How can enzyme inhibition be successfully translated to cell-based assays?

• Grant number: 21/01633-3
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: November 01, 2021
• End date: July 02, 2025
• Field of knowledge: Physical Sciences and Mathematics - Chemistry
• Principal Investigator: Carlos Alberto Montanari
• Grantee: Rafael da Fonseca Lameiro
• Host Institution: Instituto de Química de São Carlos (IQSC). Universidade de São Paulo (USP). São Carlos , SP, Brazil

Abstract

New treatments for neglected tropical diseases are needed, and peptidomimetic compounds, which inhibit cysteine proteases and are more stable than peptides, show great promise as new oral drugs, more effective and with fewer side effects than current treatments. Recent studies have shown that some compounds of this class, despite having great inhibitory activity for enzymes, have not been shown to be active against parasites in in vitro assays. This may be due to physicochemical properties not optimized for biological activity, which compromises the progress of the research to the next steps, involving in vitro and in vivo assays. In this work, we propose the use of advanced methods of computational chemistry and cheminformatics to elucidate the causes behind this lack of activity translation. We will evaluate the physicochemical properties of inactive compounds, as well as the structures of several active compounds and propose new structures with potential activity against parasites such as Trypanosoma cruzi and Leishmania spp. For this, we will use data analysis methods, machine learning and molecular modeling, to visualize the chemical space and create structure-activity relationship models in order to predict the activity of virtually generated compounds, synthesizing and evaluating the biochemical activity of the most promising ones. Thus, we intend to simultaneously enrich the chemical space of compounds that are active against cysteine proteases and against parasites that infect humans. (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

KRENN, MARIO; AI, QIANXIANG; BARTHEL, SENJA; CARSON, NESSA; FREI, ANGELO; FREY, NATHAN C.; FRIEDERICH, PASCAL; GAUDIN, THEOPHILE; GAYLE, ALBERTO ALEXANDER; JABLONKA, KEVIN MAIK; et al. SELFIES and the future of molecular string representations. PATTERNS, v. 3, n. 9, p. 27-pg., 2022-09-09. (21/01633-3)

LAMEIRO, RAFAEL F.; MONTANARI, CARLOS A.. Investigating the Lack of Translation from Cruzain Inhibition to Trypanosoma cruzi Activity with Machine Learning and Chemical Space Analyses. CHEMMEDCHEM, v. N/A, p. 13-pg., 2023-02-03. (21/01633-3, 13/18009-4)

BONATTO, VINICIUS; LAMEIRO, RAFAEL F.; ROCHO, FERNANDA R.; LAMEIRA, JERONIMO; LEITAO, ANDREI; MONTANARI, CARLOS A.. Nitriles: an attractive approach to the development of covalent inhibitors. RSC MEDICINAL CHEMISTRY, v. 14, n. 2, p. 18-pg., 2022-11-07. (21/01633-3, 20/04653-2, 18/15904-6)