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Title: | In silico analysis of missense variants of the C1qA gene related to infection and autoimmune diseases |
Authors: | Behairy, Mohammed Y. Abdelrahman, ALi A. Abdallah, Hoda Y. Ibrahim, Emad El-Deen A. Sayed, Anwar A. Azab, Marwa M. |
Keywords: | C1qA In silico Infection SLE SNP |
Issue Date: | 2022 |
Publisher: | Journal of Taibah University Medical Sciences |
Series/Report no.: | Original Article;1074-1082 |
Abstract: | Objectives: C1q is a key activator of the classical pathway of the complement system and exerts consequences relating to opsonization and phagocytosis. The C1qA gene is one of three genes encoding the C1q molecule. Defects in C1q, and especially in C1qA, have been linked to an increased susceptibility to infection, sepsis, and systemic lupus erythematosus. These defects could arise from missense single nucleotide polymorphisms (SNPs) and their deleterious impacts on protein structure and function. Thus, identifying highrisk missense SNPs in C1qA has become a necessity if we are to identify appropriate measures for prevention and management of affected patients. Methods: A comprehensive in silico study was conducted to screen the 184 missense SNPs in the C1qA gene using different tools with different algorithms and approaches. We investigated the impact of SNPs on protein function, stability, and structure. In addition, we identified the location of the SNPs on protein domains, secondary structure alignment, and the phylogenetic conservation of their positions. Results: Of the 184 missense SNPs, 10 SNPs were predicted to be the most damaging to protein function and structure. Conclusion: Ten missense SNPs were predicted to have the highest risk of damaging protein function and structure, thus leading to infection, sepsis, and systemic lupus erythematosus. These 10 SNPs constitute the best candidates for further experimental investigations. |
URI: | http://localhost:8080/xmlui/handle/123456789/7387 |
ISSN: | 1658-3612 |
Appears in Collections: | Vol 17 No 6 (2022) |
Files in This Item:
File | Description | Size | Format | |
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1074-1082.pdf | 1074-1082 | 2.11 MB | Adobe PDF | View/Open |
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