Design racional de fármacos auxiliado por computador com vistas ao direcionamento da síntese de novos derivados híbridos tiofeno-indólicos para o tratamento da leishmaniose

• Ano de defesa: 2020
• Autor(a) principal: Félix, Mayara Barbalho
• Tipo de documento: Tese
• 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: QSAR; Design de drogas; 2-amino-tiofeno; Indol; Atividade anti-Leishmanial; Leishmania (spp.); Drug design; 2-aminothiophene; Anti-Leishmanial activity; CNPQ::CIENCIAS BIOLOGICAS::FARMACOLOGIA
• Link de acesso: https://repositorio.ufpb.br/jspui/handle/123456789/20276

Chemoinformatics is presented through a range of applications in the field of drug design in order to contribute to the identification of new compounds against a variety of diseases. Among these, leishmaniasis, whose current treatment requires improvement because it has several side effects and does not have the desired efficacy. With this, this study aimed at the planning of new molecules derived from the indolic 2-aminothiophene using computational tools, synthesis and biological evaluation in order to understand its effectiveness against Leishmania amazonensis (sp.). In addition, to predict the activity of these new compounds against three other Leishmania species, using the virtual platform Chembench. For this, based on the chemical structure of the thiophene-indole hybrids, regression models were constructed and molecular docking was performed. The data obtained were used as the basis for the design of 92 new molecules with pIC50, with six compounds selected for synthesis and for carrying out biological tests (leishmanicidal activity and cytotoxicity). In parallel, starting from databases of virtual plantforms (ChemBl and PubMed), qualitative prediction models were built in the Chembench, so that the activities of the new derivatives were predicted against the species: L. donovani, L. infantum and L braziliensis, using descriptors CDK and DRAGON 7 and the algorithms Random Forest (RF) and kNN (MuDRA). Thus, through the prediction models and molecular docking, one can infer the characteristics that could have a positive influence on the leishmanicidal activity of the planned compounds. Of the synthesized compounds, one third had promising anti-Leishmania activities with IC50 ranging from 2.16 and 2.97 μM (against promastigote forms) and 0.9 and 1.71 μM (against amastigote forms), with selectivity indexes (SI) greater than those of the reference drugs used and presenting low cytotoxicity against macrophages. From the models obtained in the Chembench. Two structures were selected with good prediction for two species (37 and 87) and one in common with the three species studied (42), a structure similar to indole thiophene derivatives already biologically evaluated. These results demonstrate the ability of rational drug planning based on the Quantitative Structure-Activity Relationship (QSAR) to predict molecules with promising leishmanicidal potential and confirm the potential of thiophene-indole hybrids as potential new leishmanial agents.