Estudos de CADD na busca de fenilpropanoides multialvos para o tratamento da epilepsia

• Ano de defesa: 2023
• Autor(a) principal: Rodrigues, Teresa Carolliny Moreira Lustoza
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal da Paraíba; Brasil; Farmacologia; Programa de Pós-Graduação em Produtos Naturais e Sintéticos Bioativos; UFPB
• Palavras-chave em Português: Epilepsia; Fenilpropanoides; Multialvos; AMPA; GABAA; ADMET; Docking molecular; Modelos de predição; Epilepsy; Phenylpropanoids; Multi-targets; Molecular docking; Prediction models; CNPQ::CIENCIAS BIOLOGICAS::FARMACOLOGIA
• Link de acesso: https://repositorio.ufpb.br/jspui/handle/123456789/30360

Epilepsy is a neurological disease, characterized by hyperactivity of the central nervous system. Epileptic seizures are caused by an imbalance of excitatory and inhibitory neurotransmission. The treatment of epileptic seizures consists of antiepileptic drugs (AEDs) that act through different mechanisms of action. Many patients make use of polypharmacy, as they need more than one AEDs, which are endowed with side effects that compromise adherence and the quality of treatment. There are still patients who have refractory epilepsy, in which drugs are no longer able to control epileptic seizures. Medicinal plants have been used for centuries to treat numerous diseases, including neurological ones, empirically and stand out due to the presence of secondary metabolites, among them, phenylpropanoids, which have different biological activities. This work focused on analyzing, through the in silico approach, the use of phenylpropanoids as possible therapeutic molecules of pharmacological targets with multi-target action for the treatment of epilepsy, through methods of ligand-based virtual screening (LBVS), chemometrics, prediction, and molecular docking. In the experimental approach, a bank was created with 468 phenylpropanoid molecules found in the literature. Then, the LBVS prediction techniques were applied with models developed for the targets: alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA), T-type voltage-dependent calcium channel (CaV), acid gamma-aminobutyric acid type A (GABAA), gamma-aminobutyric acid transporter type 1 (GAT -1), voltage-gated potassium channel of the Q family (KCNQ), voltage-gated sodium channel (NaV), and N-methyl D -aspartate (NMDA). Then, the molecules, that presented the best parameters of absorption, distribution, metabolism, excretion, and toxicity (ADMET) and also ability to cross the blood-brain barrier, were analyzed and selected. Finally, molecular docking was performed with the best phenylpropanoids using two scoring functions: Moldock score and PLANTS score, and binding energies were reached. The results showed that, after the virtual screening, the TR430 molecule had an oral absorption of 99.03%, it did not violate any of the five Linpiski rules, therefore it has good bioavailability; it has also shown no toxicity, either of the molecule or its metabolites, in the evaluated parameters and it can cross the blood-brain barrier. In molecular docking, it presented a consensus score for AMPA and GABAA of -260.184 kcal/mol and -254.422 kcal/mol, respectively. Therefore, TR430 is a multi-target compound with potential antiepileptic activity, and future studies should be carried out to confirm the predictions obtained in silico.