Assessing the effects of PMM2 variants on protein stability

Phosphomannomutase 2 deficiency, PMM2-CDG, is the most frequent disorder of protein N-glycosylation. It is an autosomal recessive disease with a broad clinical and biochemical phenotype. Trying to predict the impact of novel variants is often a challenge due to the high number of variants and the di...

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Bibliographic Details
Published in:Molecular genetics and metabolism 2021-12, Vol.134 (4), p.344-352
Main Authors: Quelhas, D., Carneiro, J., Lopes-Marques, M., Jaeken, J., Martins, E., Rocha, J.F., Teixeira Carla, S.S., Ferreira, C.R., Sousa, S.F., Azevedo, L.
Format: Article
Language:English
Subjects:
Computational simulation
Deleterious variants
Molecular Dynamics Simulation
Mutation, Missense
N-glycosylation
Phosphotransferases (Phosphomutases) - chemistry
Phosphotransferases (Phosphomutases) - genetics
PMM2
Protein Conformation
Protein Multimerization
Protein Stability
Structural analyses
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Summary:Phosphomannomutase 2 deficiency, PMM2-CDG, is the most frequent disorder of protein N-glycosylation. It is an autosomal recessive disease with a broad clinical and biochemical phenotype. Trying to predict the impact of novel variants is often a challenge due to the high number of variants and the difficulty to establish solid genotype-phenotype correlations. A potential useful strategy is to use computational chemistry calculations as a tool from which relevant information on the structural impact of novel variants may be deduced. Here we present our analyses based on four well-known PMM2 deleterious variants (p.(Leu32Arg), p.(Asp65Tyr), p.(Phe119Leu), p.(Arg141His)) and the polymorphic p.(Glu197Ala) for which we have predicted the effect on protein stability. Our work predicts the effect of different amino acid residues on the conformation and stability of PMM2. These computational simulations are, therefore, an extremely useful methodology which, in combination with routinely used in silico methods of pathogenicity prediction, may help to reveal the structural impact of novel variants at the protein level, potentially leading to a better understanding of target biological molecules.
ISSN:1096-7192
1096-7206
DOI:10.1016/j.ymgme.2021.11.002