QSAR-driven discovery of bioactive compounds against CYP51 of Trypanosoma cruzi

• Grant number: 22/13442-0
• Support Opportunities: Scholarships abroad - Research Internship - Scientific Initiation
• Start date: January 15, 2023
• End date: April 14, 2023
• Field of knowledge: Health Sciences - Pharmacy
• Principal Investigator: Elizabeth Igne Ferreira
• Grantee: Erick Tavares Marcelino Alves
• Supervisor: Alexander Tropsha
• Host Institution: Faculdade de Ciências Farmacêuticas (FCF). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Institution abroad: University of North Carolina at Chapel Hill (UNC), United States
• Associated to the scholarship: 21/04778-2 - Potentially active anti-chagas disease: design and synthesis of molecular hybrid of enzymes superoxide dismutase and CYP51 with nitric oxide releasing group, BP.IC

Abstract

Chagas disease (CD) is a prevalent anthropozoonosis in Latin America. Usually, this disease affects nearly 6-7 million people and kills around ten thousand annually. CD is caused by the parasite Trypanosoma cruzi, which is mainly transmitted by an insect vector popularly known as the kissing bug. Two drugs, benznidazole and nifurtimox, are currently approved for therapeutic use. Unfortunately, these have low efficacy in the early stages of CD and exhibit gastrointestinal and neurological toxicity. Moreover, drug resistance is a significant challenge given the great variety of existing Trypanosoma cruzi strains. Therefore, there is an urgent need to develop new safe and efficacious antichagasic drugs. CPY51, also called sterol 14±-demethylase, is a target that has gained much attention in the past years. CYP51 is a critical enzyme in the CYP450 superfamily that synthesizes sterols, which are essential to the integrity of parasite membranes. Inhibiting this enzyme could thus reduce the number of CDcarrying parasites, in turn decreasing the prevalence of CD. Computational methods have proven invaluable to discovering CYP51 inhibitors, as they accelerate drug development and save money and other resources. Quantitative structure-activity relationship (QSAR) modeling is a computational approach that has been widely employed in academia and industry due to its reliability, efficiency, and low cost. In this work, we will (i) compile, curate, and integrate the largest CYP51 bioactivity dataset in the global domain; (ii) generate QSAR models to predict CYP51 inhibition following the best practices for model development and validation; (iii) virtually screen the ENAMINE REAL library, which contains 22 billion compounds, and select potential hits for experimental evaluation; and (iv) experimentally validate selected virtual hits in collaboration with Dr. Carolina Borsoi de Moraes/ICB-USP. All curated data, generated models, and virtual hits will be described in a publication and made publicly available via GitHub for use by the scientific community. (AU)