Bioorganic & medicinal chemistry letters
Jun 16, 2016
The present study describes the synthesis of two new series of 3-hydroxy-N-(4-oxo-2-phenyl-1,3-thiazinan-3-yl)-8-(trifluoromethyl)quinoline-2-carboxamide derivatives (4a-j) and 3-((7-chloroquinolin-4-ylamino)methyl)-2-phenyl-1,3-thiazinan-4-one deriv...
International journal of computational biology and drug design
Apr 13, 2015
Machine learning techniques have been widely used in drug discovery and development in the areas of cheminformatics. Aspartyl aminopeptidase (M18AAP) of Plasmodium falciparum is crucial for survival of malaria parasite. We have created predictive mod...
BACKGROUND: Early diagnosis is key to reducing the morbi-mortality associated with P. falciparum malaria among international travellers. However, access to microbiological tests can be challenging for some healthcare settings. Artificial Intelligence...
International journal of molecular sciences
Dec 2, 2021
The parasite species of genus causes Malaria, which remains a major global health problem due to parasite resistance to available Antimalarial drugs and increasing treatment costs. Consequently, computational prediction of new Antimalarial compounds...
Increasing reports of multidrug-resistant malaria parasites urge the discovery of new effective drugs with different chemical scaffolds. Protein kinases play a key role in many cellular processes such as signal transduction and cell division, making ...
European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
Mar 1, 2020
The Malaria burden was an escalating global encumbrance and need to be addressed with critical care. Anti-malarial drug discovery was integrated with supervised machine learning (ML) models to identify potent thiazolyl-traizine derivatives. This assi...
BACKGROUND: Retrospective exploratory analyses of randomised controlled trials (RCTs) seeking to identify treatment effect heterogeneity (TEH) are prone to bias and false positives. Yet the desire to learn all we can from exhaustive data measurements...
Malaria is an infectious disease that affects over 216 million people worldwide, killing over 445,000 patients annually. Due to the constant emergence of parasitic resistance to the current antimalarial drugs, the discovery of new drug candidates is ...
SAR and QSAR in environmental research
Aug 1, 2019
The large collection of known and experimentally verified compounds from the ChEMBL database was used to build different classification models for predicting the antimalarial activity against . Four different machine learning methods, namely the supp...
SAR and QSAR in environmental research
Dec 1, 2018
A series of antifolate compounds, i.e. 1-(4-chlorophenyl)-6,6-dimethyl-1,3,5-triazine-2,4-diamine, or cycloguanil analogues, have shown effective inhibiting properties against Plasmodium falciparum dihydrofolate reductase (PfDHFR). In this work, the ...