH, Quintana AM (2020) Abnormal expression of GABA A receptor subunits and hypomotility upon loss of gabra1 in zebrafish. Biol Open 1–9

  5. Zhu B, Chen C, Xue G, Lei X, Moyzis RK, Dong Q, Lin C (2014) The GABRB1 gene is associated with thalamus volume and modulates the association between thalamus volume and intelligence. Neuroimage 102:756–763

    ArticleCASPubMedGoogle Scholar

  6. Khair AM, Salvucci AE (2021) Phenotype expression variability in children with GABRB3 heterozygous mutations. Oman Med J 31–36

  7. Matukumalli LK, Lawley CT, Schnabel RD, Taylor JF, Allan MF, Heaton MP, O’Connell J, SS Moore, TPL Smith, TS Sonstegard, CP Van Tassell (2009) Development and characterization of a high density SNP genotyping assay for cattle. Plos One 1–13

  8. Butler JM (2012) Chapter 12—Single nucleotide polymorphisms and applications. In: Advanced topics in forensic DNA typing. Academic Press, pp 347–369

  9. Yavuz O, Marangoz Ö (2018) Farmakoloji ve Toksikolojide İn Siliko Yöntemlerin Kullanımı. Türkiye Klinikleri, pp 35–42

  10. Franz M, Rodriguez H, Lopes C, Zuberi K, Montojo J, Bader GD, Morris Q (2018) GeneMANIA update 2018. Nucleic Acids Res 46:60–64

    ArticleGoogle Scholar

  11. Szklarczyk D, Morris JH, Cook H, Kuhn M, Wyder S, Simonovic M, Santos A, Doncheva NT, Roth A, Bork P, Jensen LJ, von Mering C (2017) The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible. Nucleic Acids Res 362–368

  12. Ng PC, Henikoff S (2003) SIFT: predicting amino acid changes that affect protein function. Nucleic Acids Res 3812–3814

  13. Adzhubei I, Jordan DM, Sunyaev SR (2015) Predicting functional effect of human missense mutations

  14. Capriotti E, Altman RB, Bromberg Y (2013) Collective judgment predicts disease-associated single nucleotide variants. BMC Genomics 1–9

  15. Subbiah HV, Babu PR, Subbiah U (2020) In silico analysis of non-synonymous single nucleotide polymorphisms of human DEFB1 gene. Egypt J Med Human Genetics 21:1–9

    Google Scholar

  16. BitergeSüt B, Soytürk H (2021) Nonsynonymous variations of ion channel-related genes as risk factors in epilepsy. J Exp Clin Med 38(3):288–293

    ArticleGoogle Scholar

  17. Hernandez CC, Klassen TL, Jackson LG, Gurba K, Hu N, Noebels JL, Macdonald RL (2016) Deleterious rare variants reveal risk for loss of GABAA receptor function in patients with genetic epilepsy and in the general population. PloS One 11(9)

  18. Venselaar H, Beek TAHT, Kuipers RKP, Hekkelman ML, Vriend G (2010) Protein structure analysis of mutations causing inheritable diseases. An e-Science approach with life scientist friendly interfaces. BMC Bioinf 548

  19. Biro J (2006) Amino acid size, charge, hydropathy indices and matrices for protein structure analysis. Theor Biol Med Model 3:1–12

    ArticleGoogle Scholar

  20. Ashenberg O, Gong LI, Bloom JD (2013) Mutational effects on stability are largely conserved during protein evolution. Proc Natl Acad Sci 110(52):21071–21076

    ArticlePubMedPubMed CentralGoogle Scholar

  21. Broom A, Jacobi Z, Trainor K, Meiering EM (2017) Computational tools help improve protein stability but with a solubility tradeoff. J Biol Chem 292(35):14349–14361

    ArticleCASPubMedPubMed CentralGoogle Scholar

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MM: Data collection, in silico analysis, writing—original draft preparation. KÖF: Organizing the research, designing the research and methodology, writing (review and editing). ÖOE: Writing (review and editing), contributed with comments on methodology. KM Writing (review and editing) contributed with comments on methodology.

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Correspondence toÖmer Faruk Karasakal.

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Manaz, M., Karasakal, Ö.F., Özkan Oktay, al.In silico analysis of missense SNPs inGABRA1,GABRB1,andGABRB3genes associated with some diseases in neurodevelopmental disorders.Egypt J Med Hum Genet24, 67 (2023).

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