Molecular modeling of the Toxoplasma gondii adenosine kinase inhibitors

Subject Areas : Biotechnological Journal of Environmental Microbiology

Taraneh Zandi Asadabadi ^{1 *}

1 - Department of Microbiology, Faculty of Basic Sciences, Lahijan Branch, Islamic Azad University (IAU), Lahijan, Guilan, Iran

Received: 2022-03-10 Accepted : 2022-04-18 Published : 2022-03-01

Keywords: Adenosine Kinase, Drug Design, Toxoplasma Gondii, QSAR modeling, ADME properties,

Abstract :

Computer-assisted approaches might be seen as a bridge to novel medication discoveries. In 2014, the World
Health Organization declared antibiotic resistance in microorganisms to be a major global threat due to which
simple diseases that were formerly manageable have now become deadly infections. Microbial resistance is a
form of drug resistance in which a microorganism may live even when antibiotics are present in the environment.
Toxoplasmosis is a major worldwide parasitic infection caused by Toxoplasma gondii. Since Toxoplasma
gondii is not capable of purine synthesis, the protein adenosine kinase (EC.2.7.1.20) is an important enzyme
in its life pathway. Therefore, Toxoplasma gondii adenosine kinase has recently been considered a target for
developing anti-Toxoplasma agents. This study aimed to develop a 3D QSAR model to predict the activity of
adenosine kinase inhibitors in Toxoplasma gondii and to find new potent inhibitors. Acceptable values of 0.98,
0.83, and 0.91 were observed for the goodness of fit (R2), internal cross-validation (Q2), and external cross-validation
(R2pred) indices, respectively. The robustness of the model was confirmed by applying the Y-scrambling
analysis, and values of ~ 0.18 and ~ 0.0025 were observed for R2intercept and Q2intercept, respectively. This
confirmed that indices calculated for the original model were not based on the chance correlation between independent
and dependent variables. Following the structural virtual screening, new ligands were proposed using
the SwissSimilarity web tool and the ZINC database. The SwissADME web tool was used to predict the pharmacokinetic
properties of the new compounds, and a promising compound was suggested for further research.