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Integrated studies of structural biology, medicinal chemistry, and machine learning applied to the discovery of lead compounds for Malaria

Grant number: 22/13160-5
Support Opportunities:Scholarships in Brazil - Doctorate (Direct)
Effective date (Start): October 01, 2023
Effective date (End): July 31, 2027
Field of knowledge:Physical Sciences and Mathematics - Chemistry - Organic Chemistry
Principal Investigator:Rafael Victorio Carvalho Guido
Grantee:Gabriela Silva de Oliveira
Host Institution: Instituto de Física de São Carlos (IFSC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
Associated research grant:13/07600-3 - CIBFar - Center for Innovation in Biodiversity and Drug Discovery, AP.CEPID

Abstract

Malaria is an infectious disease caused by protozoa of the genus Plasmodium ssp. Despite significant success in fighting the disease over the past two decades, nearly half of the world's population was at risk of contracting malaria and there were an estimated 241 million cases and 627,000 deaths due to malaria in 2020. In the search for new candidates for antimalarial drugs, the modulation of the signaling pathways mediated by protein kinases has been explored as a strategy to inhibit the development of the parasite and treat the infection. In this sense, we selected the protein kinases PfPI4K, PfPKG and PfCLK3, validated molecular targets for the discovery of new antimalarials, for structural determination and the discovery of inhibitors as lead candidates for malaria. These enzymes are important biomolecules involved in the metabolic and signaling pathways and essential for the survival and development of the parasite. Moreover, PfPI4K, PfPKG, and PfCLK3 show differences structural features when compared to human homologous enzymes that indicate opportunities for the discovery of selective inhibitors for the parasite enzyme.The strategy employed for the discovery of new inhibitors as lead candidates includes integrated studies of Structural Biology, Biochemistry, Cell Biology, Structure-Activity Relationship Studies (SAR), Machine Learning (ML) and Structure-Based Drug Design (SBDD). The candidate molecules as inhibitors will be prospected by virtual screening campaigns of the ZINC database and from experimental screenings of the compounds collection of the Center for Research and Innovation in Biodiversity and Drugs (CIBFar-CEPID-FAPESP). The compounds that show significant inhibition of the enzymes (IC50 < 50 ¼M) and parasite growth (IC50Pf < 50 ¼M) with promising selectivity indices (SI > 10) will be selected for SAR studies for the optimization of the biological properties aiming the discovery of new lead candidates for malaria.Our laboratories at CIBFar-CEPID have adequate facilities and equipment to carry out all the experimental and computational strategies proposed herein. Moreover, our research group is a Center of Excellence of the non-profit organization Medicines for Malaria Venture (MMV) for the assessment of new drug candidates for malaria. (AU)

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