Estudos quimioinformáticos da família Asteraceae na busca de estruturas com potencial atividade contra doenças parasitárias negligenciadas

• Ano de defesa: 2024
• Autor(a) principal: Acevedo, Chonny Alexander Herrera
• 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: Asteraceae - Leishmaniose; Asteraceae - Estudos quimioinformáticos; Leishmania; Asteraceae - Metabolitos secundários; Doenças tropicais negligenciadas; Acoplamento molecular; Asteraceae; Virtual screening; Secondary metabolites; Machine learning; Neglected tropical diseases; Molecular docking; CNPQ::CIENCIAS BIOLOGICAS::FARMACOLOGIA
• Link de acesso: https://repositorio.ufpb.br/jspui/handle/123456789/32413

Leishmaniasis, classified as a Neglected Tropical Disease (NTD), poses a significant challenge to public health in the Americas. The cutaneous form (CL) of the disease has a considerable impact in South America, with Brazil, Colombia, and Peru among the nine countries reporting 85% of annual cases worldwide. Brazil also faces a significant burden of Visceral Leishmaniasis, the most lethal form of the disease. Despite control efforts in recent years, transmission persists in impoverished regions with poor hygiene conditions, facilitating contact with disease vectors. Current treatments, such as antimonial compounds, pentamidine isethionate, miltefosine, and liposomal amphotericin B, offer therapeutic options but fail to eradicate the infection and present various adverse events. In this context, there is a need to develop new chemotherapies against the different clinical forms of leishmaniasis. Considering the rich biodiversity of Colombia and Brazil, the search for secondary metabolites with leishmanicidal properties becomes relevant. The botanical family Asteraceae, with its abundance of species (over 32,000) and a wide range of secondary metabolites, including terpenoids and flavonoids, emerges as a promising source of bioactive molecules. Currently, the selection of molecules with potential biological activity is supported by computational tools, demonstrating substantial benefits in terms of cost and time compared to classical approaches like High-throughput Screening. This approach allows for a more efficient exploration of natural compounds for the development of new treatments against leishmaniasis. This doctoral work aimed to conduct chemoinformatics studies of the Asteraceae family to find new structures with therapeutic potential against the various clinical forms of leishmaniasis. The study begins with a chapter dedicated to the paradigms of drug discovery based on the structures of the therapeutic target. Next, in Chapter II, a review of various studies that used computational tools to examine compounds identified in the Asteraceae family in the search for potential drug candidates against Leishmania is conducted, highlighting the use of databases as a key tool in the search for potential leishmanicidal molecules. Subsequent chapters focus on computational studies, using different virtual screening approaches and various classes of secondary metabolites present in Asteraceae to select potential leishmanicidal compounds. Chapter III uses a library of sesquiterpene lactones from SistematX to select potential leishmanicidal compounds, employing a combined virtual screening approach based on ligand and receptor structure, identifying structures with inhibitory potential for multiple targets. Chapter IV, divided into two parts, evaluates the inhibition of Pteridine reductase 1 (PTR1) and dihydrofolate reductase-thymidylate synthase (DHFR-TS), two crucial enzymes for the metabolism of these trypanosomatid parasites. Two compounds with dual inhibitory activity for multiple Leishmania species were identified from a library of 360 diterpenoids. Finally, in Chapter V, hybrid C6C3 butyrolactone lignans were selected as inhibitors of LmDHFR-TS from a library of 314 cinnamic acid derivatives, validating the computational models through in vitro assays with the recombinant DHFR-TS enzyme.