|Year : 2022 | Volume
| Issue : 2 | Page : 228-230
Virtual screening to identify pathogenic functional mutations in the exon of ACTN3 gene, which codes for masseter muscle, thereby affecting mandibular morphology
Vijayashree Priyadharsini Jayaseelan1, Ashwin Mathew George2, A Sumathi Felicita2, Paramasivam Arumugam1
1 Molecular Biology Lab, Cellular and Molecular Research Centre, Saveetha Dental College and Hospital, Saveetha Institute of Medical and Technical Sciences [SIMATS], Saveetha University, Chennai, Tamil Nadu, India
2 Department of Orthodontics, Saveetha Dental College and Hospital, Saveetha Institute of Medical and Technical Sciences [SIMATS], Saveetha University, Chennai, Tamil Nadu, India
|Date of Submission||21-Feb-2022|
|Date of Decision||26-Apr-2022|
|Date of Acceptance||18-May-2022|
|Date of Web Publication||22-Jun-2022|
A Sumathi Felicita
Department of Orthodontics, Saveetha Dental College and Hospital, Saveetha Institute of Medical and Technical Sciences [SIMATS], Saveetha University, 162, Poonamallee High Road, Chennai - 600 077, Tamil Nadu
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Aim: To determine if In silico methods can be used to identify pathogenic non-synonymous variants in the ACTN3 (alpha actinin 3) alpha actinin gene that encodes for alpha actinin 3 three protein employing computational tools. Materials and Methods: In silico methods of detecting pathogenic variants were initiated by identifying 854 reported non-synonymous mutations in the ACTN3 gene from the Ensembl database. The non-synonymous variants of ACTN3-201 (transcript ID: ENST00000502692.5) were derived from the Ensembl database. Variants found to be pathogenic were curated using SIFT tool (The Sorting Intolerant From Tolerant), PolyPhen2 (Polymorphism Phenotyping v2), and PROVEAN (Protein Variation Effect Analyzer). The panel of curated variants was analyzed for protein stability based on substituting existing amino acid residue with a variant encoded amino acid using IMutant 3.0. Results: Among 854 variants reported in the ACTN3 gene, 26 were found to be harmful, and possibly pathogenic. The SIFT tool identified 15 variants to be highly intolerant, PolyPhen2 identified two other variants as possibly damaging, and PROVEAN predicted two variants to be highly harmful. Finally, IMutant 3.0 showed that one (single nucleotide polymorphism) resulted in decreased stability of the ACTN3 protein. Conclusions: Applying in silico approaches can help researchers identify variants exhibiting putative association with the disease phenotype.
Keywords: Alpha-actinin, malocclusion, mutation, non-synonymous, polymorphism
|How to cite this article:|
Jayaseelan VP, George AM, Felicita A S, Arumugam P. Virtual screening to identify pathogenic functional mutations in the exon of ACTN3 gene, which codes for masseter muscle, thereby affecting mandibular morphology. J Indian Acad Oral Med Radiol 2022;34:228-30
|How to cite this URL:|
Jayaseelan VP, George AM, Felicita A S, Arumugam P. Virtual screening to identify pathogenic functional mutations in the exon of ACTN3 gene, which codes for masseter muscle, thereby affecting mandibular morphology. J Indian Acad Oral Med Radiol [serial online] 2022 [cited 2022 Jun 29];34:228-30. Available from: https://www.jiaomr.in/text.asp?2022/34/2/228/347931
| Introduction|| |
The ACTN3 (alpha actinin 3) R577X genotype is associated with altered mandibular morphology. The ACTN3 gene codes for actinin alpha three protein, whose isoforms are located on the sarcomeres, enabling skeletal muscles' stabilization and contraction. The variant produced fast type II fibers with a small diameter in the masseter muscles. Recent studies have also reiterated the association of ACTN3 gene polymorphisms with phenotypes such as condyle modeling and temporomandibular disorders (TMD), and skeletal malocclusion. The aim of this was to identify pathogenic non-synonymous variants in the ACTN3 gene that encodes for actinin alpha three protein, employing computational tools.
