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Computational analysis of deleterious missense mutations in aspartoacylase that cause Canavan's disease
K Sreevishnupriya1, P Chandrasekaran, A Senthilkumar
1Bioinformatics Division, School of Biosciences and Technology, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India.
Abstract:
In this work, the most detrimental missense mutations of aspartoacylase that cause Canavan's disease were identified computationally and the substrate binding efficiencies of those missense mutations were analyzed. Out of 30 missense mutations, I-Mutant 2.0, SIFT and PolyPhen programs identified 22 variants that were less stable, deleterious and damaging respectively. Subsequently, modeling of these 22 variants was performed to understand the change in their conformations with respect to the native aspartoacylase by computing their root mean squared deviation (RMSD). Furthermore, the native protein and the 22 mutants were docked with the substrate NAA (N-Acetyl-Aspartic acid) to explain the substrate binding efficiencies of those detrimental missense mutations. Among the 22 mutants, the docking studies identified that 15 mutants caused lower binding affinity for NAA than the native protein. Finally, normal mode analysis determined that the loss of binding affinity of these 15 mutants was caused by altered flexibility in the amino acids that bind to NAA compared with the native protein. Thus, the present study showed that the majority of the substrate-binding amino acids in those 15 mutants displayed loss of flexibility, which could be the theoretical explanation of decreased binding affinity between the mutant aspartoacylases and NAA.
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