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Molecular dynamics and protein frustration analysis of human fused in Sarcoma protein variants in Amyotrophic Lateral Sclerosis type 6: An In Silico approach.

ABSTRACT: Amyotrophic lateral sclerosis (ALS) is the most frequent adult-onset motor neuron disorder. The disease is characterized by degeneration of upper and lower motor neurons, leading to death usually within five years after the onset of symptoms. While most cases are sporadic, 5%-10% of cases can be associated with familial inheritance, including ALS type 6, which is associated with mutations in the Fused in Sarcoma (FUS) gene. This work aimed to evaluate how the most frequent ALS-related mutations in FUS, R521C, R521H, and P525L affect the protein structure and function. We used prediction algorithms to analyze the effects of the non-synonymous single nucleotide polymorphisms and performed evolutionary conservation analysis, protein frustration analysis, and molecular dynamics simulations. Most of the prediction algorithms classified the three mutations as deleterious. All three mutations were predicted to reduce protein stability, especially the mutation R521C, which was also predicted to increase chaperone binding tendency. The protein frustration analysis showed an increase in frustration in the interactions involving the mutated residue 521C. Evolutionary conservation analysis showed that residues 521 and 525 of human FUS are highly conserved sites. The molecular dynamics results indicate that protein stability could be compromised in all three mutations. They also affected the exposed surface area and protein compactness. The analyzed mutations also displayed high flexibility in most residues in all variants, most notably in the interaction site with the nuclear import protein of FUS.

SUBMITTER: Bonet LFS

PROVIDER: S-EPMC8480726 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Amyotrophic Lateral Sclerosis (ALS) is the most frequent motor neuron disorder, with a significant social and economic burden. ALS remains incurable, and the only drugs approved for its treatments confers a survival benefit of a few months for the patients. Missense mutations in superoxide dismutase 1 (SOD1), a major cytoplasmic antioxidant enzyme, has been associated with ALS development, accounting for 23% of its familial cases and 7% of all sporadic cases. This work aims to characterize in silico the structural and functional effects of SOD1 protein variants. Missense mutations in SOD1 were compiled from the literature and databases. Twelve algorithms were used to predict the functional and stability effects of these mutations. ConSurf was used to estimate the evolutionary conservation of SOD1 amino-acids. GROMACS was used to perform molecular dynamics (MD) simulations of SOD1 wild-type and variants A4V, D90A, H46R, and I113T, which account for approximately half of all ALS-SOD1 cases in the United States, Europe, Japan, and United Kingdom, respectively. 233 missense mutations in SOD1 protein were compiled from the databases and literature consulted. The predictive analyses pointed to an elevated rate of deleterious and destabilizing predictions for the analyzed variants, indicating their harmful effects. The ConSurf analysis suggested that mutations in SOD1 mainly affect conserved and possibly functionally essential amino acids. The MD analyses pointed to flexibility and essential dynamics alterations at the electrostatic and metal-binding loops of variants A4V, D90A, H46R, and I113T that could lead to aberrant interactions triggering toxic protein aggregation. These alterations may have harmful implications for SOD1 and explain their association with ALS. Understanding the effects of SOD1 mutations on protein structure and function facilitates the design of further experiments and provides relevant information on the molecular mechanism of pathology, which may contribute to improvements in existing treatments for ALS.

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Molecular dynamics and protein frustration analysis of human fused in Sarcoma protein variants in Amyotrophic Lateral Sclerosis type 6: An In Silico approach.

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