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bioRxiv · 10.1101/2021.10.08.463616

Prediction and Expression Analysis of Deleterious Nonsynonymous SNPs of Arabidopsis ACD11 Gene by Combining Computational Algorithms and Molecular Docking Approach

Abstract

Accelerated cell death 11 (ACD11) is an autoimmune gene that suppresses pathogen infection in plants by preventing plant cells from becoming infected by any pathogen. This gene is widely known for growth inhibition, premature leaf chlorosis, and defense-related programmed cell death (PCD) in seedlings before flowering in Arabidopsis plant. Specific amino acid changes in the ACD11 proteins highly conserved domains are linked to autoimmune symptoms including constitutive defensive responses and necrosis without pathogen awareness. The molecular aspect of the aberrant activity of the ACD11 protein is difficult to ascertain. The purpose of our study was to find the most deleterious mutation position in the ACD11 protein and correlate them with their abnormal expression pattern. Using several computational methods, we discovered PCD vulnerable single nucleotide polymorphisms (SNPs) in ACD11. We analysed the RNA-Seq data, identified the detrimental nonsynonymous SNPs (nsSNP), built genetically mutated protein structures and used molecular docking to assess the impact of mutation. Our results demonstrated that the A15T and A39D variations in the GLTP domain were likely to be extremely detrimental mutations that inhibit the expression of the ACD11 protein domain by destabilizing its composition, as well as disrupt its catalytic effectiveness. When compared to the A15T mutant, the A39D mutant was more likely to destabilize the protein structure. In conclusion, these mutants can aid in the better understanding of the vast pool of PCD susceptibilities connected to ACD11 gene GLTP domain activation.

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BibTeXRIS

Rifat, M. H., Ahmed, J., Ahmed, M., Ahmed, F., Gulshan, A., Hasan, M.. 2021-10-09. Prediction and Expression Analysis of Deleterious Nonsynonymous SNPs of Arabidopsis ACD11 Gene by Combining Computational Algorithms and Molecular Docking Approach. https://doi.org/10.1101/2021.10.08.463616

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