In silico prediction and in vitro assessment of novel heterocyclics with antimalarial activity

Author:

Orozco Martha Ilce,Moreno Pedro,Guevara Miguel,Abonia Rodrigo,Quiroga Jairo,Insuasty Braulio,Barreto Mauricio,Burbano Maria Elena,Crespo-Ortiz Maria del PilarORCID

Abstract

AbstractThe development of new antimalarials is paramount to keep the goals on reduction of malaria cases in endemic regions. The search for quality hits has been challenging as many inhibitory molecules may not progress to the next development stage. The aim of this work was to screen an in-house library of heterocyclic compounds (HCUV) for antimalarial activity combining computational predictions and phenotypic techniques to find quality hits. The physicochemical determinants, pharmacokinetic properties (ADME), and drug-likeness of HCUV were evaluated in silico, and compounds were selected for structure-based virtual screening and in vitro analysis. Seven Plasmodium target proteins were selected from the DrugBank Database, and ligands and receptors were processed using UCSF Chimera and Open Babel before being subjected to docking using Autodock Vina and Autodock 4. Growth inhibition of P. falciparum (3D7) cultures was tested by SYBR Green assays, and toxicity was assessed using hemolytic activity tests and the Galleria mellonella in vivo model. From a total of 792 compounds, 341 with good ADME properties, drug-likeness, and no interference structures were subjected to in vitro analysis. Eight compounds showed IC50 ranging from 0.175 to 0.990 µM, and active compounds included pyridyl-diaminopyrimido-diazepines, pyridyl-N-acetyl- and pyridyl-N-phenyl-pyrazoline derivatives. The most potent compound (UV802, IC50 0.178 µM) showed no toxicophoric and was predicted to interact with P. falciparum 1-cysperoxidredoxin (PfPrx1). For the remaining 7 hits (IC50 < 1 μM), 3 showed in silico binding to PfPrx1, one was predicted to bind the haloacid dehalogenase-like hydrolase and plasmepsin II, and one interacted with the plasmodial heat shock protein 90.

Funder

Universidad del Valle

University of the Valley

Publisher

Springer Science and Business Media LLC

Subject

Infectious Diseases,Insect Science,General Veterinary,General Medicine,Parasitology

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. MalariaFlow: A comprehensive deep learning platform for multistage phenotypic antimalarial drug discovery;European Journal of Medicinal Chemistry;2024-11

2. AI in Predictive Toxicology;Advances in Medical Technologies and Clinical Practice;2024-09-27

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