Comprehensive in silico analysis of the TDP-43 protein variants related to Amyotrophic Lateral Sclerosis and Frontotemporal Dementia: Abrangente na análise silicoanalítica das variantes proteicas TDP-43 relacionadas à Esclerose Lateral Amiotrófica e Demência Frontotempor

• Autor(a) principal: Loureiro, Juliana Pereira
• Data de Publicação: 2022
• Outros Autores: Pereira, Gabriel Rodrigues Coutinho, Bloise, Leonardo Cardoso da Silva, Salerno, José Alexandre de Carvalho, Silvestre, Vinicius Abrantes, de Mesquita, Joelma Freire
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Revista Veras
• Texto Completo: https://ojs.brazilianjournals.com.br/ojs/index.php/BRJD/article/view/51249
• topic: Amyotrophic lateral sclerosis; frontotemporal dementia; in silico analysis

Amyotrophic lateral sclerosis (ALS) is a highly disabling neurodegenerative disorder characterized by the progressive loss of voluntary motor activity. ALS is currently the most frequent adult-onset motor neuron disorder, which is associated with a major economic burden. Two drugs have already been approved to treat ALS, but they confer a limited survival benefit. In turn, frontotemporal dementia (FTD) is an early-onset and fatal dementia characterized by deficits in behavior, language, and executive function. FTD is the most frequent cause of pre-senile dementia after Alzheimer's. Currently, FTD has no cure and the available treatments are merely symptomatic. Missense mutations in TDP-43, a nuclear RNA/DNA-binding protein, are among the main causes associated with ALS and FTD. Nonetheless, most of these mutations are not yet characterized. To date, no complete three-dimensional structure has already been determined for TDP-43. In this work, we characterized the impact of missense mutations in TDP-43 using prediction algorithms, evolutionary conservation analysis, and molecular dynamics simulations (MD). We also performed structural modeling and validation of the TDP-43 protein. Two hundred and seven TDP-43 mutations were compiled from the databases and literature. The predictive analysis pointed to a moderate rate of deleterious and destabilizing mutations. Furthermore, most mutations occur at evolutionarily variable positions. Combining the predictive analyses into a penalty system, our findings suggested that the uncharacterized mutations Y43C, D201Y, F211S, I222T, K224N, A260D, P262T, and A321D are considered the most-likely deleterious, thus being important targets for future investigation. This work also provided an accurate, complete, and unprecedented three-dimensional structure for TDP-43 that can be used to identify and optimize potential drug candidates. At last, our MD findings pointed to a noticeable flexibility increase in functional domains upon K263E, G335D, M337V, and Q343R variants, which may cause non-native interactions and impaired TDP-43 recognition, ultimately leading to protein aggregation.