Barbosa, Euzébio GuimarãesPinto, Samara Beatriz de Abreu2024-07-052024-07-052024-06-10PINTO, Samara Beatriz de Abreu. Plataforma integrada para pesquisa e análise de compostos promissores para o tratamento da leishmaniose: LeishMolDB. Orientador: Euzébio Guimarães Barbosa. 2024. 33 f. Trabalho de Conclusão de Curso (Graduação em Farmácia) - Departamento de Farmácia, Universidade Federal do Rio Grande do Norte, Natal, RN, 2024.https://repositorio.ufrn.br/handle/123456789/58609Open-access molecular databases play a crucial role in the evolution of medicinal chemistry. However, the development of new drugs remains a challenge, especially for leishmaniasis, whether visceral or cutaneous. The limited efficacy and toxicity of existing treatments, along with the lack of interest from the pharmaceutical industry due to high costs and low financial returns, highlight the need for new research approaches for this neglected disease. In this context, the LeishMolDB project was developed as an accessible tool to facilitate the discovery of new compounds potentially active against the amastigote forms of Leishmania, allowing the assessment of their viability as future drugs. The selection process for the molecular structures began with a literature review of articles that included IC50 information against amastigotes, selecting the most active compounds. These molecules were designed, archived in tables, converted to 3D SDF format, and then optimized. The implementation of the web platform started with the development of the front-end using HTML, JavaScript, and Tailwind CSS. For the back-end, the Python programming language was employed, with an emphasis on the RDKit library, widely used in computational chemistry. The platform offers five intuitive interfaces that allow users to explore the stored molecules and associated molecular data, such as SMILE, molecular weight, log P, hydrogen bond donors and acceptors, and TPSA. Additionally, it allows the download of structures and ligand-based virtual screening using the Tanimoto coefficient. Thus, LeishMolDB stands out as an important tool, with manually verified 3D structures, aimed at collaborating with the scientific community in the development of new drugs. The continuous sharing of information and updates aims to reduce resources and costs associated with pharmaceutical research.Attribution-NonCommercial-NoDerivs 3.0 Brazilhttp://creativecommons.org/licenses/by-nc-nd/3.0/br/LeishmanioseQuímica MedicinalTriagem VirtualBancos de DadosDesenvolvimento de FármacosbachelorThesisCNPQ::CIENCIAS DA SAUDE::FARMACIA