| Materials and Methods|| |
The missense mutations were collected from the transcript of the ACTN3 gene (ACTN3-201 (transcript ID: ENST00000502692.5)) from the Ensembl database. The SIFT (Sorting Intolerant From Tolerant), PolyPhen-2 (Polymorphism Phenotyping v2), and PROVEAN (Protein Variation Effect Analyzer) tools were used to identify the pathogenic variants in the gene selected. There were around 854 non-synonymous variants identified in the transcript, of which 26 were found to be harmful, and possibly pathogenic as assessed by SIFT and Polyphen
The SIFT tool predicts tolerated and deleterious mutations at every position of the query sequence. A tolerance index less than 0.05 was considered to be intolerant or deleterious. Scores greater than 0.05 were considered tolerated. The sensitivity and specificity of SIFT, as assessed by UniRef90, were found to be in the range of 79–92% and 36–100%.
PolyPhen-2 predicts the possible outcome of amino acid substitutions on the stability and function of human proteins using structural and comparative evolutionary considerations. The Polyphen scores have been classified as benign (< 0.452), possibly damaging (0.452–0.957 and probably damaging (> 0.957). The overall accuracy and specificity of PolyPhen were 80% and 69%, respectively.
PROVEAN predicts whether an amino acid substitution or indel impacts the biological function of a protein. A delta alignment score is computed for the given protein sequence. If the score is equal to or below the threshold (-2.5), the variant is deleterious. If the score is above the threshold, it will exhibit a neutral effect. The sensitivity, specificity, and accuracy returned the following values 78%, 79%, and 79%.
Protein stability analysis
I-Mutant v3.0 predictions are based on the protein sequence. The predictions were classified into three classes: neutral mutation (−0.5≤ DDG ≥0.5 kcal/mol), large decrease (< −0.5 kcal/mol), and a large increase (>0.5 kcal/mol). The free energy change (DDG) predicted by I-Mutant 3.0 is based on the difference between unfolding Gibbs free energy change of mutant and native protein (kcal/mol). The I-Mutant software predicts with an accuracy of 80% depending on the structure and 77% on sequence information.
The overall sensitivity of the above tools is around 46–70%. Further in vitro validation is required to derive an association between the putative pathogenic single nucleotide polymorphisms identified and the disease trait in a specific population.
| Results|| |
The scores within the range of 0–0.05 were considered harmful in the case of SIFT and a score of 0.85–1 was considered possibly damaging in the case of PolyPhen-2 analysis. This curation process left us with twenty-six damaging missense variants, further subjected to investigation with PROVEAN. Taken together, rs1227197706 was one polymorphism where all four predictions revealed a highly pathogenic outcome.
| Discussion|| |
Genetic, environmental, and psychological factors are considered etiological factors of malocclusion. Abnormal muscle activity may influence the development of malocclusion.
ACTN2 and 3 are genes that encode alpha-actinin, a protein expressed only in type-II muscle fibers. The gene is located on the long arm of chromosome 11 (11q13-14). The protein is highly conserved with 901 amino acid residues.
A study on the association of ACTN3 polymorphisms (rs678397, rs1671064, and rs1815739) with bruxism in children showed a statistically significant association for all three polymorphisms analyzed with co-dominant and recessive models. A recent study compared ACTN3 and ENPP1(ectonucleotide pyrophosphatase/phosphodiesterase 1) genotypes with mandibular condylar modeling, TMDs, and craniofacial asymmetry. Three polymorphisms of the ACTN3 gene viz, rs1671064 (missense; P = 0.02), rs1815739 (R577X nonsense; P = 0.00), and rs678397 (intronic; P = 0.04) were found to produce a significant difference between the control and case groups. The study is suggestive of the fact that genetic components serve as potential contributors to craniofacial abnormalities.
The screening of multiple SNP markers reported in a single gene to demonstrate its association with the disease phenotype is a herculean task for the researchers. Hence, computational tools are used to analyze and identify those pathogenic variants which could be associated with disease traits. Despite several advantages related to computational approaches, one of the major limitations is that not all the variants exhibiting pathogenicity scores within silico models behave the same way in the biological environment. Hence, the validation of each of the pathogenic SNP markers is a vital component to deduce the gene-disease interactions.
| Conclusion|| |
The present study provides a curated SNP panel of pathogenic variants in the ACTN gene, which can be further assessed to determine their possible association with craniofacial abnormalities, including malocclusion.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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