Last Updated: 31/07/2024
Integrated studies of structural biology, medicinal chemistry and machine learning applied to the discovery of lead compounds for malaria
Objectives
*Original in Portuguese: Estudos integrados de biologia estrutural, química medicinal e aprendizado de máquina aplicados na descoberta de compostos líderes para Malária
This project aims to use a combination of structural biology, medicinal chemistry, and machine learning to discover new lead compounds for treating malaria.
Malaria is an infectious disease caused by protozoa of the genus Plasmodium ssp.. Despite significant success in combating the disease over the last two decades, in 2020, almost half of the world’s population was at risk of contracting malaria and there were an estimated 241 million of cases and 627,000 deaths due to malaria. In the search for new candidates for antimalarial drugs, the modulation of signaling pathways mediated by protein kinases has been explored as a strategy to inhibit the development of the parasite and combat infection. In this sense, selected protein kinases were PfPI4K, PfPKG and PfCLK3, validated as molecular targets for the discovery of new antimalarials, for structural elucidation and the discovery of inhibitors as candidate lead compounds for malaria. These enzymes are important biomolecules involved in metabolic and signaling routes essential for the survival and development of the parasite. Furthermore, PfPI4K, PfPKG and PfCLK3 present structural characteristics with significant differences when compared to human homologous enzymes that indicate opportunities for the discovery of selective inhibitors for the parasite enzyme. will include integrated studies of Structural Biology, Biochemistry, Cell Biology, Structure Activity Relationship Studies (SAR), Machine Learning (ML) and Structure-Based Drug Design (SBDD). The candidate inhibitor molecules will come from virtual screenings of the ZINC database and experimental screenings of the compound collection of the Center for Research and Innovation in Biodiversity and Drugs (CIBFar-CEPID-FAPESP). Compounds that show significant inhibition of enzymes (IC50 < 50 ¼M) and parasite growth (IC50Pf < 50 ¼M) and show promising selectivity indices (SI > 10) will be selected for SAR studies to optimize biological properties aiming to the discovery of new candidate lead compounds for malaria. Laboratories at CIBFar-CEPID have adequate facilities and equipment to carry out all experimental and computational steps proposed in this project.
Oct 2023 — Jul 2027
